Mapping the Global Research Landscape of Mitophagy in Parkinson's Disease: A Bibliometric and Visualization Analysis

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However, no dedicated bibliometric analysis of mitophagy in PD exists. This study used data from the Web of Science Core Collection to map the global research landscape of mitophagy in PD. The analysis of 1,578 publications (2007–2024) identifies the United States as the most productive country. McGill University ranks as the top institution, and Nobutaka Hattori is the most prolific author. The journal Autophagy is the journal with the highest number of publications in this field. Core research themes included PINK1/Parkin, mitochondrial quality control, α-synuclein, neuroinflammation, and ferroptosis. The study provides insights into the current status of global collaboration and translational progress in this field. Future efforts should aim to further explore new pathways, enhance clinical translation, and promote collaborative partnerships to advance research and address challenges in the field. Parkinson’s disease Mitophagy Bibliometric analysis PINK1/Parkin Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 Introduction Parkinson's disease (PD), recognized as the fastest-growing neurodegenerative disorder globally, currently affects over 11.7 million individuals worldwide[ 1 ]. Characterized by progressive motor dysfunction and debilitating non-motor symptoms, PD imposes substantial socioeconomic burdens, evidenced by the $ 51.9 billion total economic burden recorded in the U.S. in 2017[ 2 ]. Global projections indicate a concerning 1.5-fold increase in PD prevalence by 2035, primarily driven by demographic aging trends[ 1 ]. While epidemiological studies highlight geographical variations in disease burden, China's projected contribution to the global PD population warrants particular attention, with estimates suggesting it may account for nearly half of worldwide cases by 2030[ 3 ]. This escalating public health challenge underscores the urgent need for multinational collaborative research and innovative therapeutic strategies. Neuropathologically, PD is characterized by the progressive loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) and the accumulation of misfolded α-synuclein in Lewy bodies and lewy neurites[ 4 , 5 ]. Although the etiology of PD has not yet been fully elucidated, accumulating evidence indicates that mitochondrial dysfunction plays a central role in disease progression. Mitochondria, as highly multifunctional organelles, are critical for neuronal survival due to the essential requirement of their structural integrity for cellular homeostasis. Notably, the pioneering discovery by Schapira's team in 1989 first reported significantly reduced activity of mitochondrial respiratory chain Complex I in postmortem brain tissues of PD patients, establishing an important molecular link between mitochondrial impairment and PD pathogenesis[ 6 ]. This discovery established the fundamental basis for the "mitochondrial deficiency hypothesis". Subsequent genetic investigations have further corroborated this framework by demonstrating direct associations between pathogenic mutations in mitochondrial quality control genes (notably PINK1 and Parkin) and familial PD cases[ 7 , 8 ]. Notably, PD animal models induced by mitochondrial toxins (e.g., MPTP and rotenone) closely recapitulate human pathological features, further validating the causal relationship between mitochondrial dysfunction and PD pathogenesis[ 9 ]. The accumulation of damaged mitochondria can trigger neuronal death, highlighting the importance of efficient mitochondrial quality control mechanisms[ 10 ]. Mitophagy, the targeted degradation of mitochondria via autophagy, is a key process for maintaining cellular health[ 11 ]. The pathogenesis of PD is closely associated with dysfunctional mitophagy, a process precisely regulated through both PINK1/Parkin-dependent and -independent pathways. Upon mitochondrial membrane potential dissipation, PINK1 accumulates on the outer mitochondrial membrane and activates Parkin's E3 ubiquitin ligase activity, which marks damaged mitochondria for autophagosome recruitment. PD-associated PINK1 or Parkin mutations disrupt this quality control mechanism, leading to toxic mitochondrial accumulation and accelerated dopaminergic neurodegeneration[ 12 ]. In addition to genetic determinants, environmental factors and aging critically impair mitophagic function. With advancing age, the progressive decline in mitochondrial function and reduced autophagic capacity lead to intracellular accumulation of damaged mitochondria, which may constitute a key pathogenic mechanism in PD[ 13 ]. In PD therapeutic research, intervention strategies targeting mitophagy have gradually become an important research direction. For example, drugs such as Pramipexole have been found to alleviate neuronal damage by activating mitophagy-related signaling pathways[ 14 ]。Furthermore, several recently developed small-molecule compounds, such as those activating PINK1 or Parkin, have demonstrated potential for enhancing mitophagy in preclinical models, offering new therapeutic prospects for PD[ 15 ]. In conclusion, mitophagy plays a central role in the pathogenesis of PD. Elucidating the regulatory mechanisms of mitophagy and its dysfunction in neurodegenerative contexts not only deepens our understanding of PD pathology, but also establishes a critical theoretical framework for developing novel therapeutic interventions targeting mitochondrial quality control. The growing scientific interest in mitophagy's role in PD pathogenesis underscores the critical need for systematic literature analysis. Comprehensive evaluation of research evolution is essential for understanding how research trends have evolved, identifying gaps in knowledge, and guiding future research efforts. In contrast to traditional reviews, bibliometric analysis provides distinct methodological advantages: it enables efficient processing of large-scale literature datasets, quantitative identification of research hotspots through citation network analysis, and visual mapping of conceptual relationships, thereby eliminating the need for labor-intensive manual article evaluations. This study employs integrated bibliometric and scientometric visualization techniques to systematically examine global research patterns in PD-related mitophagy through 2024. By analyzing publication metrics, citation networks, and collaborative patterns, our approach traces the historical development of mitophagy research while identifying emerging therapeutic paradigms. It serves as a valuable roadmap for researchers, clinicians, and funding agencies, while also emphasizing the significant achievements and collaborative efforts that have influenced this field of study. Materials and methods Data Collection This study primarily utilized the Web of Science Core Collection (WoSCC; Clarivate Analytics, USA) - the gold-standard multidisciplinary citation index encompassing over 34,000 peer-reviewed journals across 254 research categories since 1900 - to ensure rigorous bibliometric analysis of high-impact scientific literature. (Platform access: https://www.webofscience.com/wos ). To systematically map the global research landscape of mitophagy in PD, the following search formula was applied: TS=(Parkinson* OR PD) AND TS=(mitophagy OR "mitochondrial autophagy"). The search was limited to articles and reviews published up to December 2024. The final search was conducted on January 12, 2025, to ensure inclusion of the most recent publications and to prevent data bias due to database updates. A total of 1712 documents were retrieved. The initial search yield was filtered to include only English-language publications. Editorial material, book chapters, early access, meeting abstract, proceeding paper, correction, letter, data paper, publication with expression of concern, and retracted publication were excluded. The final dataset comprised articles and reviews articles that specifically addressed aspects of mitophagy in the context of PD. Bibliometric Analysis To strengthen the validity and multidimensional scope of our investigation, we employed several bibliometric tools to uncover trends and patterns within this field. CiteSpace, a software developed by Chaomei Chen, was pivotal in visualizing the co-citation and co-authorship networks, as well as tracking the evolution of key terms within the field[ 16 ]. Our utilization of CiteSpace 6.4. R1 allowed us to delve into hotspots countries, dual-map overlays of journals, keyword timelines, and co-citation analyses. In conjunction with CiteSpace, VOSviewer, developed by Nees Jan van Eck and his team, was instrumental in the bibliometric network graph analysis[ 17 ]. In this study, we utilized VOSviewer (version 1.6.20; Centre for Science and Technology Studies, Leiden University, The Netherlands) to visualize the distribution of countries, institutions, and journals, and to construct co-authorship and keyword co-occurrence networks. The clustering algorithm of VOSviewer, which is based on a similarity matrix and the VOS mapping technique, enabled the automated clustering process. We also employed Pajek (version 5.18; developed by Andrej Mrvar and Vladimir Batagelj, Faculty of Computer and Information Science, University of Ljubljana) in conjunction with VOSviewer. Pajek is an advanced tool for network analysis, specializing in the visualization and management of large-scale networks[ 18 ]. In our research, Pajek was used to calculate and optimize graph data and correlation networks, thereby enhancing the clarity and interpretability of the network visualizations. To further enhance our analysis, we employed Bibliometrix, an R-based tool, to examine key bibliometric data[ 19 ]. For the visualization and predictive modeling of publication trends over time, including both annual and predicted publication volumes, we utilized OriginPro 2024 software (OriginLab Corporation, 2024). Ethical Considerations This study is a bibliometric analysis, and all data were obtained from publicly available academic database. As the research did not involve human or animal experimentation, personal data collection, or sensitive information, ethical approval was not required. All data were aggregated and analyzed in compliance with database terms of use, copyright regulations, and academic integrity standards to ensure the transparency and reproducibility of the study. Results Literature Overview Following the screening protocol and publication search process depicted in Fig. 1 , we identified 1,578 publications related to mitophagy in PD, including 1,082 articles and 496 reviews. Using Bibliometrix, we conducted a detailed bibliometric analysis, revealing a 34.79% annual growth rate and a robust body of literature. A total of 7,428 authors contributed to these publications in 453 sources. There are only 33 single-authored documents, and the average number of co-authors per document is 6.9, highlighting the strong collaborative spirit in this research area. Furthermore, the international co-authorship rate is 26.43%, demonstrating significant global research collaboration. The average age of a document is 6.25 years, and the average citation count per document is 72.85, indicating that this field has an active and influential position in the scientific community. Publication Outputs and Trends Figure 2 A shows the annual and cumulative publication trends from 2007 to 2024. The first publication appeared in 2007, and since then, the number of publications has increased significantly, reaching a peak of 178 publications in 2021. The cumulative publications, shown by the dark blue line, demonstrate a steady upward trend, reflecting the growing body of research in this area. Analysis of Countries/Regions and Cooperation Relationships Currently, a total of 69 countries/regions are actively researching mitophagy in PD, with a significant focus in the Northern Hemisphere, especially in North America, Europe, and parts of Asia. This distribution reflects the global pattern of scientific research output, as nations with advanced scientific infrastructures mainly exist in these areas. Table 1 presents the top 10 countries/regions in terms of publication volume, along with centrality measures that highlight their crucial roles in the research network. The betweenness centrality of these countries/regions measures their significance as intermediaries, emphasizing their connectivity and influence. Moreover, the total link strength, which indicates the overall robustness of a country/region's connections in the research network, is also included in Table 1 . This metric not only represents the number of collaborations but also the intensity of these partnerships, providing a comprehensive view of each country/region's research involvement and impact. The United States (USA) emerges as the leading contributor with a total publication volume of 479 and a high intermediary centrality of 0.58, indicating its pivotal role in the global research network and its influence in shaping the field of mitophagy research in PD. "Mechanisms of Mitophagy," authored by Richard J. Youle and Derek P. Narendra and featured in Nature Reviews Molecular Cell Biology in 2011, is the most highly cited article in the USA with an outstanding 2488 citations. This article has been pivotal in shaping the discourse within the field of cellular biology, particularly in the realm of mitophagy—the selective degradation of mitochondria. Its thorough analysis of the molecular mechanisms underlying mitophagy has exerted a profound influence on subsequent research, significantly enhancing our comprehension of the process's role in maintaining cellular homeostasis and its implications in neurodegenerative diseases, notably PD. By elucidating the functions of critical proteins such as PINK1 and parkin, the article has established a foundational framework for future therapeutic strategies aimed at modulating mitophagy[ 20 ].China, with 353 publications and an intermediary centrality of 0.13, also figures prominently, reflecting its growing impact on global scientific discourse. England (170 publications) and Germany (122 publications) further underscore the significant European contribution to this research domain. However, the lower intermediary centrality values for these countries suggest that while their research output is increasing, their role in bridging international collaborations could be further enhanced. To further elucidate the landscape of international collaboration, Fig. 3 B presents a chord diagram showcasing the intricate network of co-authorships among the top 25 countries contributing to research on mitophagy in PD. Figure 3 C provides an overview of the top 9 countries with the strongest citation bursts, sorted by the start time of their respective bursts. A citation burst signifies a period during which a country's scientific publications receive a sudden and significant increase in citations. The USA began its significant burst in 2007, while China and India both demonstrate notable bursts from 2022 to 2024, with China's burst strength reaching 20.96. These bursts reflect critical periods of intense research activity and influence within the field. Figure 3 D presents the annual publication trends for the USA, China, and India, which are among the countries with the highest publication volumes and significant citation bursts. The USA shows a consistent increase in publication numbers over the years, with fluctuations but an overall upward trend, peaking around 2022. China's trend shows a steady rise from 2018 onwards, aligning with the table data that indicates a period of rapid growth in research output and influence. India, starting with a lower base,shows a gradual increase in publications, with a more pronounced rise from 2020. Table 1 Top 10 Countries/regions by publication volume including centrality and total link strength Rank Countries/regions Publications Centrality Total link strength 1 USA 479 0.58 312 2 China 353 0.13 102 3 England 170 0.24 188 4 Germany 122 0.08 153 5 Italy 121 0.09 99 6 Canada 95 0.12 90 7 Japan 89 0.03 31 8 India 63 0.05 26 9 South Korea 62 0.04 19 10 Spain 49 0.08 61 Analysis of and Institutional Cooperations Table 2 ranks the top 10 institutions by publication count in mitophagy research related to PD. The data encompasses institutions from various countries, highlighting the global distribution of research efforts in this domain. The institutions are listed according to their publication count, with McGill University from Canada leading the chart with 52 publications. University College London (UK) and the University of Pittsburgh (USA) follow with 45 and 38 publications, respectively. The USA is the most represented country with four institutions, followed by Germany with two. Citation counts vary significantly among the institutions. The National Institute of Neurological Disorders and Stroke (USA) stands out with the highest citation count of 10,427, highlighting its substantial influence on the field. We conducted an in-depth analysis of the content of these influential papers. Among them, the second most cited article, following the previously mentioned work by Richard J. Youle, is "PINK1 is selectively stabilized on impaired mitochondria to activate Parkin"[ 21 ] by Derek P. Narendra, with 2,205 citations. PINK1 stabilizes on damaged mitochondria, recruiting Parkin to trigger autophagy. Voltage-dependent proteolysis regulates PINK1 levels, keeping them low on healthy mitochondria but high on damaged ones. Mutations in PINK1 and Parkin disrupt this process, affecting mitophagy and explaining their genetic interaction in flies. Total link strength, which measures the strength of connections within the research network, shows that University College London has the highest collaborative engagement with a score of 128. This suggests a strong network of co-authorships and partnerships. Figure 4 A presents an institutional collaboration network map generated using VOSviewer. This network comprises 180 institutions, each depicted as a node, selected based on their publication of at least five papers, while excluding those lacking collaborative ties with other institutions. The resultant chart delineates five distinct clusters, with each node's color corresponding to its specific group. The node size is proportional to the number of publications, thereby accentuating institutions with a higher research output. The thickness of the lines connecting the nodes reflects the extent of collaboration, with thicker lines signifying more frequent cooperative interactions. Upon analyzing the network, it is evident that certain institutions occupy central positions within the diagram, indicating their crucial role in the overall collaborative framework. These central nodes, distinguished by their larger size and numerous connections, likely represent key research hubs actively involved in knowledge exchange and collaborative research initiatives. It is also apparent that institutions with close collaborative relationships predominantly belong to the same country. Figure 4 A presents a scholarly network map of institutional collaborations, featuring nodes of identical size and placement as those in Fig. 4 B, with uniform line thickness indicating the strength of collaborative ties. The distinctive aspect of this visualization lies in its chromatic representation of nodes, which reflects the mean year of publication. Redder shades signify more recent scholarly contributions, while bluer shades denote earlier publication periods. A notable observation within this network is the prevalence of redder nodes among several Chinese institutions, highlighting a recent and substantial surge in research publications. This visual evidence supports the broader trend of exponential growth in China's research productivity in recent years. The prominent red coloration among Chinese institutions underscores a significant escalation in their activity and contributions within the field of mitophagy in PD, indicating a profound shift in the global research landscape. Table 2 Top 10 institutions by publication volume including citations and total link strength Rank Institution Country Publication Citations Total link strength 1 McGill University Canada 52 5329 84 2 University College London UK 45 3791 128 3 University of Pittsburgh USA 38 3953 44 4 Juntendo University Japan 34 4027 55 5 Mayo Clinic USA 30 1752 99 6 Chinese Academy of Sciences China 29 1268 77 7 National Institute of Neurological Disorders and Stroke USA 27 10427 61 8 University of Lübeck Germany 26 1899 72 9 Johns Hopkins University USA 25 4827 83 10 University of Tübingen Germany 23 3506 119 Analysis of Journals Table 3 Top 10 journals in terms of number of publications, corresponding IF (JCR2023) and JCR quartile Rank Journal Publications IF(JCR2023) JCR quartile 1 Autophagy 55 14.6 Q1 2 International Journal of Molecular Sciences 53 4.9 Q1 3 Journal of Biological Chemistry 40 4 Q2 4 Cells 39 5.1 Q2 5 Human Molecular Genetics 32 3.1 Q2 6 Scientific Reports 29 3.8 Q1 7 Molecular Neurobiology 25 4.6 Q1 8 Cell Death & Disease 24 8.1 Q1 9 Frontiers in Neuroscience 23 3.2 Q2 10 Neurobiology of Disease 22 5.1 Q1 When discussing the significance of journal distribution in the field of mitophagy in PD, Bradford's Law offers a crucial perspective. Bradford's Law, introduced by Samuel C. Bradford, describes a specific pattern of journal distribution within scientific literature. According to this law, if journals are sorted by the number of papers they publish on a particular subject, they can be divided into several zones, with each zone containing an equal number of papers, while the number of journals in each zone decreases geometrically, meaning a small number of core journals account for the majority of publications[ 22 ]. We utilized a bibliometric online analysis platform “bibliometirx” to identify journals in the field of mitophagy in PD. Figure 5 illustrates the distribution of core journals. The chart reveals the ranking of journals based on the logarithm of their publication count, with those in the most central area publishing a significant proportion of articles within the field. Figure 6 A displays the number of articles published in core journals in this domain. The bar chart highlights that Autophagy is the leading journal with 55 publications, followed by International Journal of Molecular Sciences (53 publications) and Journal of Biological Chemistry (40 publications). Other notable contributors include Cells and Human Molecular Genetics. Figure 6 B provides additional detail on the number of journals in each zone. Zone 1 has 22 journals, Zone 2 has 75, and Zone 3 has 356. The 22 journals in Zone 1 are the core journals identified in Fig. 5 and Fig. 6 A. These journals have the highest publication volume, indicating their significant influence in the field. Table 4 presents the top 10 journals by number of publications, co-citation frequency, impact factor (IF;JCR 2023), and JCR quartile. Autophagy tops the list with 55 publications and an IF of 14.6, ranking in JCR Q1. International Journal of Molecular Sciences and Journal of Biological Chemistry follow, with IF of 4.9 and 4, respectively. These journals lead in both publication volume and impact factor, underscoring their key role in disseminating research findings. This analysis underscores the importance of these core journals as primary conduits for knowledge dissemination within the field, guiding researchers in selecting where to publish their work for maximum academic impact. The VOSviewer visualization (Fig. 7A) maps journals publishing mitophagy-related literature and their interrelationships. Journals are clustered into four categories based on similarity. Cluster 1 (Red) includes journals focusing on foundational medical research, neuroscience, cell biology, pharmacology, and toxicology, covering disease mechanisms, drug development, and cellular processes. Cluster 2 (Green) comprises journals rich in molecular biology, genetics, molecular neuroscience, and biochemistry, addressing molecular mechanisms, genetic diseases, and biochemical processes. Cluster 3 (Blue) encompasses journals delving into biochemistry, molecular biology, cell biology, and immunology, emphasizing cell signaling and immune responses. Cluster 4 (Yellow) bridges materials science, applied sciences, cellular metabolism, neuroscience, and stem cell research, highlighting biomaterials, cellular energy metabolism, neurodegenerative diseases, and stem cell therapies. These clusters underscore the interdisciplinary nature of current research and cross-field collaborations. Figure 7B focuses on the average normalized citations (avg.norm.citations) metric, visualized by color intensity. Deeper red indicates higher citation frequency, while bluer hues signify lower citation rates. This metric reflects journals' academic influence and significance within their fields. Journals like Nature , Journal of Cell Biology , Molecular Cell and Neuron appear in deep red, denoting higher average citation counts and thus prominent status and broad impact. Despite not having the largest nodes, their red color underscores their respected and influential position in academia. We utilized knowledge flow analysis to examine the citation and co-citation dynamics between citing and cited journals. The dual-map overlay (Fig. 8 ) illustrates the topic distribution, citation trajectory changes, and shifts in research foci across journals. The left side labels citing journals, and the right side labels cited journals. Colored curves depict knowledge flow from citing to cited journals, underscoring inter-field connectivity and influence[ 23 ].For instance, the curve connecting "MOLECULAR BIOLOGY IMMUNOLOGY" with "MOLECULAR BIOLOGY GENETICS" suggests a significant citation relationship and knowledge flow between these two fields. Analysis of authors Figure 9 illustrates a comparison between the predicted distribution of document productivity among authors in the field of mitophagy in PD, based on Lotka's Law (yellow area), and the actual distribution (red line). For authors with a single publication, the predicted proportion is 62%, but the observed proportion is much higher at 78.6%. This suggests that more authors than expected produce only one publication in this field. For authors publishing two or more documents, the actual proportion is lower than the predicted value, indicating that Lotka's Law may overestimate the number of highly prolific authors in this specific field. Table 3 offers an overview of the academic influence and institutional affiliations of the top ten authors. Hattori Nobutaka tops the list with 28 publications and 3,731 citations, underscoring his substantial impact. Richard J.Youle, with 20 publications and 12,235 citations, demonstrates exceptional influence despite fewer publications. The table also highlights authors from prestigious institutions like the University of Tübingen and McGill University, each with two representatives in the top ten, reflecting these institutions' robust research contributions. Authors such as Springer Wolfdieter and Edward A. Fon, with high total link strength, emerge as key collaborators. These authors and institutions play a leading role in advancing the field. The co-authorship network map (Fig. 10 A) vividly illustrates the collaborative landscape among researchers. Node size reflects an author's contribution, with larger nodes indicating higher publication counts or central collaborative roles, exemplified by Hattori Nobutaka and Richard J. Youle. Node colors differentiate clusters, highlighting groups of frequent co-authors and suggesting strong ties within specific research teams or thematic areas. Connecting lines denote co-authorship relationships, with closely positioned nodes, such as Edward A. Fon and Jean-Francois Trempe, indicating potential research partnerships. Figure 10 B uses average normalized citations as the metric. The visualization employs a color gradient, with darker red shades indicating higher academic impact. Prominent authors such as Richard J. Youle, Springer Wolfdieter, Hattori Nobutaka and Edward A. Fon are highlighted, reflecting their influential contributions and frequent citations. The map also shows small, emerging networks. Though currently limited, they could signal new directions and grow into larger clusters. Monitoring them is crucial for future breakthroughs. Figure 11 A focuses authors with at least eight publications, excluding isolated nodes. It highlights active collaborators, with clusters indicating closely working groups and lines showing collaborative ties. Central authors serve as key connectors. This map provides a clear view of leading scholars' collaborative relationships. Figure 11 B shows the same network with nodes colored by average publication year. Blue to red gradients indicate older to newer publications. Red nodes highlight recent activity, while blue nodes show older contributions. This helps identify the most active contributors in recent years. Table 3 Top 10 authors in terms of number of publications Rank Author Number of publication Ciations total link strength Institutions 1 Hattori Nobutaka 28 3731 229 Juntendo Univ 2 Edward A. Fon 26 3252 184 McGill Univ 3 Springer Wolfdieter 26 3918 273 Mayo Clinic 4 Fabienne C. Fiesel 23 3739 256 Mayo Clinic 5 Richard J. Youle 20 12235 101 NINDS 6 Charleen T. Chu 19 1585 55 Univ Pittsburgh 7 Christine Klein 19 1544 188 Univ Lubeck 8 Noriyuki Matsuda 17 3280 121 Tokyo Metropolitan Inst Med Sc 9 Anne Gruenewald 16 1744 171 Univ Luxembourg 10 Jean-Francois Trempe 16 829 120 McGill Univ Analysis of Keyword and topic Table 4 Top 20 keywords in mitophagy research in PD with occurrences and total link strength Rank Keyword Occurrences Total link strength 1 mitophagy 600 3272 2 parkinson's disease 467 2423 3 mitochondria 355 1910 4 parkin 266 1468 5 autophagy 250 1370 6 pink1 220 1243 7 neurodegeneration 140 836 8 mitochondrial dysfunction 87 440 9 oxidative stress 85 509 10 mitochondrial dynamics 77 429 11 parkinson disease 73 436 12 ubiquitin 70 394 13 alpha-synuclein 64 391 14 alzheimer's disease 58 374 15 apoptosis 57 315 16 aging 47 284 17 mitochondrial quality control 42 232 18 neurodegenerative diseases 39 218 19 park2 34 210 20 mitochondrial biogenesis 32 204 Keywords offer a snapshot of key research themes. Table 4 lists the top 20 keywords by frequency. The most common are “mitophagy” (600), “parkinson's disease” (467), “mitochondria” (355), and“parkin” (266), indicating that these areas are trending in current research. A co-occurrence network diagram of keywords visualized in VOSviewer (Fig. 12 A) reveals seven major clusters based on research themes. The first cluster addresses the multifactorial pathogenesis of PD, including oxidative stress, mitochondrial dysfunction, and neuroinflammation. The second cluster focuses on the Pink1/Parkin signaling pathway and its role in mitophagy and disease pathology. The third cluster examines the interplay between mitochondrial dysfunction and protein aggregation. The fourth cluster highlights the relationship between calcium signaling and mitochondrial damage. The fifth cluster explores mitophagy and oxidative stress mechanisms and their therapeutic potential. The sixth cluster investigates genetic mechanisms and potential therapeutic targets. The seventh cluster delves into protein aggregation and autophagy mechanisms. In CiteSpace, the timeline graph (Fig. 12 B) shows the most frequently occurring keywords for each of the nine thematic clusters over time: #0 (dysfunction), #1 (Alzheimer’s disease), #2 (ubiquitin), #3 (mitochondrial quality control), #4 (mitochondrial biogenesis), #5 (fission), #6 (vulnerability), #7 (mitogen-activated protein kinases, MAPKs), and #8 (mitochondrial function). The analysis revealed distinct temporal patterns: Clusters #0, #1, #2, #3, and #4 exhibited uniformly distributed nodes across the entire timeline, indicating their roles as persistent research themes, with #2 (ubiquitin) and #3 (mitochondrial quality control) showing prominent node sizes during 2007–2010, suggesting foundational focus on ubiquitin-mediated degradation pathways and proteostatic regulation. In contrast, clusters #6, #7, and #8 displayed sparse node distributions. Notably, cluster #1 (Alzheimer’s disease) spanned the full timeline, underscoring enduring interdisciplinary investigations into shared mitochondrial dysregulation mechanisms between neurodegenerative disorders. The trend topic chart (Fig. 13 ) generated by Bibliometrix illustrates the evolution and popularity of research themes. The size of each dot reflects the prevalence of a specific research focus over time. Terms like "neuroinflammation" and "ferroptosis" show increasing trends, highlighting emerging areas of interest. This reflects growing recognition of the complex interplay between mitochondrial dysfunction and other cellular processes, such as inflammation and regulated cell death, in PD pathogenesis. The increasing frequency of these terms may indicate a shift in research focus towards understanding the multifaceted mechanisms underlying neurodegenerative processes and identifying potential therapeutic targets. Figure 14 A presents an annual heatmap analysis of research keywords from 2007 to 2024, visualizing the annual popularity of each keyword. This popularity is calculated by dividing the number of citations for that keyword in a specific year by the total number of citations for that year. In the last two years, keywords such as "pink1/parkin," "neuroinflammation," "neuroprotection," "dopaminergic neuron," "usp30," "mitochondrial fission," "mitochondrial dysfunction," "prkn," "ferroptosis," "mptp," "caenorhabditis elegans," "ageing," "fibroblasts," "lysosomes," and "reactive oxygen species" have become hot topics. Figure 14 B illustrates a high degree of correlation among keywords within the research field of mitophagy in PD. This high correlation suggests that the research topics in this field are closely interconnected and likely revolve around several core concepts or issues. This could imply that researchers are generally focused on similar scientific questions and employ similar theoretical frameworks and methodologies.Furthermore, this high degree of correlation may indicate that the research trends in this field are relatively stable, with researchers consistently focusing on certain hot topics rather than frequently shifting their research focus. This could reflect the maturity of the field, where some key issues have gained widespread ecognition and in-depth study. However, despite the generally high correlation between most keywords, there may still be some keywords or themes with lower correlation. These keywords with lower correlation might represent emerging areas of research or potential research gaps that warrant further exploration. Highly cited publications Table 5 Top 15 high-cited publications related to mitophagy in PD. Rank Authors Article Title Source Title Document Type Times Cited Publication Year DOI 1 Youle, RJ et al. Mechanisms of mitophagy[ 20 ] NATURE REVIEWS MOLECULAR CELL BIOLOGY Review 2487 2011 10.1038/nrm3028 2 Geisler, S et al. PINK1/Parkin-mediated mitophagy is dependent on VDAC1 and p62/SQSTM1[ 24 ] NATURE CELL BIOLOGY Article 2218 2010 10.1038/ncb2012 3 Narendra, DP et al. PINK1 Is Selectively Stabilized on Impaired Mitochondria to Activate Parkin[ 21 ] PLOS BIOLOGY Article 2204 2010 10.1371/journal.pbio.1000298 4 Hou, YJ et al. Ageing as a risk factor for neurodegenerative disease[ 25 ] NATURE REVIEWS NEUROLOGY Review 1737 2019 10.1038/s41582-019-0244-7 5 Pickrell, AM et al. The Roles of PINK1, Parkin, and Mitochondrial Fidelity in Parkinson's Disease[ 26 ] NEURON Review 1558 2015 10.1016/j.neuron.2014.12.007 6 Matsuda, N et al. PINK1 stabilized by mitochondrial depolarization recruits Parkin to damaged mitochondria and activates latent Parkin for mitophagy[ 27 ] JOURNAL OF CELL BIOLOGY Article 1494 2010 10.1083/jcb.200910140 7 Ashrafi, G et al. The pathways of mitophagy for quality control and clearance of mitochondria[ 28 ] CELL DEATH AND DIFFERENTIATION Review 1306 2013 10.1038/cdd.2012.81 8 Dias, V et al. The Role of Oxidative Stress in Parkinson's Disease[ 29 ] JOURNAL OF PARKINSONS DISEASE Review 1303 2013 10.3233/JPD-130230 9 Vives-Bauza, C et al. PINK1-dependent recruitment of Parkin to mitochondria in mitophagy[ 41 ] PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Article 1295 2010 10.1073/pnas.0911187107 10 Chen, HC et al. Mitochondrial dynamics-fusion, fission, movement, and mitophagy-in neurodegenerative diseases[ 30 ] HUMAN MOLECULAR GENETICS Review 1135 2009 10.1093/hmg/ddp326 11 Tanaka, A et al. Proteasome and p97 mediate mitophagy and degradation of mitofusins induced by Parkin[ 31 ] JOURNAL OF CELL BIOLOGY Article 1088 2010 10.1083/jcb.201007013 12 Fang, EF et al. Mitophagy inhibits amyloid-β and tau pathology and reverses cognitive deficits in models of Alzheimer's disease[ 32 ] NATURE NEUROSCIENCE Article 1082 2019 10.1038/s41593-018-0332-9 13 Chen, Y et al. PINK1-Phosphorylated Mitofusin 2 Is a Parkin Receptor for Culling Damaged Mitochondria[ 33 ] SCIENCE Article 1019 2013 10.1126/science.1231031 14 Jin, SM et al. Mitochondrial membrane potential regulates PINK1 import and proteolytic destabilization by PARL[ 34 ] JOURNAL OF CELL BIOLOGY Article 1017 2010 10.1083/jcb.201008084 15 Wang, XN et al. PINK1 and Parkin Target Miro for Phosphorylation and Degradation to Arrest Mitochondrial Motility[ 35 ] CELL Article 910 2011 10.1016/j.cell.2011.10.018 Highly cited reference analysis Table 6 Top 10 highly cited references on Mitophagy in PD: Insights from CiteSpace LBY:5. Rank Article Title Article type Source Authors Year Cited IF(JCR2023) JCR quartile DOI 1 PINK1/Parkin-mediated mitophagy is dependent on VDAC1 and p62/SQSTM1[ 24 ] Article Nature Cell Biology Geisler S 2010 218 17.3 Q1 10.1038/ncb2012 2 PINK1 is selectively stabilized on impaired mitochondria to activate Parkin[ 21 ] Article PLoS Biology Narendra DP 2010 211 7.8 Q1 10.1371/journal.pbio.1000298 3 PINK1-dependent recruitment of Parkin to mitochondria in mitophagy[ 41 ] Article Proceedings of the National Academy of Sciences Vives-Bauza C 2010 176 9.4 Q1 10.1073/pnas.0911187107 4 The roles of PINK1, parkin, and mitochondrial fidelity in Parkinson's disease[ 26 ] Review Neuron Pickrell AM 2015 169 14.7 Q1 10.1016/j.neuron.2014.12.007 5 The ubiquitin kinase PINK1 recruits autophagy receptors to induce mitophagy[ 39 ] Article Nature Lazarou M 2015 161 50.5 Q1 10.1038/nature14893 6 PINK1 stabilized by mitochondrial depolarization recruits Parkin to damaged mitochondria and activates latent Parkin for mitophagy[ 27 ] Article The Journal of Cell Biology Matsuda N 2010 160 7.3 Q1 10.1083/jcb.200910140 7 Ubiquitin is phosphorylated by PINK1 to activate parkin[ 36 ] Article Nature Koyano F 2014 147 50.5 Q1 10.1038/nature13392 8 Parkin is recruited selectively to impaired mitochondria and promotes their autophagy[ 12 ] Article The Journal of Cell Biology Narendra DP 2008 147 7.3 Q1 10.1083/jcb.200809125 9 PINK1 phosphorylates ubiquitin to activate Parkin E3 ubiquitin ligase activity[ 37 ] Article The Journal of Cell Biology Kane LA 2014 133 7.3 Q1 10.1083/jcb.201402104 10 Mitophagy inhibits amyloid-β and tau pathology and reverses cognitive deficits in models of Alzheimer's disease[ 32 ] Article Nature Neuroscience Fang EF 2019 125 21.3 Q1 10.1038/s41593-018-0332-9 Table 6 presents the top 10 most cited references. These references were identified using CiteSpace software, with "Look Back Year (LBY)" parameter set at 5 years. This means that CiteSpace considered the citation status of each paper within 5 years after its publication. The purpose of this setting is to focus more precisely on recent research advancements, streamline the analysis network, and avoid the limitations of earlier studies. This approach helps to more accurately identify and understand key papers and research trends. Among these highly cited papers, 90% are original research articles. A significant portion of these highly cited publications overlaps with the previously mentioned top 15 highly cited publications (see Table 5 ), highlighting their importance and representativeness. Article co-citation analysis reveals the thematic, methodological, or theoretical connections between papers by tracking their co-citation frequency. In CiteSpace (with LBY = 5, see Fig. 15 A and 15 B), each node represents a paper, with its size proportional to co-citation frequency (larger nodes indicate more co-citations) and color mapping to the "citation year" (from cold to warm tones for early to recent citations). Given the LBY = 5 setting, only citations within 5 years post-publication are counted, thus the map reflects short-term academic impact. The large blue nodes in the center of the map (e.g.,papers from 2009–2014) indicate that these papers were highly co-cited within five years of publication. Despite their earlier publication dates, their conclusions or methods continue to influence subsequent research, suggesting they are core theories or classic findings in the field and remain valuable references. Conversely, the large warm-toned (red) nodes on the right represent recently published papers that have been quickly cited in a short period. Their research directions or innovations may signal emerging hotspots or future trends in the field and deserve close attention. Figure 16 A shows the results of a bibliometric analysis using CiteSpace, focusing on cluster dependencies and highlighting the top 50% of these paths. The visualization reveals how one cluster influences another, with arrow directions indicating the flow of influence. For example, an arrow from Cluster B to Cluster A means that Cluster A's development is influenced by Cluster B. Firstly, cluster #0, "Selective Autophagy" is influenced by several other clusters, including "Pink1-associated Parkinson's Disease", "Mitochondrial Dynamics", "SQSTM1 Cooperation", "Mitochondrial Fission", "Cytosolic Pink1", and "Mitochondrial Morphology". This indicates that progress in selective autophagy research is closely tied to these areas, likely intersecting in mechanisms, disease associations, and therapeutic strategies. Secondly, Cluster#2, "Intracellular Organelle" is influenced by several clusters, including "Pink1-associated Parkinson's Disease", "Mitochondrial Dynamics", "SQSTM1 Cooperation", "Mitochondrial Fission" and "Small N-terminal Tag". This highlights the significant interplay between intracellular organelle research and studies on mitochondrial function, morphology, and protein tags. Additionally, both Cluster #5, "Neuronal Damage" and Cluster #6, "Targeting Mitophagy" are influenced by "Pink1-associated Parkinson's Disease" and "E3 Ubiquitin Ligase Parkin." This underscores the importance of Pink1 and Parkin research in understanding neuronal damage and mitophagy targeting. Figure 16 B highlights the top 25 references with the strongest citation bursts. The first two bursts occurred in 2009, with papers titled "Parkin is recruited selectively to impaired mitochondria and promotes their autophagy"[ 12 ] and "The PINK1/Parkin pathway regulates mitochondrial morphology"[ 38 ]. Notably, the paper by Narendra et al. has the strongest burst (strength = 64.35) and its burst duration lasted until 2013. Another high-burst paper is "The ubiquitin kinase PINK1 recruits autophagy receptors to induce mitophagy" by Lazarou et al. (strength = 61.16)[ 39 ]. The data shows that papers published in 2010 caused the most citation bursts (seven in total), indicating a surge in related research activities. Discussion Research Trends and Future Prospects In this study, we utilized a nonlinear fitting curve to elucidate the annual publication growth trajectory of mitophagy research in PD. This trend aligns with the theory of scientific development proposed by Derek J. de Solla Price[ 40 ], which posits that the volume of scientific literature in a particular field will initially exhibit exponential growth before eventually plateauing. Notably, the inflection point of this growth pattern can be traced back to around 2010, a period during which key breakthrough studies laid the foundation for the subsequent establishment of paradigms. For instance, Narendra et al. revealed the mechanism by which PINK1 accumulates on damaged mitochondria and how this accumulation triggers the recruitment of Parkin and mitophagy[ 21 ]. Additionally, the team of Vives-Bauza elucidated how PINK1 and Parkin jointly regulate mitochondrial transport and aggregation, facilitating autophagic degradation in the perinuclear region[ 41 ]. These studies provided the molecular framework for the subsequent rapid growth phase of publications. The current surge in publication numbers indicates that the field has established a dominant paradigm and is in the application phase, characterized by the rapid expansion of knowledge and the widespread dissemination of established theories and methods. This period has benefited from recent in-depth research on PD-related mitochondrial dysfunction, such as the discovery of the interaction between α-synuclein and mitochondria[ 42 ], as well as technological advancements like CRISPR gene editing[ 43 ]. Moreover, policy funding has also been a powerful driving force behind the expansion of this field. By using the search term ("parkinson's disease” AND “mitophagy") to access the official NIH RePORTER database ( https://reporter.nih.gov ), we obtained funding data from 2007 to 2024. The initial funding in 2007 was 5.8 million dollars, which increased to 25 million dollars in 2010 (+ 331%). During the technological breakthrough period from 2011 to 2017, the average annual growth rate was 34.6%, peaking at 853 million dollars in 2017. From 2018 to 2023, during the clinical translation phase, the funding amounts stabilized in the range of 470 to 790 million dollars, reflecting a sustained shift in strategic focus towards therapeutic development. Despite the increase in publication volume, the majority of studies remain at the cellular or animal model stage, with limited clinical validation. The influence and recognition of scientific literature will accumulate over time and eventually stabilize. As shown in Fig. 2 B, the annual publication trend curve for PD-related mitophagy research is flattening. However, these predictions should be treated with caution. Although the nonlinear fitting curve provides robust predictions based on historical data, the dynamic and complex nature of scientific research cannot be overlooked. Actual trends may be influenced by a variety of internal and external factors. External factors include changes in research funding, policy adjustments, or global events, all of which can impact the scientific publication process. Internal factors involve technological advancements in related fields, the evolution of research methods, or shifts in the academic community's research focus. Global Collaboration and Regional Contributions The analysis of global research collaboration on mitophagy in PD reveals a dynamic interplay of productivity, influence, and regional specialization. The United States emerges as the central hub of global collaboration, as evidenced by its highest publication volume (479), betweenness centrality (0.58), and total link strength (312). This underscores its dual role as a primary knowledge producer and a critical nexus for international collaborations. This leadership is reinforced by seminal contributions such as the 2011 review by Richard J.Youle and Derek P. Narendra[ 20 ], which established foundational frameworks for understanding PINK1/Parkin-mediated mitochondrial quality control. While China ranks second in productivity (353 publications), its relatively low betweenness centrality (0.13) and total link strength (102) suggest a focus on domestic or regionally clustered research, indicating a need for deeper integration into global networks. European nations, notably England (170 publications) and Germany (122 publications), demonstrate strong intracontinental collaboration (total link strengths of 188 and 153, respectively). However,their relatively lower centrality values compared to the United States highlight a gap in facilitating cross-regional knowledge exchange. The citation bursts observed in China (2022–2024, strength = 20.96) and India (2022–2024, strength = 14.3) signal shifting dynamics (Fig. 3 C). China’s surge aligns with its strategic investments in neurodegenerative research. In recent years, Chinese scholars have made significant contributions to elucidating the molecular mechanisms and therapeutic strategies targeting mitophagy in PD. In the context of core regulatory pathways, Wang et al. revealed that PTEN-L acts as a novel phosphatase to inhibit PINK1-Parkin-mediated mitophagy through ubiquitin dephosphorylation[ 44 ]. Complementary studies by Huang et al. and Niu et al. further demonstrated the critical roles of metabolic enzymes (PANK2)[ 45 ] and deubiquitinating regulators (USP33)[ 46 ] in modulating PINK1-Parkin signaling, highlighting the dynamic interplay between ubiquitination and mitochondrial quality control. Regarding mitochondrial dynamics, the Chen team systematically established the involvement of Drp1-mediated fission in paraquat-induced neuronal damage[ 47 , 48 ], while Han et al. identified PINK1-dependent phosphorylation of Drp1 at Ser616 as a key modulator of mitochondrial morphology[ 49 ]. In therapeutic development, Liu et al. reported that lovastatin enhances SHP2-mediated mitophagy to alleviate parkinsonism in murine models[ 50 ]. Innovative nanotechnology-driven approaches, such as sequence-targeted lycopene nanodots[ 51 ] and single-atom nanocatalytic platforms[ 52 ], were designed to promote pro-survival mitophagy and suppress neuroinflammation, respectively. Epigenetic studies uncovered non-coding RNA networks, including the circEPS15/miR-24-3p axis[ 53 ] and LncRNA NR_030777[ 48 ], which regulate mitophagy through ATG12 and CDK1 pathways. Notably, Bao et al. proposed a non-canonical mitochondrial quality control mechanism involving mitolysosome exocytosis[ 54 ], whereas Zhang et al. and Han et al. elucidated crosstalk between mitophagy and ferroptosis via NKAα1 inhibition[ 55 ] and Nrf2-mediated lipid peroxidation regulation[ 56 ]. These findings collectively provide a multifaceted framework for understanding PD pathogenesis and advancing mitochondrion-targeted therapies. India’s growth, though starting from a smaller base, reflects rising interest in PD epidemiology and cost-effective therapeutic strategies, such as repurposed mitochondrial enhancers. Annual publication trends (Fig. 3 D) further highlight this geographic diversification: the U.S. maintains steady growth, China exhibits exponential output since 2018, and India shows accelerating contributions post-2020.Recent years have witnessed significant progress from Indian researchers in understanding mitophagy regulation and therapeutic applications in PD. By establishing drosophila models, studies revealed that Rab11 modulates mitochondrial quality control through the Parkin/PINK1 signaling pathway[ 57 ]. Rodent studies demonstrated that pharmacological inhibition of deubiquitinating enzyme USP14 markedly amplified mitophagic activity and alleviated dopaminergic neurodegeneration[ 58 ]. Furthermore, SH-SY5Y cell-based investigations elucidated that andrographolide suppresses NLRP3 inflammasome activation via Parkin-mediated mitophagy[ 59 ]. These findings collectively unravel the complexity of mitophagic networks, providing experimental foundations for developing targeted nanodelivery systems and epigenome-modulating strategies. Institutional Impact and Collaborative Strategies From the perspective of institutional distribution, research on mitophagy in PD exhibits a multipolar pattern, yet with significant geographical concentration. Institutions from North America and Europe dominate the field, with four US institutions ranking in the top ten (National Institute of Neurological Disorders and Stroke[NINDS], University of Pittsburgh, Mayo Clinic, and Johns Hopkins University). Collectively,these institutions account for 51.2% of the total citations among the top ten, with NINDS alone amassing 10,427 citations, thereby underscoring its academic leadership. Among European institutions, University College London (UCL) in the UK stands out as a core hub in the global collaborative network, with a total link strength of 128. Its extensive collaborations likely stem from the integration of clinical resources and fundamental research capabilities. As depicted in the institutional collaboration network (Fig. 4 A), institutions such as University College London (total link strength of 128) and the Mayo Clinic (total link strength of 99) occupy core hub positions. Their extensive collaborative ties indicate that the deep integration of clinical and basic research is pivotal in driving the translation of mitophagy research into therapeutic strategies. However, the collaboration network remains predominantly intra-national clusters (e.g.,US and German institutions forming distinct clusters), suggesting that geographical proximity and shared research funding systems may still be the primary drivers of collaboration, despite the global demand for PD research. The increased activity of Chinese institutions in recent years is evidenced by the concentrated distribution of red nodes (representing recent publications) in Fig. 4 B. The Chinese Academy of Sciences (CAS, 29 publications) stands as a representative of China's research productivity, ranking sixth globally in terms of publication output. It should be noted that the literature inclusion threshold of VOSviewer (≥ 5 publications) may underestimate the collaborative potential of emerging institutions,as there may be initial collaborations in the actual research network that are not visualized. For researchers newly entering the field of mitophagy in PD, priority should be given to core institutions with sustained high productivity. For instance, McGill University (with 52 publications) and University College London (with 45 publications) not only maintain stable research output but also their high total link strength (84 and 128, respectively) indicates that their achievements are mostly generated in a collaborative innovation environment. Particular attention should be paid to the 27 publications from the National Institute of Neurological Disorders and Stroke (NINDS), with an average citation per paper reaching 386 times, in order to comprehend the core theoretical framework of the field. Based on the bibliometric analysis results, a multi-dimensional strategy should be adopted when selecting collaborative teams. First, high-link-strength hub institutions should be identified, with priority given to teams with a total link strength greater than 80 and an average annual publication output exceeding five papers (such as University College London and the University of Tübingen). These institutions are characterized by dense node connection lines and spanning multiple research clusters in the collaboration network depicted in Fig. 4 A. Second, highly active institutions should be tracked, with a focus on red nodes in Fig. 4 B that have an average publication year after 2018, such as the Chinese Academy of Sciences, which has shown a significant fluctuating upward trend in publication output between 2018 and 2022. Finally, the compatibility of international cooperation should be assessed, with teams that have at least five co-authored papers with international partners being selected. It is recommended that new researchers prioritize teams with a total link strength higher than 50 and a record of transnational co-authorship in the past three years when choosing institutions, in order to enhance the visibility and translational efficiency of research outcomes. By integrating the three dimensions of institutional influence, technical complementarity, and cooperation maturity, researchers can systematically optimize their team selection decisions. Journal Distribution and Research Synergies The journal analysis shows that mitophagy research in PD is highly concentrated, with 22 core journals (Zone 1) accounting for most publications. Autophagy (IF = 14.6,Q1) stands out with 55 publications, establishing its authority in mitophagy research. Other core journals, such as International Journal of Molecular Sciences and Cells , also have high impact factors, reflecting researchers' preference for disseminating findings through high-impact platforms. However, this concentration could be risky if editorial policies or review preferences of core journals change, potentially disrupting the balanced spread of knowledge. Meanwhile, the cumulative impact of 356 peripheral journals (Zone 3), despite their lower individual contributions, may create a"long-tail effect" highlighting the potential value of niche topics. VOSviewer clustering analysis reveals that mitophagy research in PD can be divided into four distinct thematic clusters of journals. Cluster 1 (red) centers on molecular mechanisms and neuroprotection, with key journals including International Journal of Molecular Sciences , Cells , Frontiers in Neuroscience , Molecular Neurobiology , and Antioxidants , focusing on mitochondrial quality control and oxidative stress mechanisms. Cluster 2 (green) is dominated by genetics and disease modeling, featuring journals such as Human Molecular Genetics , PLOS Genetics , Mitochondrion , Biochimica et Biophysica Acta-Molecular Basis of Disease , and Journal of Neurochemistry , which concentrate on the regulation of mitophagy by PD-related gene mutations. Cluster 3 (blue) focuses on core autophagy mechanisms, covering journals like Autophagy , Journal of Biological Chemistry , Cellular and Molecular Life Sciences , EMBO Journal , and Science Advances , which delve into autophagosome formation and regulatory networks. Cluster 4 (yellow) bridges clinical translation and technological application, with journals such as npj Parkinson's Disease , Movement Disorders , Phytomedicine , Cell Death&Disease , and CNS Neuroscience&Therapeutics exploring new therapeutic technologies targeting mitochondria. Notably, top-tier interdisciplinary journals like Nature , despite their relatively low volume of publications (Fig. 7B), often feature breakthrough studies, as indicated by their high average normalized citation rates (deep red nodes). Nature 's research on mitophagy in PD has been pivotal in integrating molecular mechanisms, pathological associations, and targeted therapies. Seminal studies include the elucidation of the PARKIN-dependent ubiquitylome in response to mitochondrial depolarization[ 60 ], genome-wide RNAi screens identifying regulators of parkin upstream of mitophagy[ 61 ], and the role of USP30 in opposing parkin-mediated mitophagy[ 62 ]. Structural studies have detailed the activation mechanism of Parkin by phosphorylated ubiquitin[ 63 ], the interaction mode of PINK1 with ubiquitin[ 64 ], and the mechanism of Parkin activation by PINK1[ 65 ]. These studies have precisely explained the mechanisms of early-onset PD mutations. Research has also expanded into the gut-brain axis, revealing how intestinal infections can trigger neuronal immune attacks via mitochondrial antigens[ 66 ]. Cryo-electron microscopy capturing the full activation pathway of PINK1[ 67 ] provides an atomic-level blueprint for targeted interventions. In contrast, high-volume journals like Autophagy focus more on in-depth analysis of mechanistic details, forming a complementary pattern where top-tier journals set the direction and specialized journals deepen the research. Author Productivity and Collaborative Networks As shown in Fig. 9 , the actual distribution of author productivity significantly deviates from Lotka's Law, with a much higher proportion of authors contributing only one publication (78.6% vs. the predicted 62%). This suggests a large number of short-term participants or interdisciplinary collaborators. This pattern may result from the need to integrate knowledge across multiple disciplines, such as neurodegenerative disease mechanisms, cell biology, and molecular genetics. Among authors with two or more publications, the actual proportions are consistently lower than Lotka's Law predictions, indicating a highly concentrated core research group in the field. The research area is marked by a collaborative network centered on key scholars and institutions. Hattori Nobutaka from Juntendo University and Richard J.Youle from the National Institute of Neurological Disorders and Stroke (NINDS) have emerged as cornerstones of the field, with Hattori Nobutaka publishing 28 papers and Richard J.Youle's work being cited 12,235 times. Hattori Nobutaka's team focuses on the roles of PINK1 and Parkin genes in PD and their functions in mitochondrial quality control. Their studies have revealed that PINK1 phosphorylates the ubiquitin-like domain (Ubl) of Parkin upon loss of mitochondrial membrane potential, promoting Parkin translocation to and activation on mitochondria, thereby triggering mitophagy[ 68 ]. They also found that mitochondrial dysfunction caused by PINK1 deficiency is associated with defects in the respiratory chain rather than proton leak[ 69 ]. In animal models, Hattori Nobutaka further confirmed that Parkin deficiency impairs mitochondrial turnover and leads to dopaminergic neuronal loss[ 70 ]. Richard J.Youle's team has elucidated the critical mechanisms of PINK1 and Parkin in regulating mitophagy[ 21 ]. They discovered that PINK1 stability is regulated by mitochondrial membrane potential and identified several proteins regulating the PINK1/Parkin pathway, such as TOMM7, HSPA1L, and BAG4[ 61 ]. They also found that Rab protein cycling in the endoplasmic reticulum plays an important role in Parkin-mediated mitophagy[ 71 ]. These findings have advanced our understanding of PD pathogenesis and laid a solid foundation for the field. Notably, the institutional distribution shows that McGill University (with Edward A. Fon and Jean-Francois Trempe ) and Mayo Clinic (with Springer Wolfdieter and Fabienne C. Fiesel) each have two scholars in the top ten. Their total link strengths (184/120 for McGill and 273/256 for Mayo) are relatively high, indicating stable and efficient collaborative mechanisms within these institutions. The co-authorship network map (Fig. 10 A) shows a hierarchical structure with scholars like Hattori Nobutaka, Richard J. Youle, Springer Wolfdieter, and Edward A. Fon as central hubs. These researchers have published at least 20 papers each and connect multiple clusters, acting as bridges in cross-team collaborations. Emerging peripheral networks represent potential research frontiers, such as new genetic regulators or therapeutic targets. These groups, though currently small, may play a pivotal role in future research and require sustained funding and mentorship to enhance their impact. Figure 11 B highlights Richard J. Youle's dominance through a color gradient of average normalized citations (darker red indicates higher impact). Node colors also reflect differences in research timelines: Fon and Trempe have redder nodes (more recent publications), while Richard J. Youle and Springer Wolfdieter have bluer nodes (earlier publications). Collaboration and institutional support are key to advancing research in this field. While top scholars have made significant contributions, emerging researchers and small teams need support to prevent knowledge gaps. Interdisciplinary integration can improve research efficiency and address the complexity of PD pathogenesis. Hotspots and Frontiers Core Mechanisms and Dominant Pathways Keyword analysis in the field of mitophagy in PD reveals dynamic shifts in research paradigms and core scientific questions. Research has consistently focused on the PINK1-Parkin pathway, as evidenced by the high frequency and strong co-occurrence of keywords "PINK1" (220 occurrences) and "Parkin" (266 occurrences), with total link strengths of 1243 and 1468, respectively. This indicates that the pathway has continuously dominated the research framework since its early discovery and highlights the complexity of its regulatory mechanisms. PINK1 is a mitochondrial protein kinase that accumulates on the outer mitochondrial membrane when mitochondria are damaged or depolarized, recruiting Parkin. Parkin then ubiquitinates damaged mitochondria, marking them for autophagic degradation[ 12 , 39 , 60 ].This pathway is not only involved in mitochondrial quality control but also plays roles in oxidative stress and metabolic regulation[ 72 , 73 ]. The PINK1-Parkin pathway also interacts with other autophagy pathways, such as those mediated by FUNDC1 and BNIP3L, to maintain cellular metabolic balance[ 74 , 75 , 76 ]. In PD, loss of PINK1 and Parkin function leads to impaired mitophagy, resulting in neuronal damage and death[ 77 ].Therapeutic strategies targeting the PINK1-Parkin pathway are emerging as a research focus. Activation of this pathway can enhance mitophagy, improving mitochondrial function and cell survival. For example, certain small molecules have been identified to activate the PINK1-Parkin pathway, promoting mitochondrial clearance and cellular protection[ 78 , 79 , 80 ]. Inhibition of the deubiquitinase USP30 has been shown to enhance Parkin activity, restoring mitochondrial quality[ 81 , 82 , 83 ]. Mitochondrial Quality Control The prominence of keywords such as "mitochondrial dynamics" (rank 10), "mitochondrial quality control" (rank 17), and "mitochondrial biogenesis" (rank 20) reflects a paradigm shift in research from a singular focus on autophagy mechanisms to an integrated multimodal quality control network. Mitochondrial quality control (MQC) integrates mitochondrial dynamics (fusion and fission), mitochondrial biogenesis, and mitophagy to maintain mitochondrial integrity and cellular homeostasis[ 84 ]. Mitochondrial fission, mediated by Drp1, is a critical step in the autophagy process, facilitating the clearance of damaged mitochondria to maintain cellular health[ 85 ]. Studies show that fission and autophagy are closely linked: fission not only provides sufficient mitochondrial fragments for autophagy but also regulates autophagy efficiency through signaling pathways[ 86 ]. Inhibition of mitochondrial fission impairs autophagy, exacerbating cellular damage and death[ 87 ]. Conversely, mitochondrial fusion, mediated by MFN1/2, delays autophagy initiation through content mixing, creating a "damage buffering" mechanism. By diluting abnormal signals (e.g.,oxidatively damaged proteins), fusion postpones autophagy[ 88 , 89 ]. However, MFN2 has been shown to have dual functions in cardiomyocyte injury: it maintains mitochondrial quality through fusion and induces mitophagy by activating Parkin translocation and phosphorylation, clearing damaged mitochondria and protecting cells[ 90 ]. Recent studies have revealed that the imbalance between mitophagy and mitochondrial biogenesis is a core mechanism underlying dopaminergic neuronal degeneration. PINK1/Parkin mutations not only impair mitophagy but also inhibit PGC-1α activity through PARIS protein accumulation[ 91 , 92 ].This dual defect creates a vicious cycle: impaired mitophagy leads to the accumulation of damaged mitochondria, while insufficient biogenesis prevents neurons from compensating with functional mitochondria, ultimately exacerbating oxidative stress and energy metabolic collapse. α-synuclein PD is marked by abnormal α-synuclein aggregation, which is key to its pathogenesis. Lurette et al. controlled α-synuclein aggregation using optogenetic tools and found it significantly impacts mitophagy. The aggregates cause mitochondrial depolarization, reduced ATP, fission, and mitophagy via cardiolipin externalization, and lower mitochondrial content in dopaminergic neurons and mouse midbrains. This shows that aggregation, not overexpression, of α-synuclein drives mitophagy and mitochondrial dysfunction, offering new insights into PD[ 93 ]. Additionally, the abnormal accumulation of α-synuclein disrupts mitochondrial function and disturbs the dynamic balance of mitophagy, thereby promoting neuronal degeneration[ 94 , 95 , 96 ]. Shaltouki et al. analyzed PD patient brains, neurons, and fly models and found that α-synuclein accumulation upregulates Miro protein levels. Miro, a mitochondrial outer membrane protein, is involved in mitochondrial movement and clearance of damaged mitochondria. In PD neurons, Miro abnormally accumulates on mitochondria, delaying mitophagy. α-synuclein interacts with Miro via its N-terminus, driving Miro upregulation. Reducing Miro levels rescues mitophagy and neurodegeneration. This study underscores the role of mitochondrial-associated α-synuclein in PD and identifies Miro as a potential therapeutic target[ 97 ]. Abnormal aggregation of α-synuclein activates the p38 MAPK pathway, phosphorylating Parkin at Ser131 and impairing its function. This disrupts mitophagy, worsening mitochondrial dysfunction and neuronal death in the A53T α-synuclein model. Inhibiting p38 MAPK activity reduces apoptosis, restores mitochondrial membrane potential, and increases synaptic density[ 98 ]. Yin et al. showed that Nur77 is key to regulating α-synuclein aggregation and mitophagy using STI571 and antibodies. STI571 inhibits PHB2 Y121 phosphorylation, reduces α-synuclein aggregates, and boosts autophagy. Nur77 moves to mitochondria in the presence of α-synuclein, enhancing PHB-mediated mitophagy and reducing mitochondrial dysfunction. In α-synuclein PFF mouse models, Nur77 overexpression lowers pS129-α-synuclein levels and protects dopaminergic neurons, likely via the p-c-Abl/p-PHB2 Y121 axis. This suggests Nur77 and STI571 could be potential therapeutic targets for PD[ 99 ]. The natural compound quercetin upregulates PINK1/Parkin expression, reduces α-synuclein aggregation, and improves mitochondrial quality control in 6-OHDA-induced models[ 100 ]. These findings suggest that modulating the balance between mitophagy and α-synuclein aggregation may represent a novel therapeutic strategy for PD. Neuroinflammation and Ferroptosis The rising trends of "neuroinflammation" and "ferroptosis" (Figs. 12 and 13 A) highlight the growing emphasis on the interplay between multiple mechanisms in the field. Mitophagy, primarily mediated by the PINK1/Parkin pathway, is crucial for maintaining mitochondrial homeostasis. Dysfunction in this pathway leads to the accumulation of damaged mitochondria, resulting in mitochondrial DNA (mtDNA) leakage and reactive oxygen species (ROS) accumulation. These changes activate the cGAS-STING signaling pathway and the NLRP3 inflammasome, promoting the release of pro-inflammatory cytokines such as IL-1β and IL-6, and inducing microglial polarization towards the pro-inflammatory M1 phenotype[ 101 , 102 , 103 , 104 ]. Targeting mitophagy has been shown to effectively alleviate neuroinflammation. For instance, the natural compound Urolithin A enhances PINK1/Parkin-dependent mitophagy and inhibits NLRP3 inflammasome activation[ 103 ]. Similarly, Repaglinide activates mitophagy and modulates endoplasmic reticulum stress, inhibiting glial cell activation and neuroinflammation, thereby reducing dopaminergic neuronal apoptosis[ 105 ]. Ferroptosis, a form of iron-dependent lipid peroxidation-driven cell death, is closely intertwined with mitophagy in neurodegenerative processes. ROS accumulation from mitochondrial dysfunction can exacerbate neuronal damage via ferroptosis pathways. For example, neurotoxins like rotenone induce excessive ROS generation, activating ferroptosis markers (e.g.,GPX4 downregulation, COX2 and NCOA4 upregulation) while inhibiting autophagy flux and enhancing mitophagy markers (e.g.,LC3 and p62), ultimately leading to dopaminergic neuronal death[ 106 ]. Iron metabolism disturbances, such as iron deposition and transferrin receptor abnormalities, form a vicious cycle with mitophagy dysregulation in disease models. For instance, bifenthrin exposure exacerbates the synergistic effects of mitophagy and ferroptosis by binding to iron transport proteins (Tf) and GPX4[ 107 ]. Additionally, ferritin heavy chain 1 (FTH1) regulation is prominent in 6-OHDA models, where inhibiting ferritinophagy reduces ferroptosis and improves mitochondrial function, suggesting therapeutic potential in targeting iron metabolism and mitochondrial quality control[ 108 ]. These findings indicate that mitophagy and ferroptosis are not isolated events in neurodegenerative pathology but form a positive feedback loop through mechanisms involving oxidative stress, iron homeostasis imbalance, and energy metabolism disruption. Future research should focus on elucidating the spatiotemporal regulatory networks between these processes to inform the development of dual-target therapeutic strategies. Challenges and Future Directions Despite the prominence of keywords such as "ubiquitination" (rank 12) and "oxidative stress" (rank 9), which point to numerous potential therapeutic targets, the frequency of terms related to translational medicine, such as"therapeutic targets" and "biomarkers" does not match their scientific importance. This reflects systemic barriers in translating preclinical findings into clinical applications. Firstly, the mechanisms underlying mitophagy are complex and dynamically balanced, making precise modulation challenging. For instance, although the PINK1/Parkin pathway is extensively studied, most PD patients lack mutations in these genes, and the roles of other regulatory pathways (such as NIX and FUNDC1) are not fully understood. Intervention strategies need to be differentiated based on disease stages (compensatory vs.decompensatory phases). Secondly, existing animal and cell models fail to replicate the progressive impairment of mitophagy and the in vivo microenvironment interactions seen in human PD, limiting the reliability of drug screening. While induced pluripotent stem cell (iPSC) models, a recent focus highlighted by the keyword "fibroblasts" provide a humanized platform for mechanistic studies, their limitations in simulating aging-related microenvironments need to be overcome. Thirdly, drug development is hampered by low brain delivery efficiency, insufficient targeting specificity (which may interfere with other autophagy pathways), and individual genetic heterogeneity (e.g.,variable treatment responses in patients with LRRK2 or GBA mutations). Moreover, the clinical translation of mitophagy-related therapies is impeded by the lack of biomarkers that can monitor mitophagy activity in real time. Neuroprotective efficacy requires long-term follow-up for validation, whereas current clinical trials often rely on short-term improvements in motor symptoms as surrogate endpoints, potentially leading to biased results. Additionally, since PD pathology involves the interplay of multiple pathways (such as α-synuclein aggregation and oxidative stress), targeting mitophagy alone may be insufficient to halt disease progression. Synergistic regulation of other mechanisms (such as mitochondrial biogenesis or anti-inflammatory pathways) is needed, but the complexity and risk of side effects associated with multi-target drug development are significantly increased. Breaking these bottlenecks will require the integration of novel disease models (such as 3D brain organoids), precise delivery technologies (optimizing AAV vectors or nanoparticles), and interdisciplinary strategies (such as AI-assisted compound screening)to advance the clinical translation of mitophagy-related therapies. Limitations Our study provides a comprehensive overview of mitophagy research in PD using bibliometric techniques. However, several limitations are inherent to our approach. Firstly, our dataset is derived solely from the Web of Science Core Collection, potentially omitting relevant articles from other databases. Secondly, our analysis is confined to English-language literature, which may introduce bias. Lastly, the presence of homonymous authors or different expressions of the same author may affect the accuracy of our collaborative network analysis. Conclusion Our analysis of mitophagy research in PD from 2007 to 2024 reveals several key findings. The United States is the leading country in terms of publication output, followed by China. McGill University is the most prolific institution, while the journal Autophagy is the most frequent publication venue, with International Journal of Molecular Sciences ranking second. Hattori Nobutaka, is the most prolific author, followed by Edward A. Fon. Research foci include "pink1/parkin", "mitochondrial quality control" and α-synuclein, with neuroinflammation and ferroptosis emerging as hotspots. These findings provide a comprehensive overview of the field, highlighting critical insights into current research trajectories. We anticipate that these insights will help researchers better understand prevailing trends in mitophagy research in PD and guide future investigative endeavors. Declarations Conflict of Interest The authors declare no competing interests. Funding This work was supported by the Shanghai Municipal Commission of Health (shzyyzdxk-2024108). Acknowledgements This work was supported by the Shanghai Municipal Commission of Health (shzyyzdxk-2024108). Author Contribution J.Q.Z. conceptualized the study, designed the research framework, conducted the literature search and data collection, analyzed the data, interpreted the results, and wrote the initial draft. Q.W., Y.C. and H.M.S.,assisted in data analysis and interpretation, and edited the manuscript. S.F.X. supervised the study, conducted the final data analysis and interpretation, wrote and edited the manuscript, and managed the submission process. Data Availability No datasets were generated or analysed during the current study. 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Mitophagy Upregulation Occurs Early in the Neurodegenerative Process Mediated by α-Synuclein. Mol Neurobiol 61(11): 9032–9042. https://doi.org/10.1007/s12035-024-04131-6 Kinnart I, Manders L, Heyninck T, Imberechts D, Praschberger R, Schoovaerts N, Verfaillie C, Verstreken P, Vandenberghe W. Elevated α-synuclein levels inhibit mitophagic flux. NPJ Parkinson's Dis. 2024;10(1):80. https://doi.org/10.1038/s41531-024-00696-0 Martinez JH, Alaimo A, Gorojod RM, Porte Alcon S, Fuentes F, Coluccio Leskow F, Kotler ML. Drp-1 dependent mitochondrial fragmentation and protective autophagy in dopaminergic SH-SY5Y cells overexpressing alpha-synuclein. Molecular and Cellular Neurosciences. 2018;88:107–117. https://doi.org/10.1016/j.mcn.2018.01.004 Shaltouki A, Hsieh CH, Kim MJ, Wang X. Alpha-synuclein delays mitophagy and targeting Miro rescues neuron loss in Parkinson's models. Acta Neuropathologica. 2018;136(4):607–620. https://doi.org/10.1007/s00401-018-1873-4 Chen J, Ren Y, Gui C, Zhao M, Wu X, Mao K, Li W, Zou F. Phosphorylation of Parkin at serine 131 by p38 MAPK promotes mitochondrial dysfunction and neuronal death in mutant A53T α-synuclein model of Parkinson's disease. Cell Death & Disease. 2018;9(6):700. https://doi.org/10.1038/s41419-018-0722-7 Yin S, Shen M, Zhang Y, Wu J, Song R, Lai X, Tian Z, Wang T, Jin W, Yan J. Nur77 increases mitophagy and decreases aggregation of α-synuclein by modulating the p-c-Abl/p-PHB2 Y121 in α-synuclein PFF SH-SY5Y cells and mice. European Journal of Medicinal Chemistry. 2024;268:116251. https://doi.org/10.1016/j.ejmech.2024.116251 Wang W, Han R, He HJ, Li J, Chen SY, Gu Y, Xie C. Administration of quercetin improves mitochondria quality control and protects the neurons in 6-OHDA-lesioned Parkinson's disease models. Aging. 2021 Apr 20;13(8):11738–11751. https://doi.org/10.18632/aging.202868 Lu Y, Gao L, Yang Y, Shi D, Zhang Z, Wang X, Huang Y, Wu J, Meng J, Li H, Yan D. Protective role of mitophagy on microglia-mediated neuroinflammatory injury through mtDNA-STING signaling in manganese-induced parkinsonism. Journal of Neuroinflammation. 2025;22(1):55. https://doi.org/10.1186/s12974-025-03396-5 Quinn PMJ, Moreira PI, Ambrósio AF, Alves CH. PINK1/PARKIN signalling in neurodegeneration and neuroinflammation. Acta Neuropathologica Communications. 2020;8(1):189. https://doi.org/10.1186/s40478-020-01062-w Qiu J, Chen Y, Zhuo J, Zhang L, Liu J, Wang B, Sun D, Yu S, Lou H. Urolithin A promotes mitophagy and suppresses NLRP3 inflammasome activation in lipopolysaccharide-induced BV2 microglial cells and MPTP-induced Parkinson's disease model. Neuropharmacology. 2022;207:108963. https://doi.org/10.1016/j.neuropharm.2022.108963 Hu ZL, Sun T, Lu M, Ding JH, Du RH, Hu G. Kir6.1/K-ATP channel on astrocytes protects against dopaminergic neurodegeneration in the MPTP mouse model of Parkinson's disease via promoting mitophagy. Brain, Behavior, and Immunity. 2019;81:509–522. https://doi.org/10.1016/j.bbi.2019.07.009 Motawi TK, Al-Kady RH, Senousy MA, Abdelraouf SM (2023) Repaglinide Elicits a Neuroprotective Effect in Rotenone-Induced Parkinson's Disease in Rats: Emphasis on Targeting the DREAM-ER Stress BiP/ATF6/CHOP Trajectory and Activation of Mitophagy. ACS Chemical Neuroscience 14(1):180–194. https://doi.org/10.1021/acschemneuro.2c00656 Li X, Li W, Xie X, Fang T, Yang J, Shen Y, Wang Y, Wang H, Tao L, Zhang H (2025) ROS Regulate Rotenone-induced SH-SY5Y Dopamine Neuron Death Through Ferroptosis-mediated Autophagy and Apoptosis. Molecular Neurobiology. Advance online publication. https://doi.org/10.1007/s12035-025-04824-6 Zhang Y, Zhang B (2024) Bifenthrin Caused Parkinson's-Like Symptoms Via Mitochondrial Autophagy and Ferroptosis Pathway Stereoselectively in Parkin−/− Mice and C57BL/6 Mice. Molecular Neurobiology 61(11):9694–9707. https://doi.org/10.1007/s12035-024-04140-5 Tian Y, Lu J, Hao X, Li H, Zhang G, Liu X, Li X, Zhao C, Kuang W, Chen D, Zhu M (2020) FTH1 Inhibits Ferroptosis Through Ferritinophagy in the 6-OHDA Model of Parkinson's Disease. Neurotherapeutics 17(4):1796–1812. https://doi.org/10.1007/s13311-020-00929-z Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 20 Nov, 2025 Read the published version in Hereditas → Version 1 posted Editorial decision: Revision requested 03 Jul, 2025 Reviews received at journal 02 Jul, 2025 Reviewers agreed at journal 30 Jun, 2025 Reviewers agreed at journal 29 Jun, 2025 Reviews received at journal 28 Jun, 2025 Reviewers agreed at journal 27 Jun, 2025 Reviews received at journal 25 Jun, 2025 Reviewers agreed at journal 25 Jun, 2025 Reviewers agreed at journal 24 Jun, 2025 Reviewers agreed at journal 24 Jun, 2025 Reviewers invited by journal 24 Jun, 2025 Editor assigned by journal 24 Jun, 2025 Submission checks completed at journal 23 Jun, 2025 First submitted to journal 21 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6944875","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":476219279,"identity":"8ee23a25-6e45-4ecd-bb9b-b3f375ae4c70","order_by":0,"name":"Junqiao Zhao","email":"","orcid":"","institution":"Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Junqiao","middleName":"","lastName":"Zhao","suffix":""},{"id":476219280,"identity":"b9bfb81f-cf14-4cca-998d-5f76b2d82388","order_by":1,"name":"Qian Wang","email":"","orcid":"","institution":"Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Wang","suffix":""},{"id":476219281,"identity":"406af324-a3da-4c8e-83d9-009da96516ca","order_by":2,"name":"Yan Cao","email":"","orcid":"","institution":"Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Cao","suffix":""},{"id":476219282,"identity":"a04a6185-c12f-413d-840a-148eafb7082b","order_by":3,"name":"Huimin Shan","email":"","orcid":"","institution":"Harvard Medical School, Brigham and Women’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Huimin","middleName":"","lastName":"Shan","suffix":""},{"id":476219283,"identity":"2b577ff4-900b-4536-8808-8562bb5af7b3","order_by":4,"name":"Shifen Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIiWNgGAWjYBCDBAYG5gMHEipsePjZGwiqZmyAaGFLfPDhTJqMZM8BorXwGBvObDlsY3DDAb96gxsJ7A8+1Njl8UsfMJPmbTjPw3CDgfHDxxzcWiRnJDA2zjiWXCzZl5AmzbvjNg/j7AZmyZnbcGvhl0hgbOZhO5C44QzDMWneM7d5mGUOsDHz4tHCBtLy59+BxP1nGNukedvO8QBF8GsB28LYBrSFh5nZcGbbAR4eQlokex4wzuztS06ccYaNERjIyTwSPAeb8frF4HgCw4cf3+wS+3v4PwCj0s7e/njzwQ8f8WgBOu0Dugg4okbBKBgFo2AUUAIAV99UXBQOakQAAAAASUVORK5CYII=","orcid":"","institution":"Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Shifen","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2025-06-21 12:23:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6944875/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6944875/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s41065-025-00544-y","type":"published","date":"2025-11-20T15:58:10+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":85494202,"identity":"0f5b8842-5162-440e-a499-193f92043cab","added_by":"auto","created_at":"2025-06-26 13:32:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":365799,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLiterature screening process and results for mitophagy in PD\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/823933d1af593258015b561c.png"},{"id":85494203,"identity":"373de708-f217-457b-bb42-ac5c248056dd","added_by":"auto","created_at":"2025-06-26 13:32:16","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2874306,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDescription and forecast of publication volume for mitophagy-related research in PD.\u003c/strong\u003e \u003cstrong\u003eA \u003c/strong\u003eThe chart illustrates the annual publication volume (purple bar chart) and cumulative publication volume (dark blue line chart) related to mitophagy in PD from 2007 to 2024, showing an overall increasing trend, with the highest number of publications in 2021. The number of publications ranges from a minimum of 1 in 2007 to a maximum of 178 in 2021, with an average of 87.67 and a standard deviation of 58.27. \u003cstrong\u003eB\u003c/strong\u003e The left chart depicts the forecasted annual number of publications from 2025 to 2040. It presents the logistic fit model, along with the 95% prediction band and the 95% confidence band. The parameters of the logistic model are A1 = -74.62532, A2 = 232.91223, x0 = 2014.64653, and p = 302.71514, with an R-Square value of 0.9422, indicating a high degree of model fit. This model suggests a continuous increase in the volume of publications, projecting approximately 225 publications annually by 2040. The right chart is a zoomed-in view within the dashed line frame for clarity.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/d49ca1190d7ee6b63ba3729a.jpg"},{"id":85494205,"identity":"177ab521-272b-435b-92b3-812461172d28","added_by":"auto","created_at":"2025-06-26 13:32:16","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":407666,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCountry/region analysis of mitophagy in PD. A\u003c/strong\u003e Visualization of the collaborative network among all 69 countries/regions using VOSviewer. Node size shows research involvement, color denotes clusters, and line thickness indicates collaboration strength. \u003cstrong\u003eB\u003c/strong\u003e Chord diagram of international collaborations, with arc width indicating collaboration strength. \u003cstrong\u003eC \u003c/strong\u003eTop 9 countries with citation bursts, showing years and burst strengths. \u003cstrong\u003eD \u003c/strong\u003ePublication trends for USA, China, and India from 2007 to 2024, with lines representing countries and axes showing years and publication numbers.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/1e20984df45606080709b2bb.jpg"},{"id":85495150,"identity":"582fceaa-b728-4857-a369-c3a0b45bfc3c","added_by":"auto","created_at":"2025-06-26 13:40:16","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":523884,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInstitutional Analysis in the Field of Mitophagy in PD.\u003c/strong\u003e \u003cstrong\u003eA\u003c/strong\u003eVisualization of the collaborative network among institutions using VOSviewer. This figure displays institutions with a publication count surpassing 5. The nodes, varied in color, denote different institutional clusters, and the nodes' size corresponds to the frequency of institutional involvement. \u003cstrong\u003eB\u003c/strong\u003e Institutional collaboration network map illustrating the average publication year. Nodes are colored based on the average year of publication, with redder shades indicating more recent publications and bluer shades representing older publication periods.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/91a9562ba5199fbf39823c2e.jpg"},{"id":85495662,"identity":"1ebf9d4e-927e-43c9-b46d-c7cf33401f60","added_by":"auto","created_at":"2025-06-26 13:48:16","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":141629,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eJournal Distribution in Mitophagy Research in PD According to Bradford's Law\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/e14ab374e646d8330fee37e5.png"},{"id":85495151,"identity":"c9e2f0c0-f52a-4aa1-afdf-8f95baec4f91","added_by":"auto","created_at":"2025-06-26 13:40:16","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1621925,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e Displays the quantity of articles in core journals associated with mitophagy in PD research. \u003cstrong\u003eB\u003c/strong\u003eIllustrates the distribution of journals across Bradford's Law zones, with an emphasis on core (Zone 1), secondary (Zone 2), and peripheral (Zone 3) journals.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/3bbe8c601ceb6fe18100f180.jpg"},{"id":85494216,"identity":"f406e426-d39f-403e-b619-afe96e0d85d6","added_by":"auto","created_at":"2025-06-26 13:32:16","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":573996,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eJournal Analysis in the Context of Mitophagy in PD.\u003c/strong\u003e \u003cstrong\u003eA\u003c/strong\u003e Visualization of the journal collaboration network in VOSviewer. This figure highlights all journals that have published at least one article. A total of 453 publications from 436 journals were included after removing isolated nodes. The nodes, varied in color, denote different journal clusters, and the nodes' size corresponds to the frequency of journal appearances. \u003cstrong\u003eB\u003c/strong\u003e Node colors indicate the average normalized citation score (avg. norm. citations), with a gradient from blue (lower scores, less influence) to red (higher scores, more influence). This visualization helps identify key journals with both high publication volume and citation impact, marking their significant role in the field.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/3c9f43810a351455278624c9.jpg"},{"id":85494219,"identity":"3de32609-dcaf-43e1-93dd-55fded7c2834","added_by":"auto","created_at":"2025-06-26 13:32:16","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":255689,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDual-map overlay of journals displaying citation relationships.\u003c/strong\u003e Citing journals are positioned on the left, while cited journals are on the right, with colored paths illustrating the connections between them.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/8bee2197f71078cad79263a1.png"},{"id":85494209,"identity":"0cc8e11b-e59a-4099-9159-637d945960e2","added_by":"auto","created_at":"2025-06-26 13:32:16","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":40058,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDocument productivity distribution among authors based on Lotka's Law\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/36c0a77f74f6525d850c182a.jpg"},{"id":85494227,"identity":"7f9ed958-7b78-4798-a88f-e9b6ee09fd67","added_by":"auto","created_at":"2025-06-26 13:32:17","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":601185,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAuthorship Analysis of Mitophagy Research in PD.\u003c/strong\u003e \u003cstrong\u003eA\u003c/strong\u003e This figure includes the top 1000 authors out of 7428 based on total link strength, excluding those not connected to other nodes, resulting in a final network of 802 authors. The nodes, differentiated by color, represent authors within various clusters, with node size reflecting the frequency of their publications. \u003cstrong\u003eB \u003c/strong\u003eNetwork map highlighting key authors, with nodes colored by average normalized citations (avg. norm. citations). Redder nodes indicate higher academic influence.\u003c/p\u003e","description":"","filename":"10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/682c85bec2e7e9692effb4a8.jpg"},{"id":85495663,"identity":"4fdfa185-d1a5-4b8d-bb26-329fd9040a14","added_by":"auto","created_at":"2025-06-26 13:48:16","extension":"jpg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":262779,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCollaboration network of key authors with a minimum of 8 publications in mitophagy research. A\u003c/strong\u003e This network includes authors who have published 8 or more papers, with 41 authors remaining after excluding those without connections to other nodes. The nodes, differentiated by color, represent authors within various clusters, with node size reflecting the frequency of their publications. \u003cstrong\u003eB\u003c/strong\u003e Node colors show the average publication year. Redder nodes mean more recent activity, bluer nodes indicate older work. This helps spot active researchers and groups in the field.\u003c/p\u003e","description":"","filename":"11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/1437aa2e6263837f7d784942.jpg"},{"id":85494217,"identity":"b8f31e32-e248-4031-b148-eef82d20b521","added_by":"auto","created_at":"2025-06-26 13:32:16","extension":"jpg","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":633254,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnalysis of keywords in the study of mitophagy in PD. \u003c/strong\u003eA The network in VOSviewer shows co-occurrence relationships among keywords, organized into seven color-coded clusters from right to left: red (Cluster 1), green (Cluster 2), blue (Cluster 3), yellow (Cluster 4), purple (Cluster 5), light blue (Cluster 6), and orange (Cluster 7). \u003cstrong\u003eB \u003c/strong\u003eThe CiteSpace-generated timeline illustrates the evolution of keywords in mitophagy research. Dots represent keywords, with position indicating first appearance year and size reflecting frequency. Different timelines correspond to distinct research themes, tracking keyword trends over time.\u003c/p\u003e","description":"","filename":"12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/ba1ebb571b0d9e6df1f7c644.jpg"},{"id":85496712,"identity":"51671880-39f7-48f7-8820-c83fa61ff025","added_by":"auto","created_at":"2025-06-26 13:56:16","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":201068,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrend analysis of key terms in mitophagy research in PD\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"13.png","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/a9c189a47c6bd22a2246b58d.png"},{"id":85494225,"identity":"b3d7b53f-b136-46fb-9912-b2e23e16edfb","added_by":"auto","created_at":"2025-06-26 13:32:17","extension":"jpg","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":632977,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHeatmap analysis of keywords.\u003c/strong\u003e \u003cstrong\u003eA\u003c/strong\u003e Annual heatmap from 2007 to 2024. The annual heat value of each keyword is obtained by dividing the number of citations in that year by the total number of citations in that year. \u003cstrong\u003eB\u003c/strong\u003e Keyword relevance heatmap. Keywords with high popularity in similar time periods are clustered into one category and marked with different colors.\u003c/p\u003e","description":"","filename":"14.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/a3fcd86e2d99c0a3c5407ce4.jpg"},{"id":85494220,"identity":"2ddca6fd-d7c3-42a4-83ce-f2b5742e1fe9","added_by":"auto","created_at":"2025-06-26 13:32:16","extension":"jpg","order_by":15,"title":"Figure 15","display":"","copyAsset":false,"role":"figure","size":552772,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReference analysis in the context of mitophagy in PD.\u003c/strong\u003e \u003cstrong\u003eA\u003c/strong\u003e Visualization of the reference network in CiteSpace. The size of each node corresponds to the frequency with which the respective article is co-cited. The network map highlights the collaborative ties among authors, with lines indicating co-citation relationships. The color gradient ranging from purple to red signifies the publication years, with purple representing earlier publications and red indicating more recent ones. \u003cstrong\u003eB\u003c/strong\u003e References are clustered based on title similarity, with each cluster color-coded and labeled with numbers and themes, including topics such as #0 selective autophagy, #1 pink1-associated Parkinson's disease, #2 intracellular organelle, #3 e3 ubiquitin ligase parkin, #4 autophagic cell stress, #5 neuronal damage, #6 targeting mitophagy, #7 mitochondrial dynamics, #8 sqstm1 cooperate, #9 mitochondrial fission, #10 small n-terminal tag, #11 cytosolic pink1, and #12 mitochondrial morphology, #13 mitophagy in neurodegenerative diseases.\u003c/p\u003e","description":"","filename":"15.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/0740d799b320fa587a27c5b2.jpg"},{"id":85494226,"identity":"744d4a14-bc9b-4ea1-8f9b-f99eacc56433","added_by":"auto","created_at":"2025-06-26 13:32:17","extension":"jpg","order_by":16,"title":"Figure 16","display":"","copyAsset":false,"role":"figure","size":727854,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e Dependency relationships among co-cited literature clusters in the research on mitophagy in PD, generated by displaying the top 50% of cluster dependency paths. The direction of the arrows between clusters indicates the direction of influence, such as an arrow pointing from Cluster B to Cluster A signifies that the development of Cluster A is influenced by Cluster B. \u003cstrong\u003eB\u003c/strong\u003e The top 25 references with the strongest citation bursts.\u003c/p\u003e","description":"","filename":"16.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/381e95679b446aa17c63fd96.jpg"},{"id":96650323,"identity":"b41834ad-783d-47af-b399-fdcd6509580b","added_by":"auto","created_at":"2025-11-24 16:11:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":12354291,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6944875/v1/ec157c81-1308-466c-ab25-0c203bfa4d63.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Mapping the Global Research Landscape of Mitophagy in Parkinson's Disease: A Bibliometric and Visualization Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003e Parkinson's disease (PD), recognized as the fastest-growing neurodegenerative disorder globally, currently affects over 11.7\u0026nbsp;million individuals worldwide[ \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e ]. Characterized by progressive motor dysfunction and debilitating non-motor symptoms, PD imposes substantial socioeconomic burdens, evidenced by the \u003cspan\u003e$\u003c/span\u003e51.9\u0026nbsp;billion total economic burden recorded in the U.S. in 2017[ \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e ]. Global projections indicate a concerning 1.5-fold increase in PD prevalence by 2035, primarily driven by demographic aging trends[ \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e ]. While epidemiological studies highlight geographical variations in disease burden, China's projected contribution to the global PD population warrants particular attention, with estimates suggesting it may account for nearly half of worldwide cases by 2030[ \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e ]. This escalating public health challenge underscores the urgent need for multinational collaborative research and innovative therapeutic strategies. Neuropathologically, PD is characterized by the progressive loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) and the accumulation of misfolded α-synuclein in Lewy bodies and lewy neurites[ \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e , \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e ]. Although the etiology of PD has not yet been fully elucidated, accumulating evidence indicates that mitochondrial dysfunction plays a central role in disease progression. Mitochondria, as highly multifunctional organelles, are critical for neuronal survival due to the essential requirement of their structural integrity for cellular homeostasis. Notably, the pioneering discovery by Schapira's team in 1989 first reported significantly reduced activity of mitochondrial respiratory chain Complex I in postmortem brain tissues of PD patients, establishing an important molecular link between mitochondrial impairment and PD pathogenesis[ \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e ]. This discovery established the fundamental basis for the \"mitochondrial deficiency hypothesis\". Subsequent genetic investigations have further corroborated this framework by demonstrating direct associations between pathogenic mutations in mitochondrial quality control genes (notably PINK1 and Parkin) and familial PD cases[ \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e , \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e ]. Notably, PD animal models induced by mitochondrial toxins (e.g., MPTP and rotenone) closely recapitulate human pathological features, further validating the causal relationship between mitochondrial dysfunction and PD pathogenesis[ \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e ]. The accumulation of damaged mitochondria can trigger neuronal death, highlighting the importance of efficient mitochondrial quality control mechanisms[ \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e ]. \u003c/p\u003e \u003cp\u003eMitophagy, the targeted degradation of mitochondria via autophagy, is a key process for maintaining cellular health[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The pathogenesis of PD is closely associated with dysfunctional mitophagy, a process precisely regulated through both PINK1/Parkin-dependent and -independent pathways. Upon mitochondrial membrane potential dissipation, PINK1 accumulates on the outer mitochondrial membrane and activates Parkin's E3 ubiquitin ligase activity, which marks damaged mitochondria for autophagosome recruitment. PD-associated PINK1 or Parkin mutations disrupt this quality control mechanism, leading to toxic mitochondrial accumulation and accelerated dopaminergic neurodegeneration[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In addition to genetic determinants, environmental factors and aging critically impair mitophagic function. With advancing age, the progressive decline in mitochondrial function and reduced autophagic capacity lead to intracellular accumulation of damaged mitochondria, which may constitute a key pathogenic mechanism in PD[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In PD therapeutic research, intervention strategies targeting mitophagy have gradually become an important research direction. For example, drugs such as Pramipexole have been found to alleviate neuronal damage by activating mitophagy-related signaling pathways[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]。Furthermore, several recently developed small-molecule compounds, such as those activating PINK1 or Parkin, have demonstrated potential for enhancing mitophagy in preclinical models, offering new therapeutic prospects for PD[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In conclusion, mitophagy plays a central role in the pathogenesis of PD. Elucidating the regulatory mechanisms of mitophagy and its dysfunction in neurodegenerative contexts not only deepens our understanding of PD pathology, but also establishes a critical theoretical framework for developing novel therapeutic interventions targeting mitochondrial quality control.\u003c/p\u003e \u003cp\u003eThe growing scientific interest in mitophagy's role in PD pathogenesis underscores the critical need for systematic literature analysis. Comprehensive evaluation of research evolution is essential for understanding how research trends have evolved, identifying gaps in knowledge, and guiding future research efforts. In contrast to traditional reviews, bibliometric analysis provides distinct methodological advantages: it enables efficient processing of large-scale literature datasets, quantitative identification of research hotspots through citation network analysis, and visual mapping of conceptual relationships, thereby eliminating the need for labor-intensive manual article evaluations. This study employs integrated bibliometric and scientometric visualization techniques to systematically examine global research patterns in PD-related mitophagy through 2024. By analyzing publication metrics, citation networks, and collaborative patterns, our approach traces the historical development of mitophagy research while identifying emerging therapeutic paradigms. It serves as a valuable roadmap for researchers, clinicians, and funding agencies, while also emphasizing the significant achievements and collaborative efforts that have influenced this field of study.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Collection\u003c/h2\u003e \u003cp\u003eThis study primarily utilized the Web of Science Core Collection (WoSCC; Clarivate Analytics, USA) - the gold-standard multidisciplinary citation index encompassing over 34,000 peer-reviewed journals across 254 research categories since 1900 - to ensure rigorous bibliometric analysis of high-impact scientific literature. (Platform access: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.webofscience.com/wos\u003c/span\u003e\u003cspan address=\"https://www.webofscience.com/wos\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). To systematically map the global research landscape of mitophagy in PD, the following search formula was applied: TS=(Parkinson* OR PD) AND TS=(mitophagy OR \"mitochondrial autophagy\"). The search was limited to articles and reviews published up to December 2024. The final search was conducted on January 12, 2025, to ensure inclusion of the most recent publications and to prevent data bias due to database updates. A total of 1712 documents were retrieved.\u003c/p\u003e \u003cp\u003eThe initial search yield was filtered to include only English-language publications. Editorial material, book chapters, early access, meeting abstract, proceeding paper, correction, letter, data paper, publication with expression of concern, and retracted publication were excluded. The final dataset comprised articles and reviews articles that specifically addressed aspects of mitophagy in the context of PD.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBibliometric Analysis\u003c/h3\u003e\n\u003cp\u003eTo strengthen the validity and multidimensional scope of our investigation, we employed several bibliometric tools to uncover trends and patterns within this field.\u003c/p\u003e \u003cp\u003eCiteSpace, a software developed by Chaomei Chen, was pivotal in visualizing the co-citation and co-authorship networks, as well as tracking the evolution of key terms within the field[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Our utilization of CiteSpace 6.4. R1 allowed us to delve into hotspots countries, dual-map overlays of journals, keyword timelines, and co-citation analyses.\u003c/p\u003e \u003cp\u003eIn conjunction with CiteSpace, VOSviewer, developed by Nees Jan van Eck and his team, was instrumental in the bibliometric network graph analysis[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In this study, we utilized VOSviewer (version 1.6.20; Centre for Science and Technology Studies, Leiden University, The Netherlands) to visualize the distribution of countries, institutions, and journals, and to construct co-authorship and keyword co-occurrence networks. The clustering algorithm of VOSviewer, which is based on a similarity matrix and the VOS mapping technique, enabled the automated clustering process. We also employed Pajek (version 5.18; developed by Andrej Mrvar and Vladimir Batagelj, Faculty of Computer and Information Science, University of Ljubljana) in conjunction with VOSviewer. Pajek is an advanced tool for network analysis, specializing in the visualization and management of large-scale networks[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In our research, Pajek was used to calculate and optimize graph data and correlation networks, thereby enhancing the clarity and interpretability of the network visualizations.\u003c/p\u003e \u003cp\u003eTo further enhance our analysis, we employed Bibliometrix, an R-based tool, to examine key bibliometric data[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. For the visualization and predictive modeling of publication trends over time, including both annual and predicted publication volumes, we utilized OriginPro 2024 software (OriginLab Corporation, 2024).\u003c/p\u003e\n\u003ch3\u003eEthical Considerations\u003c/h3\u003e\n\u003cp\u003eThis study is a bibliometric analysis, and all data were obtained from publicly available academic database. As the research did not involve human or animal experimentation, personal data collection, or sensitive information, ethical approval was not required. All data were aggregated and analyzed in compliance with database terms of use, copyright regulations, and academic integrity standards to ensure the transparency and reproducibility of the study.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eLiterature Overview\u003c/h2\u003e \u003cp\u003eFollowing the screening protocol and publication search process depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, we identified 1,578 publications related to mitophagy in PD, including 1,082 articles and 496 reviews. Using Bibliometrix, we conducted a detailed bibliometric analysis, revealing a 34.79% annual growth rate and a robust body of literature. A total of 7,428 authors contributed to these publications in 453 sources. There are only 33 single-authored documents, and the average number of co-authors per document is 6.9, highlighting the strong collaborative spirit in this research area. Furthermore, the international co-authorship rate is 26.43%, demonstrating significant global research collaboration. The average age of a document is 6.25 years, and the average citation count per document is 72.85, indicating that this field has an active and influential position in the scientific community.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePublication Outputs and Trends\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA shows the annual and cumulative publication trends from 2007 to 2024. The first publication appeared in 2007, and since then, the number of publications has increased significantly, reaching a peak of 178 publications in 2021. The cumulative publications, shown by the dark blue line, demonstrate a steady upward trend, reflecting the growing body of research in this area.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAnalysis of Countries/Regions and Cooperation Relationships\u003c/h3\u003e\n\u003cp\u003eCurrently, a total of 69 countries/regions are actively researching mitophagy in PD, with a significant focus in the Northern Hemisphere, especially in North America, Europe, and parts of Asia. This distribution reflects the global pattern of scientific research output, as nations with advanced scientific infrastructures mainly exist in these areas. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the top 10 countries/regions in terms of publication volume, along with centrality measures that highlight their crucial roles in the research network. The betweenness centrality of these countries/regions measures their significance as intermediaries, emphasizing their connectivity and influence. Moreover, the total link strength, which indicates the overall robustness of a country/region's connections in the research network, is also included in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. This metric not only represents the number of collaborations but also the intensity of these partnerships, providing a comprehensive view of each country/region's research involvement and impact.\u003c/p\u003e \u003cp\u003eThe United States (USA) emerges as the leading contributor with a total publication volume of 479 and a high intermediary centrality of 0.58, indicating its pivotal role in the global research network and its influence in shaping the field of mitophagy research in PD. \"Mechanisms of Mitophagy,\" authored by Richard J. Youle and Derek P. Narendra and featured in Nature Reviews Molecular Cell Biology in 2011, is the most highly cited article in the USA with an outstanding 2488 citations. This article has been pivotal in shaping the discourse within the field of cellular biology, particularly in the realm of mitophagy\u0026mdash;the selective degradation of mitochondria. Its thorough analysis of the molecular mechanisms underlying mitophagy has exerted a profound influence on subsequent research, significantly enhancing our comprehension of the process's role in maintaining cellular homeostasis and its implications in neurodegenerative diseases, notably PD. By elucidating the functions of critical proteins such as PINK1 and parkin, the article has established a foundational framework for future therapeutic strategies aimed at modulating mitophagy[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].China, with 353 publications and an intermediary centrality of 0.13, also figures prominently, reflecting its growing impact on global scientific discourse. England (170 publications) and Germany (122 publications) further underscore the significant European contribution to this research domain. However, the lower intermediary centrality values for these countries suggest that while their research output is increasing, their role in bridging international collaborations could be further enhanced.\u003c/p\u003e \u003cp\u003eTo further elucidate the landscape of international collaboration, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB presents a chord diagram showcasing the intricate network of co-authorships among the top 25 countries contributing to research on mitophagy in PD.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC provides an overview of the top 9 countries with the strongest citation bursts, sorted by the start time of their respective bursts. A citation burst signifies a period during which a country's scientific publications receive a sudden and significant increase in citations. The USA began its significant burst in 2007, while China and India both demonstrate notable bursts from 2022 to 2024, with China's burst strength reaching 20.96. These bursts reflect critical periods of intense research activity and influence within the field.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD presents the annual publication trends for the USA, China, and India, which are among the countries with the highest publication volumes and significant citation bursts. The USA shows a consistent increase in publication numbers over the years, with fluctuations but an overall upward trend, peaking around 2022. China's trend shows a steady rise from 2018 onwards, aligning with the table data that indicates a period of rapid growth in research output and influence. India, starting with a lower base,shows a gradual increase in publications, with a more pronounced rise from 2020.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 10 Countries/regions by publication volume including centrality and total link strength\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCountries/regions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePublications\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCentrality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal link strength\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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colname=\"c3\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCanada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eAnalysis of and Institutional Cooperations\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e ranks the top 10 institutions by publication count in mitophagy research related to PD. The data encompasses institutions from various countries, highlighting the global distribution of research efforts in this domain. The institutions are listed according to their publication count, with McGill University from Canada leading the chart with 52 publications. University College London (UK) and the University of Pittsburgh (USA) follow with 45 and 38 publications, respectively. The USA is the most represented country with four institutions, followed by Germany with two. Citation counts vary significantly among the institutions. The National Institute of Neurological Disorders and Stroke (USA) stands out with the highest citation count of 10,427, highlighting its substantial influence on the field. We conducted an in-depth analysis of the content of these influential papers. Among them, the second most cited article, following the previously mentioned work by Richard J. Youle, is \"PINK1 is selectively stabilized on impaired mitochondria to activate Parkin\"[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] by Derek P. Narendra, with 2,205 citations. PINK1 stabilizes on damaged mitochondria, recruiting Parkin to trigger autophagy. Voltage-dependent proteolysis regulates PINK1 levels, keeping them low on healthy mitochondria but high on damaged ones. Mutations in PINK1 and Parkin disrupt this process, affecting mitophagy and explaining their genetic interaction in flies. Total link strength, which measures the strength of connections within the research network, shows that University College London has the highest collaborative engagement with a score of 128. This suggests a strong network of co-authorships and partnerships.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA presents an institutional collaboration network map generated using VOSviewer. This network comprises 180 institutions, each depicted as a node, selected based on their publication of at least five papers, while excluding those lacking collaborative ties with other institutions. The resultant chart delineates five distinct clusters, with each node's color corresponding to its specific group. The node size is proportional to the number of publications, thereby accentuating institutions with a higher research output. The thickness of the lines connecting the nodes reflects the extent of collaboration, with thicker lines signifying more frequent cooperative interactions.\u003c/p\u003e \u003cp\u003eUpon analyzing the network, it is evident that certain institutions occupy central positions within the diagram, indicating their crucial role in the overall collaborative framework. These central nodes, distinguished by their larger size and numerous connections, likely represent key research hubs actively involved in knowledge exchange and collaborative research initiatives. It is also apparent that institutions with close collaborative relationships predominantly belong to the same country.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA presents a scholarly network map of institutional collaborations, featuring nodes of identical size and placement as those in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB, with uniform line thickness indicating the strength of collaborative ties. The distinctive aspect of this visualization lies in its chromatic representation of nodes, which reflects the mean year of publication. Redder shades signify more recent scholarly contributions, while bluer shades denote earlier publication periods. A notable observation within this network is the prevalence of redder nodes among several Chinese institutions, highlighting a recent and substantial surge in research publications. This visual evidence supports the broader trend of exponential growth in China's research productivity in recent years. The prominent red coloration among Chinese institutions underscores a significant escalation in their activity and contributions within the field of mitophagy in PD, indicating a profound shift in the global research landscape.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 10 institutions by publication volume including citations and total link strength\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInstitution\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePublication\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCitations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal link strength\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMcGill University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCanada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity College London\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3791\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity of Pittsburgh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJuntendo University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMayo Clinic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChinese Academy of Sciences\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNational Institute of Neurological Disorders and Stroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity of L\u0026uuml;beck\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJohns Hopkins University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity of T\u0026uuml;bingen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of Journals\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 10 journals in terms of number of publications, corresponding IF (JCR2023) and JCR quartile\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePublications\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIF(JCR2023)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eJCR quartile\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAutophagy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInternational Journal of Molecular Sciences\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal of Biological Chemistry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHuman Molecular Genetics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScientific Reports\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMolecular Neurobiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCell Death \u0026amp; Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrontiers in Neuroscience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeurobiology of Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhen discussing the significance of journal distribution in the field of mitophagy in PD, Bradford's Law offers a crucial perspective. Bradford's Law, introduced by Samuel C. Bradford, describes a specific pattern of journal distribution within scientific literature. According to this law, if journals are sorted by the number of papers they publish on a particular subject, they can be divided into several zones, with each zone containing an equal number of papers, while the number of journals in each zone decreases geometrically, meaning a small number of core journals account for the majority of publications[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe utilized a bibliometric online analysis platform \u0026ldquo;bibliometirx\u0026rdquo; to identify journals in the field of mitophagy in PD. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e illustrates the distribution of core journals. The chart reveals the ranking of journals based on the logarithm of their publication count, with those in the most central area publishing a significant proportion of articles within the field. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA displays the number of articles published in core journals in this domain. The bar chart highlights that \u003cem\u003eAutophagy\u003c/em\u003e is the leading journal with 55 publications, followed by \u003cem\u003eInternational Journal of Molecular Sciences\u003c/em\u003e (53 publications) and \u003cem\u003eJournal of Biological Chemistry\u003c/em\u003e (40 publications). Other notable contributors include \u003cem\u003eCells\u003c/em\u003e and \u003cem\u003eHuman Molecular Genetics.\u003c/em\u003e Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB provides additional detail on the number of journals in each zone. Zone 1 has 22 journals, Zone 2 has 75, and Zone 3 has 356. The 22 journals in Zone 1 are the core journals identified in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA. These journals have the highest publication volume, indicating their significant influence in the field.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents the top 10 journals by number of publications, co-citation frequency, impact factor (IF;JCR 2023), and JCR quartile. \u003cem\u003eAutophagy\u003c/em\u003e tops the list with 55 publications and an IF of 14.6, ranking in JCR Q1. \u003cem\u003eInternational Journal of Molecular Sciences\u003c/em\u003e and \u003cem\u003eJournal of Biological Chemistry\u003c/em\u003e follow, with IF of 4.9 and 4, respectively. These journals lead in both publication volume and impact factor, underscoring their key role in disseminating research findings.\u003c/p\u003e \u003cp\u003eThis analysis underscores the importance of these core journals as primary conduits for knowledge dissemination within the field, guiding researchers in selecting where to publish their work for maximum academic impact.\u003c/p\u003e \u003cp\u003eThe VOSviewer visualization (Fig.\u0026nbsp;7A) maps journals publishing mitophagy-related literature and their interrelationships. Journals are clustered into four categories based on similarity. Cluster 1 (Red) includes journals focusing on foundational medical research, neuroscience, cell biology, pharmacology, and toxicology, covering disease mechanisms, drug development, and cellular processes. Cluster 2 (Green) comprises journals rich in molecular biology, genetics, molecular neuroscience, and biochemistry, addressing molecular mechanisms, genetic diseases, and biochemical processes. Cluster 3 (Blue) encompasses journals delving into biochemistry, molecular biology, cell biology, and immunology, emphasizing cell signaling and immune responses. Cluster 4 (Yellow) bridges materials science, applied sciences, cellular metabolism, neuroscience, and stem cell research, highlighting biomaterials, cellular energy metabolism, neurodegenerative diseases, and stem cell therapies. These clusters underscore the interdisciplinary nature of current research and cross-field collaborations.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;7B focuses on the average normalized citations (avg.norm.citations) metric, visualized by color intensity. Deeper red indicates higher citation frequency, while bluer hues signify lower citation rates. This metric reflects journals' academic influence and significance within their fields. Journals like \u003cem\u003eNature\u003c/em\u003e, \u003cem\u003eJournal of Cell Biology\u003c/em\u003e, \u003cem\u003eMolecular Cell\u003c/em\u003e and \u003cem\u003eNeuron\u003c/em\u003e appear in deep red, denoting higher average citation counts and thus prominent status and broad impact. Despite not having the largest nodes, their red color underscores their respected and influential position in academia.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe utilized knowledge flow analysis to examine the citation and co-citation dynamics between citing and cited journals. The dual-map overlay (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003e) illustrates the topic distribution, citation trajectory changes, and shifts in research foci across journals. The left side labels citing journals, and the right side labels cited journals. Colored curves depict knowledge flow from citing to cited journals, underscoring inter-field connectivity and influence[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].For instance, the curve connecting \"MOLECULAR BIOLOGY IMMUNOLOGY\" with \"MOLECULAR BIOLOGY GENETICS\" suggests a significant citation relationship and knowledge flow between these two fields.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of authors\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e illustrates a comparison between the predicted distribution of document productivity among authors in the field of mitophagy in PD, based on Lotka's Law (yellow area), and the actual distribution (red line). For authors with a single publication, the predicted proportion is 62%, but the observed proportion is much higher at 78.6%. This suggests that more authors than expected produce only one publication in this field. For authors publishing two or more documents, the actual proportion is lower than the predicted value, indicating that Lotka's Law may overestimate the number of highly prolific authors in this specific field.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e offers an overview of the academic influence and institutional affiliations of the top ten authors. Hattori Nobutaka tops the list with 28 publications and 3,731 citations, underscoring his substantial impact. Richard J.Youle, with 20 publications and 12,235 citations, demonstrates exceptional influence despite fewer publications. The table also highlights authors from prestigious institutions like the University of T\u0026uuml;bingen and McGill University, each with two representatives in the top ten, reflecting these institutions' robust research contributions. Authors such as Springer Wolfdieter and Edward A. Fon, with high total link strength, emerge as key collaborators. These authors and institutions play a leading role in advancing the field.\u003c/p\u003e \u003cp\u003eThe co-authorship network map (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e10\u003c/span\u003eA) vividly illustrates the collaborative landscape among researchers. Node size reflects an author's contribution, with larger nodes indicating higher publication counts or central collaborative roles, exemplified by Hattori Nobutaka and Richard J. Youle. Node colors differentiate clusters, highlighting groups of frequent co-authors and suggesting strong ties within specific research teams or thematic areas. Connecting lines denote co-authorship relationships, with closely positioned nodes, such as Edward A. Fon and Jean-Francois Trempe, indicating potential research partnerships. Figure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e10\u003c/span\u003eB uses average normalized citations as the metric. The visualization employs a color gradient, with darker red shades indicating higher academic impact. Prominent authors such as Richard J. Youle, Springer Wolfdieter, Hattori Nobutaka and Edward A. Fon are highlighted, reflecting their influential contributions and frequent citations. The map also shows small, emerging networks. Though currently limited, they could signal new directions and grow into larger clusters. Monitoring them is crucial for future breakthroughs.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e11\u003c/span\u003eA focuses authors with at least eight publications, excluding isolated nodes. It highlights active collaborators, with clusters indicating closely working groups and lines showing collaborative ties. Central authors serve as key connectors. This map provides a clear view of leading scholars' collaborative relationships. Figure\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e11\u003c/span\u003eB shows the same network with nodes colored by average publication year. Blue to red gradients indicate older to newer publications. Red nodes highlight recent activity, while blue nodes show older contributions. This helps identify the most active contributors in recent years.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 10 authors in terms of number of publications\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAuthor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of publication\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCiations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003etotal link strength\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eInstitutions\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHattori Nobutaka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJuntendo Univ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEdward A. Fon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMcGill Univ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpringer Wolfdieter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMayo Clinic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFabienne C. Fiesel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMayo Clinic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRichard J. Youle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNINDS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCharleen T. Chu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1585\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUniv Pittsburgh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChristine Klein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUniv Lubeck\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNoriyuki Matsuda\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTokyo Metropolitan Inst Med Sc\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnne Gruenewald\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUniv Luxembourg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJean-Francois Trempe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMcGill Univ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of Keyword and topic\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 20 keywords in mitophagy research in PD with occurrences and total link strength\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeyword\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOccurrences\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal link strength\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emitophagy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3272\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eparkinson's disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2423\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emitochondria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1910\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eparkin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1468\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eautophagy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1370\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epink1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1243\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eneurodegeneration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e836\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emitochondrial dysfunction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e440\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eoxidative stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e509\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emitochondrial dynamics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e429\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eparkinson disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e436\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eubiquitin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e394\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ealpha-synuclein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e391\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ealzheimer's disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e374\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eapoptosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e315\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eaging\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e284\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emitochondrial quality control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e232\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eneurodegenerative diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e218\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epark2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emitochondrial biogenesis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eKeywords offer a snapshot of key research themes. Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e4\u003c/span\u003e lists the top 20 keywords by frequency. The most common are \u0026ldquo;mitophagy\u0026rdquo; (600), \u0026ldquo;parkinson's disease\u0026rdquo; (467), \u0026ldquo;mitochondria\u0026rdquo; (355), and\u0026ldquo;parkin\u0026rdquo; (266), indicating that these areas are trending in current research.\u003c/p\u003e \u003cp\u003eA co-occurrence network diagram of keywords visualized in VOSviewer (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e12\u003c/span\u003eA) reveals seven major clusters based on research themes. The first cluster addresses the multifactorial pathogenesis of PD, including oxidative stress, mitochondrial dysfunction, and neuroinflammation. The second cluster focuses on the Pink1/Parkin signaling pathway and its role in mitophagy and disease pathology. The third cluster examines the interplay between mitochondrial dysfunction and protein aggregation. The fourth cluster highlights the relationship between calcium signaling and mitochondrial damage. The fifth cluster explores mitophagy and oxidative stress mechanisms and their therapeutic potential. The sixth cluster investigates genetic mechanisms and potential therapeutic targets. The seventh cluster delves into protein aggregation and autophagy mechanisms.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn CiteSpace, the timeline graph (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e12\u003c/span\u003eB) shows the most frequently occurring keywords for each of the nine thematic clusters over time: #0 (dysfunction), #1 (Alzheimer\u0026rsquo;s disease), #2 (ubiquitin), #3 (mitochondrial quality control), #4 (mitochondrial biogenesis), #5 (fission), #6 (vulnerability), #7 (mitogen-activated protein kinases, MAPKs), and #8 (mitochondrial function). The analysis revealed distinct temporal patterns: Clusters #0, #1, #2, #3, and #4 exhibited uniformly distributed nodes across the entire timeline, indicating their roles as persistent research themes, with #2 (ubiquitin) and #3 (mitochondrial quality control) showing prominent node sizes during 2007\u0026ndash;2010, suggesting foundational focus on ubiquitin-mediated degradation pathways and proteostatic regulation. In contrast, clusters #6, #7, and #8 displayed sparse node distributions. Notably, cluster #1 (Alzheimer\u0026rsquo;s disease) spanned the full timeline, underscoring enduring interdisciplinary investigations into shared mitochondrial dysregulation mechanisms between neurodegenerative disorders.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe trend topic chart (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e13\u003c/span\u003e) generated by Bibliometrix illustrates the evolution and popularity of research themes. The size of each dot reflects the prevalence of a specific research focus over time. Terms like \"neuroinflammation\" and \"ferroptosis\" show increasing trends, highlighting emerging areas of interest. This reflects growing recognition of the complex interplay between mitochondrial dysfunction and other cellular processes, such as inflammation and regulated cell death, in PD pathogenesis. The increasing frequency of these terms may indicate a shift in research focus towards understanding the multifaceted mechanisms underlying neurodegenerative processes and identifying potential therapeutic targets.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e14\u003c/span\u003eA presents an annual heatmap analysis of research keywords from 2007 to 2024, visualizing the annual popularity of each keyword. This popularity is calculated by dividing the number of citations for that keyword in a specific year by the total number of citations for that year. In the last two years, keywords such as \"pink1/parkin,\" \"neuroinflammation,\" \"neuroprotection,\" \"dopaminergic neuron,\" \"usp30,\" \"mitochondrial fission,\" \"mitochondrial dysfunction,\" \"prkn,\" \"ferroptosis,\" \"mptp,\" \"caenorhabditis elegans,\" \"ageing,\" \"fibroblasts,\" \"lysosomes,\" and \"reactive oxygen species\" have become hot topics. Figure\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e14\u003c/span\u003eB illustrates a high degree of correlation among keywords within the research field of mitophagy in PD. This high correlation suggests that the research topics in this field are closely interconnected and likely revolve around several core concepts or issues. This could imply that researchers are generally focused on similar scientific questions and employ similar theoretical frameworks and methodologies.Furthermore, this high degree of correlation may indicate that the research trends in this field are relatively stable, with researchers consistently focusing on certain hot topics rather than frequently shifting their research focus. This could reflect the maturity of the field, where some key issues have gained widespread ecognition and in-depth study. However, despite the generally high correlation between most keywords, there may still be some keywords or themes with lower correlation. These keywords with lower correlation might represent emerging areas of research or potential research gaps that warrant further exploration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eHighly cited publications\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 15 high-cited publications related to mitophagy in PD.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAuthors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArticle Title\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSource Title\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDocument Type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTimes Cited\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePublication Year\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDOI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYoule, RJ et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMechanisms of mitophagy[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNATURE REVIEWS MOLECULAR CELL BIOLOGY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReview\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/nrm3028\u003c/span\u003e\u003cspan address=\"10.1038/nrm3028\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeisler, S et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePINK1/Parkin-mediated mitophagy is dependent on VDAC1 and p62/SQSTM1[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e 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class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePickrell, AM et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe Roles of PINK1, Parkin, and Mitochondrial Fidelity in Parkinson's Disease[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNEURON\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReview\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neuron.2014.12.007\u003c/span\u003e\u003cspan address=\"10.1016/j.neuron.2014.12.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMatsuda, N et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePINK1 stabilized by mitochondrial depolarization recruits Parkin to damaged mitochondria and activates latent Parkin for mitophagy[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJOURNAL OF CELL BIOLOGY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArticle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1083/jcb.200910140\u003c/span\u003e\u003cspan address=\"10.1083/jcb.200910140\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAshrafi, G et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe pathways of mitophagy for quality control and clearance of mitochondria[\u003cspan citationid=\"CR28\" 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\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVives-Bauza, C et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePINK1-dependent recruitment of Parkin to mitochondria in mitophagy[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArticle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e 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align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/hmg/ddp326\u003c/span\u003e\u003cspan address=\"10.1093/hmg/ddp326\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTanaka, A et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProteasome and p97 mediate mitophagy and degradation of mitofusins induced by Parkin[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e 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colname=\"c3\"\u003e \u003cp\u003eMitophagy inhibits amyloid-β and tau pathology and reverses cognitive deficits in models of Alzheimer's disease[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNATURE NEUROSCIENCE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArticle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41593-018-0332-9\u003c/span\u003e\u003cspan address=\"10.1038/s41593-018-0332-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e 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class=\"RefSource\"\u003e10.1126/science.1231031\u003c/span\u003e\u003cspan address=\"10.1126/science.1231031\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJin, SM et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMitochondrial membrane potential regulates PINK1 import and proteolytic destabilization by PARL[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJOURNAL OF CELL BIOLOGY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArticle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1083/jcb.201008084\u003c/span\u003e\u003cspan address=\"10.1083/jcb.201008084\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWang, XN et al.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePINK1 and Parkin Target Miro for Phosphorylation and Degradation to Arrest Mitochondrial Motility[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCELL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArticle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.cell.2011.10.018\u003c/span\u003e\u003cspan address=\"10.1016/j.cell.2011.10.018\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eHighly cited reference analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 10 highly cited references on Mitophagy in PD: Insights from CiteSpace LBY:5.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArticle Title\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArticle type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAuthors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCited\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eIF(JCR2023)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eJCR quartile\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eDOI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePINK1/Parkin-mediated mitophagy is dependent on VDAC1 and p62/SQSTM1[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArticle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNature Cell Biology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGeisler S\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/ncb2012\u003c/span\u003e\u003cspan address=\"10.1038/ncb2012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePINK1 is selectively stabilized on impaired mitochondria to activate Parkin[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArticle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePLoS Biology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNarendra DP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pbio.1000298\u003c/span\u003e\u003cspan address=\"10.1371/journal.pbio.1000298\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePINK1-dependent recruitment of Parkin to mitochondria in mitophagy[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArticle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProceedings of the National Academy of Sciences\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVives-Bauza C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1073/pnas.0911187107\u003c/span\u003e\u003cspan address=\"10.1073/pnas.0911187107\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe roles of PINK1, parkin, and mitochondrial fidelity in Parkinson's disease[\u003cspan citationid=\"CR26\" 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targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe ubiquitin kinase PINK1 recruits autophagy receptors to induce mitophagy[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArticle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNature\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLazarou M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e50.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/nature14893\u003c/span\u003e\u003cspan address=\"10.1038/nature14893\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePINK1 stabilized by mitochondrial depolarization recruits Parkin to damaged mitochondria and activates latent Parkin for mitophagy[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArticle\u003c/p\u003e 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align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUbiquitin is phosphorylated by PINK1 to activate parkin[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArticle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNature\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eKoyano F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e50.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/nature13392\u003c/span\u003e\u003cspan address=\"10.1038/nature13392\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParkin is recruited selectively to impaired mitochondria and promotes their autophagy[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArticle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe Journal of Cell Biology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNarendra DP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1083/jcb.200809125\u003c/span\u003e\u003cspan address=\"10.1083/jcb.200809125\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePINK1 phosphorylates ubiquitin to activate Parkin E3 ubiquitin ligase activity[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArticle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe Journal of Cell Biology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eKane LA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1083/jcb.201402104\u003c/span\u003e\u003cspan address=\"10.1083/jcb.201402104\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMitophagy inhibits amyloid-β and tau pathology and reverses cognitive deficits in models of Alzheimer's disease[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArticle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNature Neuroscience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFang EF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e21.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41593-018-0332-9\u003c/span\u003e\u003cspan address=\"10.1038/s41593-018-0332-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e6\u003c/span\u003e presents the top 10 most cited references. These references were identified using CiteSpace software, with \"Look Back Year (LBY)\" parameter set at 5 years. This means that CiteSpace considered the citation status of each paper within 5 years after its publication. The purpose of this setting is to focus more precisely on recent research advancements, streamline the analysis network, and avoid the limitations of earlier studies. This approach helps to more accurately identify and understand key papers and research trends. Among these highly cited papers, 90% are original research articles. A significant portion of these highly cited publications overlaps with the previously mentioned top 15 highly cited publications (see Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e), highlighting their importance and representativeness.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eArticle co-citation analysis reveals the thematic, methodological, or theoretical connections between papers by tracking their co-citation frequency. In CiteSpace (with LBY\u0026thinsp;=\u0026thinsp;5, see Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e15\u003c/span\u003eA and \u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e15\u003c/span\u003eB), each node represents a paper, with its size proportional to co-citation frequency (larger nodes indicate more co-citations) and color mapping to the \"citation year\" (from cold to warm tones for early to recent citations). Given the LBY\u0026thinsp;=\u0026thinsp;5 setting, only citations within 5 years post-publication are counted, thus the map reflects short-term academic impact. The large blue nodes in the center of the map (e.g.,papers from 2009\u0026ndash;2014) indicate that these papers were highly co-cited within five years of publication. Despite their earlier publication dates, their conclusions or methods continue to influence subsequent research, suggesting they are core theories or classic findings in the field and remain valuable references. Conversely, the large warm-toned (red) nodes on the right represent recently published papers that have been quickly cited in a short period. Their research directions or innovations may signal emerging hotspots or future trends in the field and deserve close attention.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e16\u003c/span\u003eA shows the results of a bibliometric analysis using CiteSpace, focusing on cluster dependencies and highlighting the top 50% of these paths. The visualization reveals how one cluster influences another, with arrow directions indicating the flow of influence. For example, an arrow from Cluster B to Cluster A means that Cluster A's development is influenced by Cluster B. Firstly, cluster #0, \"Selective Autophagy\" is influenced by several other clusters, including \"Pink1-associated Parkinson's Disease\", \"Mitochondrial Dynamics\", \"SQSTM1 Cooperation\", \"Mitochondrial Fission\", \"Cytosolic Pink1\", and \"Mitochondrial Morphology\". This indicates that progress in selective autophagy research is closely tied to these areas, likely intersecting in mechanisms, disease associations, and therapeutic strategies. Secondly, Cluster#2, \"Intracellular Organelle\" is influenced by several clusters, including \"Pink1-associated Parkinson's Disease\", \"Mitochondrial Dynamics\", \"SQSTM1 Cooperation\", \"Mitochondrial Fission\" and \"Small N-terminal Tag\". This highlights the significant interplay between intracellular organelle research and studies on mitochondrial function, morphology, and protein tags. Additionally, both Cluster #5, \"Neuronal Damage\" and Cluster #6, \"Targeting Mitophagy\" are influenced by \"Pink1-associated Parkinson's Disease\" and \"E3 Ubiquitin Ligase Parkin.\" This underscores the importance of Pink1 and Parkin research in understanding neuronal damage and mitophagy targeting.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e16\u003c/span\u003eB highlights the top 25 references with the strongest citation bursts. The first two bursts occurred in 2009, with papers titled \"Parkin is recruited selectively to impaired mitochondria and promotes their autophagy\"[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and \"The PINK1/Parkin pathway regulates mitochondrial morphology\"[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Notably, the paper by Narendra et al. has the strongest burst (strength\u0026thinsp;=\u0026thinsp;64.35) and its burst duration lasted until 2013. Another high-burst paper is \"The ubiquitin kinase PINK1 recruits autophagy receptors to induce mitophagy\" by Lazarou et al. (strength\u0026thinsp;=\u0026thinsp;61.16)[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The data shows that papers published in 2010 caused the most citation bursts (seven in total), indicating a surge in related research activities.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eResearch Trends and Future Prospects\u003c/h2\u003e \u003cp\u003eIn this study, we utilized a nonlinear fitting curve to elucidate the annual publication growth trajectory of mitophagy research in PD. This trend aligns with the theory of scientific development proposed by Derek J. de Solla Price[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], which posits that the volume of scientific literature in a particular field will initially exhibit exponential growth before eventually plateauing. Notably, the inflection point of this growth pattern can be traced back to around 2010, a period during which key breakthrough studies laid the foundation for the subsequent establishment of paradigms. For instance, Narendra et al. revealed the mechanism by which PINK1 accumulates on damaged mitochondria and how this accumulation triggers the recruitment of Parkin and mitophagy[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Additionally, the team of Vives-Bauza elucidated how PINK1 and Parkin jointly regulate mitochondrial transport and aggregation, facilitating autophagic degradation in the perinuclear region[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. These studies provided the molecular framework for the subsequent rapid growth phase of publications. The current surge in publication numbers indicates that the field has established a dominant paradigm and is in the application phase, characterized by the rapid expansion of knowledge and the widespread dissemination of established theories and methods. This period has benefited from recent in-depth research on PD-related mitochondrial dysfunction, such as the discovery of the interaction between α-synuclein and mitochondria[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], as well as technological advancements like CRISPR gene editing[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Moreover, policy funding has also been a powerful driving force behind the expansion of this field. By using the search term (\"parkinson's disease\u0026rdquo; AND \u0026ldquo;mitophagy\") to access the official NIH RePORTER database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://reporter.nih.gov\u003c/span\u003e\u003cspan address=\"https://reporter.nih.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), we obtained funding data from 2007 to 2024. The initial funding in 2007 was 5.8\u0026nbsp;million dollars, which increased to 25\u0026nbsp;million dollars in 2010 (+\u0026thinsp;331%). During the technological breakthrough period from 2011 to 2017, the average annual growth rate was 34.6%, peaking at 853\u0026nbsp;million dollars in 2017. From 2018 to 2023, during the clinical translation phase, the funding amounts stabilized in the range of 470 to 790\u0026nbsp;million dollars, reflecting a sustained shift in strategic focus towards therapeutic development. Despite the increase in publication volume, the majority of studies remain at the cellular or animal model stage, with limited clinical validation. The influence and recognition of scientific literature will accumulate over time and eventually stabilize. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, the annual publication trend curve for PD-related mitophagy research is flattening. However, these predictions should be treated with caution. Although the nonlinear fitting curve provides robust predictions based on historical data, the dynamic and complex nature of scientific research cannot be overlooked. Actual trends may be influenced by a variety of internal and external factors. External factors include changes in research funding, policy adjustments, or global events, all of which can impact the scientific publication process. Internal factors involve technological advancements in related fields, the evolution of research methods, or shifts in the academic community's research focus.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eGlobal Collaboration and Regional Contributions\u003c/h2\u003e \u003cp\u003eThe analysis of global research collaboration on mitophagy in PD reveals a dynamic interplay of productivity, influence, and regional specialization.\u003c/p\u003e \u003cp\u003eThe United States emerges as the central hub of global collaboration, as evidenced by its highest publication volume (479), betweenness centrality (0.58), and total link strength (312). This underscores its dual role as a primary knowledge producer and a critical nexus for international collaborations. This leadership is reinforced by seminal contributions such as the 2011 review by Richard J.Youle and Derek P. Narendra[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], which established foundational frameworks for understanding PINK1/Parkin-mediated mitochondrial quality control. While China ranks second in productivity (353 publications), its relatively low betweenness centrality (0.13) and total link strength (102) suggest a focus on domestic or regionally clustered research, indicating a need for deeper integration into global networks. European nations, notably England (170 publications) and Germany (122 publications), demonstrate strong intracontinental collaboration (total link strengths of 188 and 153, respectively). However,their relatively lower centrality values compared to the United States highlight a gap in facilitating cross-regional knowledge exchange.\u003c/p\u003e \u003cp\u003eThe citation bursts observed in China (2022\u0026ndash;2024, strength\u0026thinsp;=\u0026thinsp;20.96) and India (2022\u0026ndash;2024, strength\u0026thinsp;=\u0026thinsp;14.3) signal shifting dynamics (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). China\u0026rsquo;s surge aligns with its strategic investments in neurodegenerative research. In recent years, Chinese scholars have made significant contributions to elucidating the molecular mechanisms and therapeutic strategies targeting mitophagy in PD. In the context of core regulatory pathways, Wang et al. revealed that PTEN-L acts as a novel phosphatase to inhibit PINK1-Parkin-mediated mitophagy through ubiquitin dephosphorylation[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Complementary studies by Huang et al. and Niu et al. further demonstrated the critical roles of metabolic enzymes (PANK2)[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] and deubiquitinating regulators (USP33)[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] in modulating PINK1-Parkin signaling, highlighting the dynamic interplay between ubiquitination and mitochondrial quality control. Regarding mitochondrial dynamics, the Chen team systematically established the involvement of Drp1-mediated fission in paraquat-induced neuronal damage[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], while Han et al. identified PINK1-dependent phosphorylation of Drp1 at Ser616 as a key modulator of mitochondrial morphology[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. In therapeutic development, Liu et al. reported that lovastatin enhances SHP2-mediated mitophagy to alleviate parkinsonism in murine models[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Innovative nanotechnology-driven approaches, such as sequence-targeted lycopene nanodots[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] and single-atom nanocatalytic platforms[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], were designed to promote pro-survival mitophagy and suppress neuroinflammation, respectively. Epigenetic studies uncovered non-coding RNA networks, including the circEPS15/miR-24-3p axis[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] and LncRNA NR_030777[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], which regulate mitophagy through ATG12 and CDK1 pathways. Notably, Bao et al. proposed a non-canonical mitochondrial quality control mechanism involving mitolysosome exocytosis[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], whereas Zhang et al. and Han et al. elucidated crosstalk between mitophagy and ferroptosis via NKAα1 inhibition[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] and Nrf2-mediated lipid peroxidation regulation[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. These findings collectively provide a multifaceted framework for understanding PD pathogenesis and advancing mitochondrion-targeted therapies.\u003c/p\u003e \u003cp\u003eIndia\u0026rsquo;s growth, though starting from a smaller base, reflects rising interest in PD epidemiology and cost-effective therapeutic strategies, such as repurposed mitochondrial enhancers. Annual publication trends (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD) further highlight this geographic diversification: the U.S. maintains steady growth, China exhibits exponential output since 2018, and India shows accelerating contributions post-2020.Recent years have witnessed significant progress from Indian researchers in understanding mitophagy regulation and therapeutic applications in PD. By establishing drosophila models, studies revealed that Rab11 modulates mitochondrial quality control through the Parkin/PINK1 signaling pathway[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Rodent studies demonstrated that pharmacological inhibition of deubiquitinating enzyme USP14 markedly amplified mitophagic activity and alleviated dopaminergic neurodegeneration[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Furthermore, SH-SY5Y cell-based investigations elucidated that andrographolide suppresses NLRP3 inflammasome activation via Parkin-mediated mitophagy[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. These findings collectively unravel the complexity of mitophagic networks, providing experimental foundations for developing targeted nanodelivery systems and epigenome-modulating strategies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eInstitutional Impact and Collaborative Strategies\u003c/h2\u003e \u003cp\u003eFrom the perspective of institutional distribution, research on mitophagy in PD exhibits a multipolar pattern, yet with significant geographical concentration. Institutions from North America and Europe dominate the field, with four US institutions ranking in the top ten (National Institute of Neurological Disorders and Stroke[NINDS], University of Pittsburgh, Mayo Clinic, and Johns Hopkins University). Collectively,these institutions account for 51.2% of the total citations among the top ten, with NINDS alone amassing 10,427 citations, thereby underscoring its academic leadership. Among European institutions, University College London (UCL) in the UK stands out as a core hub in the global collaborative network, with a total link strength of 128. Its extensive collaborations likely stem from the integration of clinical resources and fundamental research capabilities.\u003c/p\u003e \u003cp\u003eAs depicted in the institutional collaboration network (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), institutions such as University College London (total link strength of 128) and the Mayo Clinic (total link strength of 99) occupy core hub positions. Their extensive collaborative ties indicate that the deep integration of clinical and basic research is pivotal in driving the translation of mitophagy research into therapeutic strategies. However, the collaboration network remains predominantly intra-national clusters (e.g.,US and German institutions forming distinct clusters), suggesting that geographical proximity and shared research funding systems may still be the primary drivers of collaboration, despite the global demand for PD research. The increased activity of Chinese institutions in recent years is evidenced by the concentrated distribution of red nodes (representing recent publications) in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB. The Chinese Academy of Sciences (CAS, 29 publications) stands as a representative of China's research productivity, ranking sixth globally in terms of publication output. It should be noted that the literature inclusion threshold of VOSviewer (\u0026ge;\u0026thinsp;5 publications) may underestimate the collaborative potential of emerging institutions,as there may be initial collaborations in the actual research network that are not visualized.\u003c/p\u003e \u003cp\u003eFor researchers newly entering the field of mitophagy in PD, priority should be given to core institutions with sustained high productivity. For instance, McGill University (with 52 publications) and University College London (with 45 publications) not only maintain stable research output but also their high total link strength (84 and 128, respectively) indicates that their achievements are mostly generated in a collaborative innovation environment. Particular attention should be paid to the 27 publications from the National Institute of Neurological Disorders and Stroke (NINDS), with an average citation per paper reaching 386 times, in order to comprehend the core theoretical framework of the field. Based on the bibliometric analysis results, a multi-dimensional strategy should be adopted when selecting collaborative teams. First, high-link-strength hub institutions should be identified, with priority given to teams with a total link strength greater than 80 and an average annual publication output exceeding five papers (such as University College London and the University of T\u0026uuml;bingen). These institutions are characterized by dense node connection lines and spanning multiple research clusters in the collaboration network depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA. Second, highly active institutions should be tracked, with a focus on red nodes in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB that have an average publication year after 2018, such as the Chinese Academy of Sciences, which has shown a significant fluctuating upward trend in publication output between 2018 and 2022. Finally, the compatibility of international cooperation should be assessed, with teams that have at least five co-authored papers with international partners being selected. It is recommended that new researchers prioritize teams with a total link strength higher than 50 and a record of transnational co-authorship in the past three years when choosing institutions, in order to enhance the visibility and translational efficiency of research outcomes. By integrating the three dimensions of institutional influence, technical complementarity, and cooperation maturity, researchers can systematically optimize their team selection decisions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eJournal Distribution and Research Synergies\u003c/h2\u003e \u003cp\u003eThe journal analysis shows that mitophagy research in PD is highly concentrated, with 22 core journals (Zone 1) accounting for most publications. \u003cem\u003eAutophagy\u003c/em\u003e (IF\u0026thinsp;=\u0026thinsp;14.6,Q1) stands out with 55 publications, establishing its authority in mitophagy research. Other core journals, such as \u003cem\u003eInternational Journal of Molecular Sciences\u003c/em\u003e and \u003cem\u003eCells\u003c/em\u003e, also have high impact factors, reflecting researchers' preference for disseminating findings through high-impact platforms. However, this concentration could be risky if editorial policies or review preferences of core journals change, potentially disrupting the balanced spread of knowledge. Meanwhile, the cumulative impact of 356 peripheral journals (Zone 3), despite their lower individual contributions, may create a\"long-tail effect\" highlighting the potential value of niche topics.\u003c/p\u003e \u003cp\u003eVOSviewer clustering analysis reveals that mitophagy research in PD can be divided into four distinct thematic clusters of journals. Cluster 1 (red) centers on molecular mechanisms and neuroprotection, with key journals including \u003cem\u003eInternational Journal of Molecular Sciences\u003c/em\u003e, \u003cem\u003eCells\u003c/em\u003e, \u003cem\u003eFrontiers in Neuroscience\u003c/em\u003e, \u003cem\u003eMolecular Neurobiology\u003c/em\u003e, and \u003cem\u003eAntioxidants\u003c/em\u003e, focusing on mitochondrial quality control and oxidative stress mechanisms. Cluster 2 (green) is dominated by genetics and disease modeling, featuring journals such as \u003cem\u003eHuman Molecular Genetics\u003c/em\u003e, \u003cem\u003ePLOS Genetics\u003c/em\u003e, \u003cem\u003eMitochondrion\u003c/em\u003e, \u003cem\u003eBiochimica et Biophysica Acta-Molecular Basis of Disease\u003c/em\u003e, and \u003cem\u003eJournal of Neurochemistry\u003c/em\u003e, which concentrate on the regulation of mitophagy by PD-related gene mutations. Cluster 3 (blue) focuses on core autophagy mechanisms, covering journals like \u003cem\u003eAutophagy\u003c/em\u003e, \u003cem\u003eJournal of Biological Chemistry\u003c/em\u003e, \u003cem\u003eCellular and Molecular Life Sciences\u003c/em\u003e, \u003cem\u003eEMBO Journal\u003c/em\u003e, and \u003cem\u003eScience Advances\u003c/em\u003e, which delve into autophagosome formation and regulatory networks. Cluster 4 (yellow) bridges clinical translation and technological application, with journals such as \u003cem\u003enpj Parkinson's Disease\u003c/em\u003e, \u003cem\u003eMovement Disorders\u003c/em\u003e, \u003cem\u003ePhytomedicine\u003c/em\u003e, \u003cem\u003eCell Death\u0026amp;Disease\u003c/em\u003e, and \u003cem\u003eCNS Neuroscience\u0026amp;Therapeutics\u003c/em\u003e exploring new therapeutic technologies targeting mitochondria.\u003c/p\u003e \u003cp\u003eNotably, top-tier interdisciplinary journals like \u003cem\u003eNature\u003c/em\u003e, despite their relatively low volume of publications (Fig.\u0026nbsp;7B), often feature breakthrough studies, as indicated by their high average normalized citation rates (deep red nodes). \u003cem\u003eNature\u003c/em\u003e's research on mitophagy in PD has been pivotal in integrating molecular mechanisms, pathological associations, and targeted therapies. Seminal studies include the elucidation of the PARKIN-dependent ubiquitylome in response to mitochondrial depolarization[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], genome-wide RNAi screens identifying regulators of parkin upstream of mitophagy[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e], and the role of USP30 in opposing parkin-mediated mitophagy[\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Structural studies have detailed the activation mechanism of Parkin by phosphorylated ubiquitin[\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], the interaction mode of PINK1 with ubiquitin[\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e], and the mechanism of Parkin activation by PINK1[\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. These studies have precisely explained the mechanisms of early-onset PD mutations. Research has also expanded into the gut-brain axis, revealing how intestinal infections can trigger neuronal immune attacks via mitochondrial antigens[\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Cryo-electron microscopy capturing the full activation pathway of PINK1[\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e] provides an atomic-level blueprint for targeted interventions. In contrast, high-volume journals like \u003cem\u003eAutophagy\u003c/em\u003e focus more on in-depth analysis of mechanistic details, forming a complementary pattern where top-tier journals set the direction and specialized journals deepen the research.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eAuthor Productivity and Collaborative Networks\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e, the actual distribution of author productivity significantly deviates from Lotka's Law, with a much higher proportion of authors contributing only one publication (78.6% vs. the predicted 62%). This suggests a large number of short-term participants or interdisciplinary collaborators. This pattern may result from the need to integrate knowledge across multiple disciplines, such as neurodegenerative disease mechanisms, cell biology, and molecular genetics. Among authors with two or more publications, the actual proportions are consistently lower than Lotka's Law predictions, indicating a highly concentrated core research group in the field.\u003c/p\u003e \u003cp\u003eThe research area is marked by a collaborative network centered on key scholars and institutions. Hattori Nobutaka from Juntendo University and Richard J.Youle from the National Institute of Neurological Disorders and Stroke (NINDS) have emerged as cornerstones of the field, with Hattori Nobutaka publishing 28 papers and Richard J.Youle's work being cited 12,235 times. Hattori Nobutaka's team focuses on the roles of PINK1 and Parkin genes in PD and their functions in mitochondrial quality control. Their studies have revealed that PINK1 phosphorylates the ubiquitin-like domain (Ubl) of Parkin upon loss of mitochondrial membrane potential, promoting Parkin translocation to and activation on mitochondria, thereby triggering mitophagy[\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. They also found that mitochondrial dysfunction caused by PINK1 deficiency is associated with defects in the respiratory chain rather than proton leak[\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. In animal models, Hattori Nobutaka further confirmed that Parkin deficiency impairs mitochondrial turnover and leads to dopaminergic neuronal loss[\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. Richard J.Youle's team has elucidated the critical mechanisms of PINK1 and Parkin in regulating mitophagy[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. They discovered that PINK1 stability is regulated by mitochondrial membrane potential and identified several proteins regulating the PINK1/Parkin pathway, such as TOMM7, HSPA1L, and BAG4[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. They also found that Rab protein cycling in the endoplasmic reticulum plays an important role in Parkin-mediated mitophagy[\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. These findings have advanced our understanding of PD pathogenesis and laid a solid foundation for the field. Notably, the institutional distribution shows that McGill University (with Edward A. Fon and Jean-Francois Trempe ) and Mayo Clinic (with Springer Wolfdieter and Fabienne C. Fiesel) each have two scholars in the top ten. Their total link strengths (184/120 for McGill and 273/256 for Mayo) are relatively high, indicating stable and efficient collaborative mechanisms within these institutions.\u003c/p\u003e \u003cp\u003eThe co-authorship network map (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e10\u003c/span\u003eA) shows a hierarchical structure with scholars like Hattori Nobutaka, Richard J. Youle, Springer Wolfdieter, and Edward A. Fon as central hubs. These researchers have published at least 20 papers each and connect multiple clusters, acting as bridges in cross-team collaborations. Emerging peripheral networks represent potential research frontiers, such as new genetic regulators or therapeutic targets. These groups, though currently small, may play a pivotal role in future research and require sustained funding and mentorship to enhance their impact. Figure\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e11\u003c/span\u003eB highlights Richard J. Youle's dominance through a color gradient of average normalized citations (darker red indicates higher impact). Node colors also reflect differences in research timelines: Fon and Trempe have redder nodes (more recent publications), while Richard J. Youle and Springer Wolfdieter have bluer nodes (earlier publications).\u003c/p\u003e \u003cp\u003eCollaboration and institutional support are key to advancing research in this field. While top scholars have made significant contributions, emerging researchers and small teams need support to prevent knowledge gaps. Interdisciplinary integration can improve research efficiency and address the complexity of PD pathogenesis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eHotspots and Frontiers\u003c/h2\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eCore Mechanisms and Dominant Pathways\u003c/h2\u003e \u003cp\u003eKeyword analysis in the field of mitophagy in PD reveals dynamic shifts in research paradigms and core scientific questions. Research has consistently focused on the PINK1-Parkin pathway, as evidenced by the high frequency and strong co-occurrence of keywords \"PINK1\" (220 occurrences) and \"Parkin\" (266 occurrences), with total link strengths of 1243 and 1468, respectively. This indicates that the pathway has continuously dominated the research framework since its early discovery and highlights the complexity of its regulatory mechanisms. PINK1 is a mitochondrial protein kinase that accumulates on the outer mitochondrial membrane when mitochondria are damaged or depolarized, recruiting Parkin. Parkin then ubiquitinates damaged mitochondria, marking them for autophagic degradation[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].This pathway is not only involved in mitochondrial quality control but also plays roles in oxidative stress and metabolic regulation[\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. The PINK1-Parkin pathway also interacts with other autophagy pathways, such as those mediated by FUNDC1 and BNIP3L, to maintain cellular metabolic balance[\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. In PD, loss of PINK1 and Parkin function leads to impaired mitophagy, resulting in neuronal damage and death[\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e].Therapeutic strategies targeting the PINK1-Parkin pathway are emerging as a research focus. Activation of this pathway can enhance mitophagy, improving mitochondrial function and cell survival. For example, certain small molecules have been identified to activate the PINK1-Parkin pathway, promoting mitochondrial clearance and cellular protection[\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Inhibition of the deubiquitinase USP30 has been shown to enhance Parkin activity, restoring mitochondrial quality[\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eMitochondrial Quality Control\u003c/h2\u003e \u003cp\u003eThe prominence of keywords such as \"mitochondrial dynamics\" (rank 10), \"mitochondrial quality control\" (rank 17), and \"mitochondrial biogenesis\" (rank 20) reflects a paradigm shift in research from a singular focus on autophagy mechanisms to an integrated multimodal quality control network. Mitochondrial quality control (MQC) integrates mitochondrial dynamics (fusion and fission), mitochondrial biogenesis, and mitophagy to maintain mitochondrial integrity and cellular homeostasis[\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMitochondrial fission, mediated by Drp1, is a critical step in the autophagy process, facilitating the clearance of damaged mitochondria to maintain cellular health[\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e]. Studies show that fission and autophagy are closely linked: fission not only provides sufficient mitochondrial fragments for autophagy but also regulates autophagy efficiency through signaling pathways[\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. Inhibition of mitochondrial fission impairs autophagy, exacerbating cellular damage and death[\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e]. Conversely, mitochondrial fusion, mediated by MFN1/2, delays autophagy initiation through content mixing, creating a \"damage buffering\" mechanism. By diluting abnormal signals (e.g.,oxidatively damaged proteins), fusion postpones autophagy[\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. However, MFN2 has been shown to have dual functions in cardiomyocyte injury: it maintains mitochondrial quality through fusion and induces mitophagy by activating Parkin translocation and phosphorylation, clearing damaged mitochondria and protecting cells[\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e]. Recent studies have revealed that the imbalance between mitophagy and mitochondrial biogenesis is a core mechanism underlying dopaminergic neuronal degeneration. PINK1/Parkin mutations not only impair mitophagy but also inhibit PGC-1α activity through PARIS protein accumulation[\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e].This dual defect creates a vicious cycle: impaired mitophagy leads to the accumulation of damaged mitochondria, while insufficient biogenesis prevents neurons from compensating with functional mitochondria, ultimately exacerbating oxidative stress and energy metabolic collapse.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eα-synuclein\u003c/h2\u003e \u003cp\u003ePD is marked by abnormal α-synuclein aggregation, which is key to its pathogenesis. Lurette et al. controlled α-synuclein aggregation using optogenetic tools and found it significantly impacts mitophagy. The aggregates cause mitochondrial depolarization, reduced ATP, fission, and mitophagy via cardiolipin externalization, and lower mitochondrial content in dopaminergic neurons and mouse midbrains. This shows that aggregation, not overexpression, of α-synuclein drives mitophagy and mitochondrial dysfunction, offering new insights into PD[\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e]. Additionally, the abnormal accumulation of α-synuclein disrupts mitochondrial function and disturbs the dynamic balance of mitophagy, thereby promoting neuronal degeneration[\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e, \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e]. Shaltouki et al. analyzed PD patient brains, neurons, and fly models and found that α-synuclein accumulation upregulates Miro protein levels. Miro, a mitochondrial outer membrane protein, is involved in mitochondrial movement and clearance of damaged mitochondria. In PD neurons, Miro abnormally accumulates on mitochondria, delaying mitophagy. α-synuclein interacts with Miro via its N-terminus, driving Miro upregulation. Reducing Miro levels rescues mitophagy and neurodegeneration. This study underscores the role of mitochondrial-associated α-synuclein in PD and identifies Miro as a potential therapeutic target[\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e]. Abnormal aggregation of α-synuclein activates the p38 MAPK pathway, phosphorylating Parkin at Ser131 and impairing its function. This disrupts mitophagy, worsening mitochondrial dysfunction and neuronal death in the A53T α-synuclein model. Inhibiting p38 MAPK activity reduces apoptosis, restores mitochondrial membrane potential, and increases synaptic density[\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e]. Yin et al. showed that Nur77 is key to regulating α-synuclein aggregation and mitophagy using STI571 and antibodies. STI571 inhibits PHB2 Y121 phosphorylation, reduces α-synuclein aggregates, and boosts autophagy. Nur77 moves to mitochondria in the presence of α-synuclein, enhancing PHB-mediated mitophagy and reducing mitochondrial dysfunction. In α-synuclein PFF mouse models, Nur77 overexpression lowers pS129-α-synuclein levels and protects dopaminergic neurons, likely via the p-c-Abl/p-PHB2 Y121 axis. This suggests Nur77 and STI571 could be potential therapeutic targets for PD[\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe natural compound quercetin upregulates PINK1/Parkin expression, reduces α-synuclein aggregation, and improves mitochondrial quality control in 6-OHDA-induced models[\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e]. These findings suggest that modulating the balance between mitophagy and α-synuclein aggregation may represent a novel therapeutic strategy for PD.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eNeuroinflammation and Ferroptosis\u003c/h2\u003e \u003cp\u003eThe rising trends of \"neuroinflammation\" and \"ferroptosis\" (Figs.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e12\u003c/span\u003e and \u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e13\u003c/span\u003eA) highlight the growing emphasis on the interplay between multiple mechanisms in the field. Mitophagy, primarily mediated by the PINK1/Parkin pathway, is crucial for maintaining mitochondrial homeostasis. Dysfunction in this pathway leads to the accumulation of damaged mitochondria, resulting in mitochondrial DNA (mtDNA) leakage and reactive oxygen species (ROS) accumulation. These changes activate the cGAS-STING signaling pathway and the NLRP3 inflammasome, promoting the release of pro-inflammatory cytokines such as IL-1β and IL-6, and inducing microglial polarization towards the pro-inflammatory M1 phenotype[\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e, \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e, \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e, \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e]. Targeting mitophagy has been shown to effectively alleviate neuroinflammation. For instance, the natural compound Urolithin A enhances PINK1/Parkin-dependent mitophagy and inhibits NLRP3 inflammasome activation[\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e]. Similarly, Repaglinide activates mitophagy and modulates endoplasmic reticulum stress, inhibiting glial cell activation and neuroinflammation, thereby reducing dopaminergic neuronal apoptosis[\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFerroptosis, a form of iron-dependent lipid peroxidation-driven cell death, is closely intertwined with mitophagy in neurodegenerative processes. ROS accumulation from mitochondrial dysfunction can exacerbate neuronal damage via ferroptosis pathways. For example, neurotoxins like rotenone induce excessive ROS generation, activating ferroptosis markers (e.g.,GPX4 downregulation, COX2 and NCOA4 upregulation) while inhibiting autophagy flux and enhancing mitophagy markers (e.g.,LC3 and p62), ultimately leading to dopaminergic neuronal death[\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e]. Iron metabolism disturbances, such as iron deposition and transferrin receptor abnormalities, form a vicious cycle with mitophagy dysregulation in disease models. For instance, bifenthrin exposure exacerbates the synergistic effects of mitophagy and ferroptosis by binding to iron transport proteins (Tf) and GPX4[\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e]. Additionally, ferritin heavy chain 1 (FTH1) regulation is prominent in 6-OHDA models, where inhibiting ferritinophagy reduces ferroptosis and improves mitochondrial function, suggesting therapeutic potential in targeting iron metabolism and mitochondrial quality control[\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e]. These findings indicate that mitophagy and ferroptosis are not isolated events in neurodegenerative pathology but form a positive feedback loop through mechanisms involving oxidative stress, iron homeostasis imbalance, and energy metabolism disruption. Future research should focus on elucidating the spatiotemporal regulatory networks between these processes to inform the development of dual-target therapeutic strategies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eChallenges and Future Directions\u003c/h2\u003e \u003cp\u003eDespite the prominence of keywords such as \"ubiquitination\" (rank 12) and \"oxidative stress\" (rank 9), which point to numerous potential therapeutic targets, the frequency of terms related to translational medicine, such as\"therapeutic targets\" and \"biomarkers\" does not match their scientific importance. This reflects systemic barriers in translating preclinical findings into clinical applications. Firstly, the mechanisms underlying mitophagy are complex and dynamically balanced, making precise modulation challenging. For instance, although the PINK1/Parkin pathway is extensively studied, most PD patients lack mutations in these genes, and the roles of other regulatory pathways (such as NIX and FUNDC1) are not fully understood. Intervention strategies need to be differentiated based on disease stages (compensatory vs.decompensatory phases). Secondly, existing animal and cell models fail to replicate the progressive impairment of mitophagy and the in vivo microenvironment interactions seen in human PD, limiting the reliability of drug screening. While induced pluripotent stem cell (iPSC) models, a recent focus highlighted by the keyword \"fibroblasts\" provide a humanized platform for mechanistic studies, their limitations in simulating aging-related microenvironments need to be overcome. Thirdly, drug development is hampered by low brain delivery efficiency, insufficient targeting specificity (which may interfere with other autophagy pathways), and individual genetic heterogeneity (e.g.,variable treatment responses in patients with LRRK2 or GBA mutations). Moreover, the clinical translation of mitophagy-related therapies is impeded by the lack of biomarkers that can monitor mitophagy activity in real time. Neuroprotective efficacy requires long-term follow-up for validation, whereas current clinical trials often rely on short-term improvements in motor symptoms as surrogate endpoints, potentially leading to biased results. Additionally, since PD pathology involves the interplay of multiple pathways (such as α-synuclein aggregation and oxidative stress), targeting mitophagy alone may be insufficient to halt disease progression. Synergistic regulation of other mechanisms (such as mitochondrial biogenesis or anti-inflammatory pathways) is needed, but the complexity and risk of side effects associated with multi-target drug development are significantly increased. Breaking these bottlenecks will require the integration of novel disease models (such as 3D brain organoids), precise delivery technologies (optimizing AAV vectors or nanoparticles), and interdisciplinary strategies (such as AI-assisted compound screening)to advance the clinical translation of mitophagy-related therapies.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eOur study provides a comprehensive overview of mitophagy research in PD using bibliometric techniques. However, several limitations are inherent to our approach. Firstly, our dataset is derived solely from the Web of Science Core Collection, potentially omitting relevant articles from other databases. Secondly, our analysis is confined to English-language literature, which may introduce bias. Lastly, the presence of homonymous authors or different expressions of the same author may affect the accuracy of our collaborative network analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur analysis of mitophagy research in PD from 2007 to 2024 reveals several key findings. The United States is the leading country in terms of publication output, followed by China. McGill University is the most prolific institution, while the journal \u003cem\u003eAutophagy\u003c/em\u003e is the most frequent publication venue, with \u003cem\u003eInternational Journal of Molecular Sciences\u003c/em\u003e ranking second. Hattori Nobutaka, is the most prolific author, followed by Edward A. Fon. Research foci include \"pink1/parkin\", \"mitochondrial quality control\" and α-synuclein, with neuroinflammation and ferroptosis emerging as hotspots. These findings provide a comprehensive overview of the field, highlighting critical insights into current research trajectories. We anticipate that these insights will help researchers better understand prevailing trends in mitophagy research in PD and guide future investigative endeavors.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eConflict of Interest\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Shanghai Municipal Commission of Health (shzyyzdxk-2024108).\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThis work was supported by the Shanghai Municipal Commission of Health (shzyyzdxk-2024108).\u003c/p\u003e \u003cp\u003e \u003cb\u003eAuthor Contribution\u003c/b\u003e J.Q.Z. conceptualized the study, designed the research framework, conducted the literature search and data collection, analyzed the data, interpreted the results, and wrote the initial draft. Q.W., Y.C. and H.M.S.,assisted in data analysis and interpretation, and edited the manuscript. S.F.X. supervised the study, conducted the final data analysis and interpretation, wrote and edited the manuscript, and managed the submission process.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e \u003cp\u003eNo datasets were generated or analysed during the current study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLuo Y, Qiao L, Li M, Wen X, Zhang W, Li X (2025) Global, regional, national epidemiology and trends of Parkinson\u0026rsquo;s disease from 1990 to 2021: findings from the Global Burden of Disease Study 2021. 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Advance online publication. https://doi.org/10.1007/s12035-025-04824-6\u003c/li\u003e\n\u003cli\u003eZhang Y, Zhang B (2024) Bifenthrin Caused Parkinson\u0026apos;s-Like Symptoms Via Mitochondrial Autophagy and Ferroptosis Pathway Stereoselectively in Parkin\u0026minus;/\u0026minus; Mice and C57BL/6 Mice. Molecular Neurobiology 61(11):9694\u0026ndash;9707. https://doi.org/10.1007/s12035-024-04140-5\u003c/li\u003e\n\u003cli\u003eTian Y, Lu J, Hao X, Li H, Zhang G, Liu X, Li X, Zhao C, Kuang W, Chen D, Zhu M (2020) FTH1 Inhibits Ferroptosis Through Ferritinophagy in the 6-OHDA Model of Parkinson\u0026apos;s Disease. Neurotherapeutics 17(4):1796\u0026ndash;1812. https://doi.org/10.1007/s13311-020-00929-z\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"hereditas","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"here","sideBox":"Learn more about [Hereditas](http://hereditasjournal.biomedcentral.com/)","snPcode":"41065","submissionUrl":"https://submission.nature.com/new-submission/41065/3","title":"Hereditas","twitterHandle":"@OAgenetics","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Parkinson’s disease, Mitophagy, Bibliometric analysis, PINK1/Parkin","lastPublishedDoi":"10.21203/rs.3.rs-6944875/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6944875/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eParkinson\u0026rsquo;s disease (PD) is closely linked to mitochondrial dysfunction and mitophagy, a key mechanism in PD pathogenesis. However, no dedicated bibliometric analysis of mitophagy in PD exists. This study used data from the Web of Science Core Collection to map the global research landscape of mitophagy in PD. The analysis of 1,578 publications (2007\u0026ndash;2024) identifies the United States as the most productive country. McGill University ranks as the top institution, and Nobutaka Hattori is the most prolific author. The journal \u003cem\u003eAutophagy\u003c/em\u003e is the journal with the highest number of publications in this field. Core research themes included PINK1/Parkin, mitochondrial quality control, α-synuclein, neuroinflammation, and ferroptosis. The study provides insights into the current status of global collaboration and translational progress in this field. Future efforts should aim to further explore new pathways, enhance clinical translation, and promote collaborative partnerships to advance research and address challenges in the field.\u003c/p\u003e","manuscriptTitle":"Mapping the Global Research Landscape of Mitophagy in Parkinson's Disease: A Bibliometric and Visualization Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-26 13:32:11","doi":"10.21203/rs.3.rs-6944875/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-03T17:25:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-02T07:14:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"274895034576147276283070704766603287400","date":"2025-06-30T14:16:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"130360540983220250934217381764699896138","date":"2025-06-29T09:43:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-28T11:53:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"188235928107415736115043317744505629378","date":"2025-06-28T03:06:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-25T07:26:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"202258421251316536142232389122169698758","date":"2025-06-25T06:42:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"121271160581816065438068027834320868706","date":"2025-06-24T19:59:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"201057592406890916828669954637699078523","date":"2025-06-24T13:03:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-24T09:08:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-24T08:58:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-23T06:47:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"Hereditas","date":"2025-06-21T12:08:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"hereditas","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"here","sideBox":"Learn more about [Hereditas](http://hereditasjournal.biomedcentral.com/)","snPcode":"41065","submissionUrl":"https://submission.nature.com/new-submission/41065/3","title":"Hereditas","twitterHandle":"@OAgenetics","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"453d172d-ed18-4fb2-a568-0ac75af56f26","owner":[],"postedDate":"June 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-24T16:06:16+00:00","versionOfRecord":{"articleIdentity":"rs-6944875","link":"https://doi.org/10.1186/s41065-025-00544-y","journal":{"identity":"hereditas","isVorOnly":false,"title":"Hereditas"},"publishedOn":"2025-11-20 15:58:10","publishedOnDateReadable":"November 20th, 2025"},"versionCreatedAt":"2025-06-26 13:32:11","video":"","vorDoi":"10.1186/s41065-025-00544-y","vorDoiUrl":"https://doi.org/10.1186/s41065-025-00544-y","workflowStages":[]},"version":"v1","identity":"rs-6944875","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6944875","identity":"rs-6944875","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}