Inhibition of Lipid Accumulation in NAFLD Liver by Extract of Rosa laevigata Fruit Extract through Activation of the PI3K-AKT Signaling Pathway

Inhibition of Lipid Accumulation in NAFLD Liver by Extract of Rosa laevigata Fruit Extract through Activation of the PI3K-AKT Signaling Pathway | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Inhibition of Lipid Accumulation in NAFLD Liver by Extract of Rosa laevigata Fruit Extract through Activation of the PI3K-AKT Signaling Pathway Pengbo NI, Yaoyao WANG, Pinyi GAO, Danqi LI, Xuegui LIU This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6926759/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Non-Alcoholic Fatty Liver Disease (NAFLD) is a chronic metabolic disorder primarily characterized by lipid accumulation in the liver, which is its main pathological feature. The fruit of Rosa laevigata Michx (RLF) is recognized for its diverse bioactive properties and has garnered significant attention for its potential use in developing dietary supplements for NAFLD treatment. However, its lipid-lowering efficacy and underlying mechanisms remain unclear. To investigate this, we developed an NAFLD cell model by treating HepG2 cells with oleic acid and evaluated the lipid-lowering effects of RLF extract. The effectiveness was measured using five indicators: triglycerides (TG), total cholesterol (T-CHO), low-density lipoprotein cholesterol (LDL-C), aspartate transaminase (AST), and alanine transaminase (ALT). The lipid-lowering mechanism was predicted using HPLC-MS alongside network pharmacology. Antioxidant ability was evaluated using DPPH and ABTS assays, with three indicators—total antioxidant capacity (T-AOC), superoxide dismutase (SOD), and malondialdehyde (MDA)—used to assess antioxidant effects. Additionally, Western blotting (WB) was employed to validate the network pharmacology predictions. Results indicated that, compared to the model group, the RLF extract significantly reduced TG, T-CHO, LDL, AST, and ALT levels by 55.9%, 37.1%, 25.3%, 67.5%, and 51.1%, respectively. T-AOC and SOD levels were significantly increased by 182.5% and 136.8%, respectively, while MDA content was reduced by 47.3%. WB analysis indicated that the RLF extract alleviated abnormalities in lipid metabolism and antioxidant-related genes PI3K and p-AKT. These findings suggest that the therapeutic effects of RLF extract on NAFLD may be mediated by the modulation of oxidative damage responses via the PI3K-AKT signaling pathway. Biological sciences/Drug discovery/Target identification Biological sciences/Drug discovery/Target validation Health sciences/Diseases/Metabolic disorders Rosa laevigata Fruit Non-Alcoholic Fatty Liver Disease network pharmacology Cell fat accumulation model Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction NAFLD is a metabolic disorder of the liver characterized by the excessive accumulation of fat in liver tissue, which is not linked to alcohol consumption 1 . Typically, NAFLD is diagnosed when fat constitutes more than 5–10% of liver weight. There are two forms of NAFLD: simple fatty liver and non-alcoholic steatohepatitis (NASH) 2 . Simple fatty liver generally does not pose serious health risks, whereas NASH can lead to liver inflammation and fibrosis, potentially progressing to severe conditions such as cirrhosis and liver cancer 3 . NAFLD is often associated with metabolic disorders such as obesity, diabetes, and hypertension, as well as lifestyle factors like poor diet and insufficient physical activity. The prevalence of NAFLD varies across regions and populations but generally shows an increasing trend. Based on global studies and surveys, NAFLD has emerged as a prevalent chronic liver condition worldwide. In some countries, particularly developed nations, the prevalence of NAFLD exceeds that of traditional alcohol-related liver disease. As obesity, diabetes, and metabolic syndrome become more common, the incidence of NAFLD is on the rise. It is estimated that approximately 25–30% of adults worldwide are affected by NAFLD. In certain groups, such as individuals with hyperlipidemia, patients with type 2 diabetes, and those with metabolic syndrome, the likelihood of having the disease may reach up to 50%.In summary, NAFLD has emerged as a significant public health issue globally, underscoring the need for effective prevention and management strategies. An increasing number of clinicians and researchers worldwide have embraced traditional Chinese medicine due to its minimal side effects and consistent therapeutic benefits 4, 5 . RLF is the dried fruit of Rosa laevigata Michx, a species within the Rosaceae family. Widely distributed in southern China, the fruits contain various active compounds, including flavonoids, lignins, polyphenols, steroids, triterpenoids, polysaccharides, and other bioactive substances 6 . In the realm of Traditional Chinese Medicine (TCM), RLF is recorded in the "Shu Ben Cao," authored by Han Baosheng between 935 and 960 ADS, and has since been integrated into the "Chinese Pharmacopoeia." This herb is recognized for its association with the bladder, kidney, and large intestine meridians and is known for its effects in reducing urination frequency, consolidating kidney essence, and controlling bowel movements to treat conditions such as steatorrhea, frequent urination, bleeding, and diarrhea 7 . Recent studies have shown that RLF possesses multiple pharmacological activities, including antioxidant, anti-inflammatory, antimicrobial, and lipid-lowering effects 8 . It also plays a significant role in immune regulation, providing benefits for liver and kidney protection as well as lipid reduction. Research conducted by Liu et al. demonstrated that the flavonoids in RLF exhibit scavenging properties against free radicals, such as 2,2-diphenyl-1-picrylhydrazyl (DPPH) 9 , hydroxyl radicals, and superoxide anions, showcasing significant reducing capabilities 10 . Oral administration of RLF extract at doses of 25 and 50 mg/kg/day for four weeks in mice fed a high-fat diet resulted in a notable increase in various antioxidant levels in the liver, including catalase (CAT), SOD, GSH, and glutathione peroxidase (GPX) 11 . Furthermore, total flavonoids from RLF dose-dependently reduced the concentration of hepatic MDA. Traditional Chinese Medicine is characterized by its “multicomponent, multitarget, and multipath way” effects, which collectively regulate biological networks in the body to achieve a synergistic therapeutic function. Understanding the mechanisms of traditional Chinese medicine through conventional experiments can be challenging; therefore, a systematic analysis of these mechanisms is essential 12, 13 . Network pharmacology is a novel and comprehensive research approach that utilizes techniques such as bioinformatics, systems biology, and computational chemistry to explore the interactions between traditional Chinese medicine and the molecular, cellular, and tissue components within organisms 14 . By integrating vast amounts of bioinformatics, cheminformatics, and pharmacological data, it aims to understand drug mechanisms at a systemic level and uncover interactions between drugs and multiple targets 15, 16 . This approach provides a theoretical basis for the design of multi-target drugs 17 . In traditional Chinese medicine, most single herbs and formulas exhibit both multicomponent and multitarget properties. However, elucidating the scientific foundations of traditional Chinese medicine from molecular and systemic perspectives remains a significant challenge. Thus, this field lends itself well to integration with network pharmacology. This study employed HPLC-QTOF-MS/MS technology to analyze the chemical composition of RLF 18 . Using network pharmacology approaches, it predicted the mechanism of action of RLF in combating NAFLD, identifying a total of 48 compounds, 126 protein targets, and 20 signaling pathways. Additionally, the study constructed both a compound-target network and a pathway-target network 19 . Gene Ontology (GO) analysis and KEGG enrichment analysis were conducted to gather biological insights. Furthermore, the outcomes of the network analysis were corroborated through in vitro biological experiments 20 . Overall, this study provides scientific evidence to support the use of RLF in the treatment of NAFLD and demonstrates the effectiveness of modern technology in exploring the value of traditional Chinese medicine 21 . 2. Materials and methods 2.1 Chemicals reagents and materials Rosa laevigata fruits were harvested from Bo Zhou, Anhui. Phosphate-buffered solution (PBS) was purchased from Boster Biological Technology Co., Ltd. (Wuhan, China). The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium bromide (MTT) was obtained from Beijing Solarbio Science & Technology Co., Ltd. (Beijing, China). Fetal bovine serum (FBS) was sourced from Clark Bioscience (Richmond, VA, USA). Dimethyl sulfoxide (DMSO), Dulbecco’s Modified Eagle’s Medium (high glucose) (DMEM), trypsin, penicillin (10 kU/mL), and streptomycin (10 mg/mL) were purchased from Thermo Fisher Scientific Co., Ltd. (Beijing, China). Oleic acid (OA), 2,2-Diphenyl-1-picrylhydrazyl (DPPH), and 2,2'-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) were obtained from Shanghai Macklin Biochemical Co., Ltd. (Shanghai, China). Kits for detecting total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) were purchased from Jiancheng Technology Co., Ltd. (Nanjing, China). The Bicinchoninic Acid (BCA) protein assay kit, superoxide dismutase (SOD) assay kit, malondialdehyde (MDA) assay kit, total antioxidant capacity (T-AOC) assay kit, and Oil Red O staining kit (ORO) were sourced from Beyotime Biotechnology Co., Ltd. (Shanghai, China). The secondary antibody was obtained from Beijing Bioss Biotechnology Co., Ltd. (Beijing, China). All other analytical-grade reagents were purchased locally. 2.2 Sample Preparation Rosa laevigata fruit samples were cut into fragments and subjected to ethanol extraction at a sample-to-ethanol ratio of 1:10 (g/mL) at 60°C for 3 hours. The extract was then filtered and concentrated to a thick paste using a rotary evaporator at 60°C under vacuum. This thick paste was dried in a controlled oven until the weight remained constant, yielding ethanol extracts from RLF, which were then stored at − 20°C 22 . 2.3 RLF by HPLC-Q-TOF-MS/MS Table 1 presents the gradient elution procedure for chromatographic analysis. Solvent A consists of 0.1% formic acid, while solvent B is acetonitrile. The temperature of the chromatographic column (Sepax GP-C18 Column) was set to 40°C, with a flow rate of 0.3 mL/min. In positive ion mode, the spray voltage and nebulizer temperature were set to 5500 V and 500°C, respectively. In negative ion mode, these settings were adjusted to 4400 V and 450°C, respectively. The scanning range for the first-order mass spectrum was m/z 100–1200, while the second-order mass spectrum scanned from m/z 50-1000. The collision-induced dissociation (CID) voltage was set to ± 60 V, with a collision energy of 35 ± 15 eV 23, 24 . Table 1 Chromatographic gradient elution procedure. Time(min) A(%) B(%) 0 95 5 10 30 70 17 0 100 18 0 100 19 95 5 21 95 5 2.4 RLF-NAFLD Network Pharmacology Analysis Using UPLC-Q-TOF-MS/MS analysis to identify the chemical composition of RLF, we gathered compound targets from several databases, including TCMSP, HERB, PubChem, STITCH, Swiss Target Prediction, Similarity Ensemble Approach (SEA), and TargetNet 25 . We retrieved keywords such as "NAFLD," "nonalcoholic fatty liver," and "fatty liver" from OMIM, PharmGKB, GeneCards, DrugBank, and the Therapeutic Target Database (TTD) to identify relevant disease targets 26, 27 . The direct disease targets were inputted into the String database to broaden the disease network, with a minimum required interaction score set at 0.900 for the highest confidence level. The resulting extended disease targets, along with the direct disease targets, were then utilized as wound-related disease targets 28 . Subsequently, the results from the aforementioned databases were compiled, deduplicated, and standardized in UniProt to derive the RLF-related compound targets and NAFLD disease targets. Common targets between the compounds and the disease were identified using the OmicShare tool. These shared targets were then analyzed through a protein-protein interaction (PPI) network using the String database 29 , with the species set to "Homo sapiens" and a confidence threshold of over 0.900. All networks were visualized using Cytoscape 3.6.0 software (Bethesda, MD, USA). The network construction proceeded as follows: (1) the PPI network for common targets and (2) the RLF-Compound-Target network 30 . 2.5 KEGG and GO Enrichment Analysis GO and KEGG are widely used methods for identifying common functions among genes based on biological ontologies 31 . NAFLD-related disease targets were submitted to the Metascape online platform to perform KEGG and GO enrichment analyses. The option 'H sapiens' (human) was selected for custom analysis under the 'Input/Analysis as Species' section. Under the 'Functional Set,' 'Pathway,' and 'Structural Complex' options, KEGG and GO analyses were chosen for their respective evaluations. The results of the GO functional and KEGG pathway enrichment analyses were then exported as a ZIP file for visualization and graphical analysis using an online bioinformatics platform 32 . 2.6 Establishment NAFLD cells model with HepG2 cells Human HepG2 liver cancer cells were purchased from the Chinese Academy of Sciences (Beijing) Cell Bank (Beijing, China). HepG2 cells were plated in 6-well plates at a density of 10,000 to 30,000 cells per well in high-glucose DMEM containing 10% FBS and then incubated at 37°C with 5% CO2 for 24 hours. The supernatant of the control group was replaced with 2 mL of culture medium, while the model group was treated with 2 mL of culture medium containing 0.15 mmol/L oleic acid (OA) and incubated for an additional 24 hours. The model group was then stained with Oil Red O (ORO) and compared with the control group to determine whether the model was successfully established 33 . 2.7 MTT assay Cell viability was determined by an MTT assay with some modifications to assess the safety of RLF. Human HepG2 liver cancer cells were seeded at a density of 5 × 10³ cells/well in 96-well microculture plates and grown at 37°C with 5% CO2 overnight. The supernatant was then removed. After incubation, the medium was replaced with 100 µL of 1 mg/mL MTT reagent and incubated for another 4 hours at 37°C with 5% CO2. The MTT reagent was removed, and 150 µL of DMSO was added to each well. The plates were shaken for 15 minutes on a table oscillator and analyzed using a microplate reader at 490 nm. Each sample was analyzed three times, and the values were averaged 34 . 2.8 Measurement of intracellular lipid-lowering levels of RLF HepG2 cells were incubated at a density of 2 × 10⁵ cells/mL in 6-well plates. Two milliliters of culture medium were added to the control group; 2 mL of oleic acid (OA) at 0.15 mmol/L was added to the model group; 2 mL of atorvastatin at 0.15 mmol/L was added to the positive group; 1 mL of RLF at 2 mg/mL and 1 mL of OA at 0.3 mmol/L were added to the RLF-L group; 1 mL of RLF at 4 mg/mL and 1 mL of OA at 0.3 mmol/L were added to the RLF-M group; and 1 mL of RLF at 8 mg/mL and 1 mL of OA at 0.3 mmol/L were added to the RLF-H group. After 24 hours of culture, PBS was used to wash the excess culture medium three times. IP cell lysis buffer was then added, and the cells were lysed in an ice bath for 30 minutes. The levels of TG, T-CHO, LDL-C, ALT, and AST were measured following the instructions provided by the manufacturers of the detection kits. The protein concentration in each well was measured using a BCA protein assay kit to standardize the data 35 . 2.9 Measurement of vitro Antioxidant levels of RLF DPPH and ABTS radicals were used to investigate the in vitro antioxidant capacity. DPPH and ABTS were dissolved in ethanol to prepare stock solutions. For the DPPH radical scavenging assay, the control group received a mixture of DPPH solution and 50% ethanol. The sample group received a mixture of DPPH solution with sample solutions at concentrations of 0.005, 0.02, 0.08, 0.3, 0.8, 2, and 5 mg/mL. The sample background group received a mixture of DPPH solution with sample solutions at the same concentrations, along with anhydrous ethanol. Reactions for the DPPH radical scavenging assay were conducted in the dark for 30 minutes, after which the absorbance was measured at 517 nm, and the radical scavenging activity was calculated according to Eq. ( 1 ). For the ABTS radical scavenging assay, reactions were conducted in the dark for 10 minutes, with absorbance measured at 734 nm, and the radical scavenging activity calculated according to Eq. (2): 2.10 Measurement of vivo Antioxidant levels of RLF HepG2 cells were incubated at a density of 2 × 10⁵ cells/mL in 6-well plates. Two milliliters of culture medium were added to the control group; 2 mL of oleic acid (OA) at 0.15 mmol/L was added to the model group; 1 mL of RLF at 2 mg/mL and 1 mL of OA at 0.3 mmol/L were added to the RLF-L group; 1 mL of RLF at 4 mg/mL and 1 mL of OA at 0.3 mmol/L were added to the RLF-M group; and 1 mL of RLF at 8 mg/mL and 1 mL of OA at 0.3 mmol/L were added to the RLF-H group. After 24 hours of culture, PBS was used to wash the excess culture medium three times. IP cell lysis buffer was then added, and the cells were lysed in an ice bath for 30 minutes. The levels of T-AOC, SOD, and MDA were measured according to the instructions provided by the manufacturers of the detection kits. The protein concentration in each well was measured using a BCA protein assay kit to standardize the data. 2.11 Western Blotting IP cell lysis buffer was used to lyse cells from the Control, RLF-L, RLF-M, and RLF-H groups. The protein concentration was measured using a BCA protein assay kit. The protein samples were then stored at -80°C until further analysis. Western blotting was performed to determine the expression levels of AKT, phosphorylated AKT (p-AKT), and β-actin in each group. 2.12 Statistical analysis Each experiment was performed in triplicate for each group. The data were presented as mean ± standard deviation (SD) values and statistically analyzed with one-way analysis of variance, followed by Tukey’s multiple-comparisons tests. P < 0.05 was considered statistically significant. 3. Results 3.1 Substance composition of RLF by HPLC-Q-TOF-MS/MS Total ion chromatography of RLF extracts obtained via HPLC-Q-TOF-MS/MS in both positive and negative ion modes is presented in Attached Figure S1. Based on mass spectrometry data compared with the MzCloud, mzVault, and ChemSpider databases as well as relevant literature, a total of 48 compounds were identified in the RLF extract 36, 37 . These include 10 flavonoids and their glycosides, 10 organic acids, 6 triterpenes, 5 monosaccharides, 4 phenolic acids, and 2 sphingolipids. The relative percentage content of the identified compounds was calculated using the area normalization method. Among these, 9 compounds had a relative percentage content greater than 0.5%, including 2 flavonoids, 4 saponins, and 3 other compounds. The compound with the highest relative percentage content was Compound 33 (Tiliroside), with a relative percentage of 6.6%. Detailed information on the names, molecular formulas, molecular weights, and fragment ions of the compounds is summarized in Attached Table S1. 3.2 Results of Network Pharmacology Study on RLF A total of 244 proteins related to RLF compound targets were identified, with detailed information provided in Attached Table S2. For NAFLD disease targets, 1,928 target proteins were screened, and the number of targets, along with their database sources, is illustrated in Fig. 1A. The RLF-related compound targets and NAFLD disease targets were imported into Venny 2.1 to create a Venn diagram, as shown in Fig. 1B. The overlap between RLF-related compound targets and NAFLD disease targets revealed 126 common targets. These targets were then imported into the STRING database for protein-protein interaction (PPI) network prediction 38 . The resulting network was analyzed and visualized using Cytoscape 3.2.1, with topology analysis performed using the "Network Analyzer" function. Nodes with larger sizes and darker colors indicate higher degrees of connectivity. The results, presented in Fig. 1C, show that the top six targets with the highest degree values were AKT, INS, TNF, IL6, TP53, and IL1B, with degree values of 99, 98, 96, 95, 92, and 92, respectively. Using a degree value cutoff of 38, 65 targets with degree values ≥ 38 were identified as key targets for the interaction between RLF and NAFLD (detailed degree values are listed in Attached Table S3). Furthermore, a "drug-component-target" network was constructed by mapping the 126 target proteins with RLF compounds, as shown in Fig. 1D. The results suggest that RLF extract has potential therapeutic effects on NAFLD, primarily acting on the targets AKT, INS, TNF, IL6, TP53, and IL1B. 3.3 Results of KEGG and GO Enrichment Analysis GO functional enrichment analysis can be utilized to describe the functions of gene targets across three aspects: Biological Process (BP), Cellular Component (CC), and Molecular Function (MF). In the GO enrichment analysis, a total of 1,340 terms were identified, with 1,219 terms related to BP, 35 terms related to CC, and 86 terms related to MF. The top 20 terms in BP, CC, and MF were selected and visualized using a bioinformatics online platform, as shown in Fig. 2A. The BP terms primarily involve processes such as monooxygenase activity, glial cell apoptotic process, inflammatory response, and response to UV-A. The CC terms mainly include transcription repressor complex, caveola, euchromatin, and plasma membrane raft. The MF terms predominantly relate to death receptor binding, transcription coactivator binding, tumor necrosis factor receptor binding, and tumor necrosis factor receptor superfamily binding 38 . KEGG pathway analysis can predict the roles of protein target interaction networks in various cellular activities and identify key protein targets along with their associated pathways. In the KEGG enrichment analysis, a total of 167 major pathways were identified, and the top 20 pathways were visualized using the bioinformatics online platform, as shown in Fig. 2B. The enriched pathways primarily include Pathways in Cancer, Lipid and Atherosclerosis, Human Cytomegalovirus Infection, Fluid Shear Stress and Atherosclerosis, AGE-RAGE Signaling Pathway in Diabetic Complications, Hepatitis C, Hepatitis B, TNF Signaling Pathway, IL-17 Signaling Pathway, Prostate Cancer, Kaposi Sarcoma-Associated Herpesvirus Infection, Epstein-Barr Virus Infection, Influenza A, Measles, Chagas Disease, Toxoplasmosis, PI3K-Akt Signaling Pathway, Proteoglycans in Cancer, FoxO Signaling Pathway, and Tuberculosis. The results indicate that the biomolecular processes involved in RLF treatment for NAFLD include monooxygenase activity, transcription repressor complex, and death receptor binding, while the relevant pathways include Lipid and Atherosclerosis and the PI3K-Akt signaling pathway. 3.4 Changes in NAFLD HepG2 cells model morphology after ORO staining ORO is a lipid-soluble azo dye renowned for its strong fat-staining capabilities. While it stains phospholipids and cholesterol weakly, it specifically colors neutral lipids such as triglycerides within cells, rendering them red or orange. HepG2 cells were cultured for 24 hours in both control and model groups and subsequently stained with ORO. Microscopic observations of these cells are presented in Figs. 4A and 4B. Figure 3A shows the control group cells, which are densely distributed in a rhomboid arrangement. In contrast, Fig. 3B depicts the model group cells, where no significant changes in cell morphology are observed; however, numerous lipid droplets in the intercellular matrix are stained red by ORO. Hematoxylin, a natural dye that becomes an acidic dye known as hematoxylin red upon oxidation, binds to the negatively charged deoxyribonucleic acid (DNA) in the cell nucleus, coloring it blue-purple. After ORO staining, the cells were subjected to a secondary staining with hematoxylin. Figures 3C and 3D illustrate that the nuclei of the cells were stained blue-purple by hematoxylin. The control group cells exhibit clear membrane boundaries and a clean intercellular matrix, whereas the model group cells show numerous lipid droplets distributed both within the cell membrane and in the intercellular matrix. The experimental results indicate that after 24 hours of OA treatment, HepG2 cells exhibit significant accumulation of lipid droplets within the cell membrane and intercellular matrix. This cell model effectively simulates the pathological lipid accumulation observed in hepatocytes in non-alcoholic fatty liver disease (NAFLD). 3.5 Effects of RLF Extract on Lipid Reduction in Oleic Acid-Induced HepG2 Cells in a NAFLD Model 3.5.1 MTT Assay Assessment of the Effects of Different Concentrations of RLF Extract on the NAFLD Cell Model Using the MTT Assay. A cell viability rate exceeding 80% was considered safe for use. As shown in Fig. 4, the cell viability decreased in a dose-dependent manner after 48 hours of treatment with different concentrations of RLF extract. At extract concentrations of 4 mg/mL and 4.5 mg/mL, the cell viability dropped to 81.9% and 74.6%, respectively. Therefore, a maximum concentration of 4 mg/mL RLF extract was selected for subsequent experiments. 3.5.2 ORO Staining Assay Figure 5 illustrates the effect of RLF extract on lipid reduction in the NAFLD cell model, as observed through ORO staining. In Fig. 5A, the control group cells exhibit intact cell membranes, with nuclei stained purple by hematoxylin and a clear intercellular matrix. Figure 5B shows the model group cells, where numerous red lipid droplets are distributed both inside and outside the cell membranes. In Fig. 5C, the positive drug group demonstrates complete clearance of lipid droplets from the intercellular matrix, although some residual droplets remain within the cell membranes. Figures 5D-F illustrate the effects of different concentrations of RLF extract. As the concentration increases from low to high, there is a notable decrease in the intracellular lipid droplet content. Additionally, in the high-concentration treatment group, some lipid droplets within the cell membranes are also partially cleared. 3.5.3 Evaluation of lipid-lowering activity of RLF extract TG and total T-CHO can be obtained from dietary sources as well as synthesized in the liver. These lipids serve as energy reserves stored in body and liver tissues, directly reflecting lipid levels in the body. Compared to the control group, the OA-induced NAFLD model exhibited significantly elevated levels of TG, T-CHO, LDL, ALT, and AST, as shown in Figs. 6A and 6B. Specifically, the TG and T-CHO contents in the model cells were 0.297 and 0.186 mmol/g protein, respectively, whereas in the RLF-H group, these values were reduced to 0.131 and 0.117 mmol/g protein, respectively. This indicates that RLF extract effectively reduces lipid levels in the model cells, with reductions of 55.9% in TG and 37.1% in T-CHO. LDL is the primary form of cholesterol transport in the body. Elevated levels of LDL can lead to metabolic diseases and increase the risk of cardiovascular disease. As depicted in Fig. 6C, the LDL content in the model cells was approximately 0.194 mmol/g protein, while in the RLF-H group, it decreased to 0.145 mmol/g protein, representing a 25.3% reduction compared to the model group. ALT and AST are crucial transaminases involved in amino acid metabolism. In cases of acute liver damage, ALT and AST are released from liver cells into the bloodstream, resulting in elevated levels. Figures 6D and 6E illustrate that the ALT and AST levels in the model cells were 9.43 and 18.04 U/g protein, respectively, whereas in the RLF-H group, these levels were reduced to 3.06 and 8.81 U/g protein, respectively, showing decreases of 67.5% and 51.1% compared to the model group. This indicates that RLF extract can regulate the elevation of ALT and AST caused by damage, thereby improving lipid levels, and mitigating oxidative or inflammatory damage induced by lipid accumulation in the cells. 3.6 Assessment of Antioxidant Activity of RLF Extract 3.6.1 Extracellular Antioxidant Activity The DPPH assay measures the reduction of free radicals, while the ABTS assay evaluates antioxidant capacity by reacting generated free radicals with antioxidants. These are two commonly used methods for assessing antioxidant activity. As shown in Fig. 7A, the RLF extract demonstrated significant DPPH free radical reduction, with its scavenging activity exhibiting a concentration-dependent effect. At a concentration of 5 mg/mL, the DPPH free radical reduction capability of the RLF extract was 98.86%, approaching that of Vitamin C (99.49%). As illustrated in Fig. 7B, the RLF extract also exhibited strong ABTS free radical scavenging ability, achieving 100% ABTS scavenging capacity at 5 mg/mL, which is equivalent to the positive control, Vitamin C (100%). These results indicate that the RLF extract possesses substantial free radical reduction and scavenging abilities, suggesting potential antioxidant activity. 3.6.2 Intracellular Antioxidant Activity Further investigation into the lipid-lowering mechanism of RLF extract was conducted. T-AOC represents the overall amount of antioxidant substances in the body and is used to assess overall antioxidant capacity. As shown in Fig. 8A, the antioxidant capacity of the model group cells was reduced, with an intracellular T-AOC activity of approximately 0.058 mmol/g. In contrast, the T-AOC activity in the RLF-H group cells was approximately 0.243 mmol/g, representing an increase of 182.5%. SOD is a crucial antioxidant enzyme that plays a key role in protecting cells from oxidative damage. As depicted in Fig. 8B, SOD activity in the model group cells decreased, increasing the likelihood of oxidative stress. The SOD activity in the model group cells was approximately 4.04 U/mg protein, whereas in the RLF-H group cells, it was approximately 9.57 U/mg protein, reflecting an increase of 136.8%. MDA is an oxidative product generated from lipid peroxidation and is commonly used as an indicator of oxidative damage. As illustrated in Fig. 8C, the NAFLD cell model exhibited elevated lipid levels, exacerbating oxidative damage. The MDA content in the model group cells was approximately 0.708 mmol/mg protein, while in the RLF-H group cells, it was approximately 0.373 mmol/mg protein, representing a decrease of 47.3% compared to the model group. These results indicate that RLF extract can modulate oxidative damage induced by elevated lipid levels. 3.7 RLF extracts promote the decrease of intracellular lipid levels by activating the PI3K-AKT signaling pathway. Based on network pharmacology and KEGG/GO pathway enrichment analysis, we hypothesize that RLF extract activates the AKT signaling pathway, with the PI3K-AKT pathway being involved in lipid metabolism in NAFLD hepatocytes. Through in vitro and in vivo antioxidant assays, we have determined that oxidative stress is involved in the onset and progression of NAFLD. To further investigate, we measured the protein expression levels of the PI3K-AKT signaling pathway in oleic acid-induced NAFLD hepatocyte lipid accumulation models. The results from WB analysis are shown in Fig. 9A. After normalizing the WB band intensity, as illustrated in Fig. 9B, the expression levels of AKT protein were consistent among the five experimental groups, indicating no significant inter-group differences in AKT protein content, which warrants further investigation into its phosphorylated form. Figure 9C D demonstrate that RLF extract significantly inhibited the overexpression of p-AKT and PI3K induced by oleic acid, with maximum inhibition rates reaching 63.6% and 70.28%, respectively. These experimental results suggest that RLF extract may exert its lipid-lowering effect through the PI3K-AKT signaling pathway, confirming the key pathway predicted by network pharmacology. 4. Discussion NAFLD is characterized by the accumulation of lipids in the liver, independent of alcohol intake. This liver disease is quite common and can progress pathologically from simple fatty liver to steatohepatitis, fibrosis, and potentially to cirrhosis and liver cancer. The pathogenesis of NAFLD involves a complex interplay of multiple mechanisms. In recent years, the 'multiple hit' hypothesis has gained significant recognition 39 . This hypothesis posits that the development of NAFLD is a multifaceted process. Initial fat accumulation, triggered by poor dietary habits and obesity as the 'first hit,' induces hepatic lesions. Subsequently, 'multiple parallel hits'—such as metabolic syndrome, drug toxicity, and insulin resistance—further damage the liver, leading to inflammation and oxidative stress that accelerate disease progression. Currently, treatment options for NAFLD are relatively limited, focusing primarily on controlling underlying conditions, improving metabolic status, and mitigating liver damage 40 . Treatment approaches include lifestyle modifications, pharmacotherapy, and surgical interventions. However, long-term pharmacotherapy can lead to drug resistance and adverse effects 41 , while surgical interventions carry intraoperative risks and potential postoperative complications. Natural medicines, known for their eco-friendliness, high safety profile, and lower risk of resistance, have become a prominent area of interest for developing treatments for NAFLD 42 . In recent years, RLF has garnered increasing attention due to its lipid-lowering activity. Studies have shown that RLF extracts reduce the expression of key molecules involved in the fatty acid synthesis pathway, enhancing fatty acid β-oxidation and consequently alleviating hepatic lipid buildup caused by a high-fat diet in animal models 43 . Furthermore, research has demonstrated that total flavonoids and low-molecular-weight polysaccharides derived from RLF can lower blood lipid levels and enhance high-density lipoprotein cholesterol (HDL) levels by modulating the antioxidant system 44 . In this study, HPLC-QTOF-MS/MS was employed to identify the primary components of RLF extracts. Based on comparisons with literature and databases, 48 compounds were identified, including 10 flavonoids and their glycosides, 10 organic acids, 6 terpenes, 5 monosaccharides, 4 phenolic acids, and 2 ceramide compounds. Using area normalization, the relative percentage content of each component identified by liquid chromatography-mass spectrometry was calculated. Nine compounds in the RLF extract had a relative percentage content greater than 0.5‰, including 2 flavonoids, 4 saponins, and 3 other compounds. We hypothesize that the lipid-lowering activity of RLF extracts may be attributed to the diverse range of flavonoid components, which aligns with findings reported in the literature. However, due to the complexity of lipid synthesis mechanisms, it remains challenging to pinpoint a specific primary factor or mechanism responsible for the lipid-lowering effects of RLF, necessitating further research in this area 45, 46 . The concept of 'network pharmacology' was first introduced in 2007 47 . It is an emerging discipline based on multidisciplinary concepts, including molecular biology, biochemistry, and bioinformatics. This field utilizes network-based information and systems biology techniques to study drug mechanisms, interactions, and targets 48 . By integrating extensive bioinformatics, cheminformatics, and pharmacological data, network pharmacology aims to understand drug mechanisms from a systems perspective, revealing interactions between drugs and multiple targets, thereby providing a theoretical foundation for the design of multi-target drugs 49 . In this study, network pharmacology was applied to predict the targets and pathways of Rosa laevigata Michx extract (RLFE) in the treatment of NAFLD. Database searches identified 244 RLFE-related targets and 1,928 NAFLD-related targets, with 126 targets overlapping between RLFE and NAFLD. These targets were imported into Cytoscape for protein-protein interaction (PPI) network analysis, which identified 65 key targets based on degree centrality. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted on the key targets. The GO enrichment analysis yielded a total of 1,340 entries, including 1,219 in biological processes (BP), 35 in cellular components (CC), and 86 in molecular functions (MF). Major processes included apoptosis, transcriptional repression, and autophagy receptor binding. The KEGG enrichment analysis identified 167 major pathways, including those related to cancer, lipid metabolism, atherosclerosis, and the PI3K-Akt signaling pathway. Multi-target drug therapies are becoming an important trend in this field. This study utilized OA to induce lipid accumulation in HepG2 human liver cancer cells, thereby establishing a cell model for NAFLD. The effect of OA on lipid accumulation in the NAFLD liver cell model was directly observed using ORO staining. The control group cells exhibited intact membranes, with nuclei stained purple by hematoxylin and clear interstitial areas. In contrast, the model group displayed numerous red lipid droplets distributed both inside and outside the cell membranes, confirming the successful construction of the NAFLD liver cell model. The impact of RLF extract on the cell model was then examined. It was found that as the concentration of the extract increased, lipid levels within the cells significantly decreased in the RLF-L, RLF-M, and RLF-H groups, providing preliminary evidence of the lipid-lowering activity of RLF extract. Subsequent experiments measured the effects of RLF extract on the NAFLD liver cell model using assay kits for TG, TC, LDL, ALT, and AST. The results indicated that in the RLF-H group, intracellular levels of TG, TC, and LDL were 0.131, 0.117, and 0.145 mmol/g protein, respectively, while ALT and AST levels were 3.06 and 8.81 U/g protein, respectively. Compared to the model group, intracellular lipid levels decreased by 55.9%, 37.1%, and 25.3%, respectively, while enzyme activity levels decreased by 67.5% and 51.1%. These results align with predictions from network pharmacology, demonstrating that RLF extract has significant lipid-lowering potential and can be used for the treatment of NAFLD. RLF extract notably reduces the levels of TG, TC, and LDL in diseased liver cells. Additionally, the inclusion of RLF extract lowered intracellular ALT and AST activity levels compared to the model group, indicating a modulation of liver cell damage induced by NAFLD and an improvement in cellular oxidative damage or inflammatory injury associated with elevated lipid levels. Research has demonstrated that RLF possesses remarkable antioxidant capabilities, with its high content of total flavonoids closely associated with its antioxidant activity, as confirmed by HPLC-Q-TOF-MS/MS analysis. The study also found that RLF total flavonoids significantly increased the concentrations of various antioxidant compounds, such as catalase (CAT), superoxide dismutase (SOD), glutathione (GSH), and glutathione peroxidase (GPX), in the liver of obese mice. Based on predictions from network pharmacology and KEGG and GO enrichment pathway analyses, it is hypothesized that RLF extract treats NAFLD through antioxidant pathways. To further investigate the antioxidant properties of RLF extract, subsequent experiments employed DPPH and ABTS assays to evaluate its free radical scavenging capacity, as well as T-AOC, SOD, and MDA assay kits to assess the antioxidant capability of the model cells after RLF extract treatment. The results showed that RLF extract exhibited strong free radical scavenging activity, with a concentration of 5 mg/mL achieving DPPH and ABTS scavenging effects comparable to those of vitamin C. Additionally, RLF extract increased the overall antioxidant capacity of HepG2 cells by 182.5%, enhanced intracellular SOD activity by 136.8%, and decreased the production of the lipid peroxidation product MDA by 47.3%, thus safeguarding the cells against oxidative damage. Serine/threonine kinase (AKT) has garnered significant attention in the medical field due to its essential role in regulating various cellular functions, including metabolism, growth, proliferation, survival, transcription, and protein synthesis 50 . Signals that activate or inhibit AKT can originate from receptor tyrosine kinases, integrins, B-cell and T-cell receptors, cytokine receptors, G protein-coupled receptors, and various stimuli that trigger the production of phosphatidylinositol (3,4,5)-trisphosphate (PIP3) via phosphatidylinositol 3-kinase (PI3K) 51 . The biomarker of the PI3K-AKT signaling pathway is reflected through the dynamic regulation of total PI3K and AKT proteins, as well as their phosphorylated forms 52 . The regulatory function of this pathway is linked to a variety of human diseases, including cancer, diabetes, lipid metabolism disorders, cardiovascular diseases, and neurological conditions. The PI3K-AKT signaling pathway was identified in the pathway enrichment predictions derived from network pharmacology. Consequently, this study employed Western blot analysis to evaluate the expression levels of PI3K, AKT, and phosphorylated AKT (p-AKT) proteins in NAFLD model cells treated with RLF. The experimental results indicated that RLF extract downregulated PI3K expression, activated the PI3K-AKT signaling pathway, and decreased the expression of p-AKT, effectively blocking the phosphorylation of the AKT protein. Specifically, the relative expression levels of PI3K and p-AKT in the cells were reduced by 63.6% and 70.28%, respectively. These findings suggest that consistent with predictions from network pharmacology and pathway enrichment analysis, RLF extract may modulate lipid metabolism by downregulating PI3K protein expression and inhibiting AKT phosphorylation, thereby affecting nuclear factor E2 (NF-E2) and regulating the downstream protein Nrf2 53 . This action contributes to the suppression of oxidative stress responses. These findings offer a fresh perspective on the application of RLF as both a medicinal and dietary plant for the treatment of NAFLD. Declarations conflict of interest The authors declare no conflict of interest. Acknowledgements Acknowledgements This work was supported by National Natural Science Foundation of China (81703377), Young Top Talents in “Xing Liao Talent Program” (XLYC2007168) of Liaoning province of P. R. China, Foundation (LJKMZ20220786) from the Project of Education Department of Liaoning Province of P. R. China, Young and Middle-aged Scientific and Technological Innovation Talents in Shenyang (RC210148) of Liaoning province of P. R. China, Foundation (No. 2023JH2/101600021) from the Project of Science and Technology Department of Liaoning province of P. R. 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Chen, Polygonum cuspidatum Extract Exerts Antihyperlipidemic Effects by Regulation of PI3K/AKT/FOXO3 Signaling Pathway, Oxid Med Cell Longev , 2021, 2021 , 3830671. Additional Declarations No competing interests reported. Supplementary Files Supplementarydata.docx Highlights.docx Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6926759","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":492734448,"identity":"74f95024-d89e-4f72-9e45-bed25583fba8","order_by":0,"name":"Pengbo NI","email":"","orcid":"","institution":"Shenyang University of Chemical Technology","correspondingAuthor":false,"prefix":"","firstName":"Pengbo","middleName":"","lastName":"NI","suffix":""},{"id":492734450,"identity":"eeb413f7-bf20-47d3-9cdc-25bc603e0f6d","order_by":1,"name":"Yaoyao WANG","email":"","orcid":"","institution":"Shenyang University of Chemical Technology","correspondingAuthor":false,"prefix":"","firstName":"Yaoyao","middleName":"","lastName":"WANG","suffix":""},{"id":492734452,"identity":"5b4caf74-e6be-4066-9985-c7b19d3af917","order_by":2,"name":"Pinyi GAO","email":"","orcid":"","institution":"Shenyang University of Chemical Technology","correspondingAuthor":false,"prefix":"","firstName":"Pinyi","middleName":"","lastName":"GAO","suffix":""},{"id":492734454,"identity":"77587514-577d-4ad3-ac86-93dd31737a9d","order_by":3,"name":"Danqi LI","email":"","orcid":"","institution":"Shenyang University of Chemical Technology","correspondingAuthor":false,"prefix":"","firstName":"Danqi","middleName":"","lastName":"LI","suffix":""},{"id":492734456,"identity":"9cc9fa9e-ed0e-4e40-b5ba-7a8012153ae0","order_by":4,"name":"Xuegui LIU","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYBACPmYog429ASaWgF8LG1wLzwEQZUCEFjhLIoFYLew8ZtI8FbWJfZLPn0nz1Pxh4GfPMWD4uQOfw3iMjXnOHE9sk84B6j1mwCDZ88aAsfcMXi2Gj3nbjoG0sEnzNhgwGNzIMWBmbMOrxeAw7z+gFsnjz8Ba7InQArSloSaxTYLBDGKLBEEtbMWGc44dMG7jyTG2nHPMmEfizLOCg714tPDzH94m8aamTnZ++/GHN97UyMnxtydvfPATjxYoOAwiWCSABA+IdYCgBgaGOhDB/IEIlaNgFIyCUTACAQB3HkM2MKfrmQAAAABJRU5ErkJggg==","orcid":"","institution":"Shenyang University of Chemical Technology","correspondingAuthor":true,"prefix":"","firstName":"Xuegui","middleName":"","lastName":"LIU","suffix":""}],"badges":[],"createdAt":"2025-06-19 02:38:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6926759/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6926759/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88135146,"identity":"67a352a3-6b5d-4764-8b07-d62b297e5f8e","added_by":"auto","created_at":"2025-08-01 21:36:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2657150,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Search results of NAFLD disease targets;(B) Venn diagram of RLF-related compound targets and NAFLD disease targets;(C) PPI network of 126 target proteins mapped by RLF and NAFLD;(D) \"Drug - ingredient - target\" PPI network.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6926759/v1/3b085677b573d38398ee6930.png"},{"id":88135145,"identity":"99f388d4-a2d5-4231-82eb-17236e99b22b","added_by":"auto","created_at":"2025-08-01 21:36:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":568572,"visible":true,"origin":"","legend":"\u003cp\u003e(A) GO functional enrichment analysis;(B) Enrichment analysis of KEGG pathway.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6926759/v1/531c041b1b391075cc44b264.png"},{"id":88135148,"identity":"d8620440-db87-43c7-a0ba-98c02dddb457","added_by":"auto","created_at":"2025-08-01 21:36:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2309121,"visible":true,"origin":"","legend":"\u003cp\u003eMorphology of HepG2 cells under different conditions. Control group (A, C); OA=0.15 mmol/L (B, D).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6926759/v1/5390047c7746c5c02359b92a.png"},{"id":88135152,"identity":"0d5478c4-6bdf-4070-bcca-29d80ac6227c","added_by":"auto","created_at":"2025-08-01 21:36:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":87799,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of RLF Extract on HepG2 Cells. *P＜0.01 vs the control group.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6926759/v1/445a29662a1ff9b3d4851186.png"},{"id":88135151,"identity":"83d98207-423b-4f53-b120-99d834d2208c","added_by":"auto","created_at":"2025-08-01 21:36:50","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":3407351,"visible":true,"origin":"","legend":"\u003cp\u003eMorphology of HepG2 cells under different conditions. Control group (A); OA group = 150 μM (B); AT group = 100 μM (C); RLF-L group = 1 mg/mL (D); RLF-M group = 2 mg/mL (E); RLF-H group = 4 mg/mL (F).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6926759/v1/0f7a9da0013347c08a725c8f.png"},{"id":88135164,"identity":"015d5d97-a8df-4663-8c2e-f842ebab3879","added_by":"auto","created_at":"2025-08-01 21:36:50","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":217419,"visible":true,"origin":"","legend":"\u003cp\u003eLipid-lowering effect of RLF extract on HepG2 cells; (A) Triglyceride content in HepG2 cells; (B)Total cholesterol content in HepG2 cells; (C) Low density lipoprotein cholesterol content in HepG2 cells; (D) Glutamic pyruvic transaminase activity in HepG2 cells; (E) Glutamic oxalacetic transaminase activity in HepG2 cells. *P\u0026lt;0.01 vs the M group.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6926759/v1/40f88e0b3f6015acdfdaa9cf.png"},{"id":88135900,"identity":"fd6a7b68-f55b-4632-bcff-3e0a8c68f612","added_by":"auto","created_at":"2025-08-01 21:52:50","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":96991,"visible":true,"origin":"","legend":"\u003cp\u003eScavenging of DPPH and ABTS free radicals by RLF extract; (A) DPPH free radical scavenging test; (B) ABTS free radical scavenging test.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6926759/v1/b89652a66f2d0abca3cc047b.png"},{"id":88135193,"identity":"8b86dc78-9d71-4bd7-a233-f651a78be215","added_by":"auto","created_at":"2025-08-01 21:36:51","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":130036,"visible":true,"origin":"","legend":"\u003cp\u003eAntioxidant effect of RLF extract on HepG2 cells; (A) Total antioxidant capacity of HepG2 cells; (B) Superoxide dismutase activity in HepG2 cells; (C) Malondialdehyde content in HepG2 cells. *P\u0026lt;0.01vs the M group.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-6926759/v1/5fc08eefd0d31231f93398f3.png"},{"id":88135749,"identity":"8233ec10-b126-4d2e-804d-67c9f6c4a8f4","added_by":"auto","created_at":"2025-08-01 21:44:50","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":300095,"visible":true,"origin":"","legend":"\u003cp\u003eRLF extracts activate the PI3K-AKT signaling pathway in HepG2 cells; (A) Western blot analysis results; (B) Ratio of AKT/β-actin protein level; (C) Ratio of p-AKT/AKT protein level; (D) Ratio of PI3K/β-actin protein level. *P\u0026lt;0.01vs the M group.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-6926759/v1/87d73918bc4351560dd3192e.png"},{"id":109405084,"identity":"6f1c45a8-f0cc-4a29-b29e-494d90b041c0","added_by":"auto","created_at":"2026-05-17 12:54:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":12543170,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6926759/v1/76cfd921-3859-4158-9846-2fb19ff56d45.pdf"},{"id":88136315,"identity":"39be6845-e8e0-4277-a061-c66c91cf43de","added_by":"auto","created_at":"2025-08-01 22:08:50","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":241495,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarydata.docx","url":"https://assets-eu.researchsquare.com/files/rs-6926759/v1/c3596625fd6da64189355b34.docx"},{"id":88135740,"identity":"ba06bc6c-6acc-4578-874c-57a94e635f2f","added_by":"auto","created_at":"2025-08-01 21:44:50","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":10594,"visible":true,"origin":"","legend":"","description":"","filename":"Highlights.docx","url":"https://assets-eu.researchsquare.com/files/rs-6926759/v1/eb3669e6eef8926f25b03377.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Inhibition of Lipid Accumulation in NAFLD Liver by Extract of Rosa laevigata Fruit Extract through Activation of the PI3K-AKT Signaling Pathway","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eNAFLD is a metabolic disorder of the liver characterized by the excessive accumulation of fat in liver tissue, which is not linked to alcohol consumption\u003csup\u003e1\u003c/sup\u003e. Typically, NAFLD is diagnosed when fat constitutes more than 5\u0026ndash;10% of liver weight. There are two forms of NAFLD: simple fatty liver and non-alcoholic steatohepatitis (NASH)\u003csup\u003e2\u003c/sup\u003e. Simple fatty liver generally does not pose serious health risks, whereas NASH can lead to liver inflammation and fibrosis, potentially progressing to severe conditions such as cirrhosis and liver cancer\u003csup\u003e3\u003c/sup\u003e. NAFLD is often associated with metabolic disorders such as obesity, diabetes, and hypertension, as well as lifestyle factors like poor diet and insufficient physical activity. The prevalence of NAFLD varies across regions and populations but generally shows an increasing trend. Based on global studies and surveys, NAFLD has emerged as a prevalent chronic liver condition worldwide. In some countries, particularly developed nations, the prevalence of NAFLD exceeds that of traditional alcohol-related liver disease. As obesity, diabetes, and metabolic syndrome become more common, the incidence of NAFLD is on the rise. It is estimated that approximately 25\u0026ndash;30% of adults worldwide are affected by NAFLD. In certain groups, such as individuals with hyperlipidemia, patients with type 2 diabetes, and those with metabolic syndrome, the likelihood of having the disease may reach up to 50%.In summary, NAFLD has emerged as a significant public health issue globally, underscoring the need for effective prevention and management strategies.\u003c/p\u003e\u003cp\u003eAn increasing number of clinicians and researchers worldwide have embraced traditional Chinese medicine due to its minimal side effects and consistent therapeutic benefits\u003csup\u003e4, 5\u003c/sup\u003e. RLF is the dried fruit of \u003cem\u003eRosa laevigata\u003c/em\u003e Michx, a species within the Rosaceae family. Widely distributed in southern China, the fruits contain various active compounds, including flavonoids, lignins, polyphenols, steroids, triterpenoids, polysaccharides, and other bioactive substances\u003csup\u003e6\u003c/sup\u003e. In the realm of Traditional Chinese Medicine (TCM), RLF is recorded in the \"Shu Ben Cao,\" authored by Han Baosheng between 935 and 960 ADS, and has since been integrated into the \"Chinese Pharmacopoeia.\" This herb is recognized for its association with the bladder, kidney, and large intestine meridians and is known for its effects in reducing urination frequency, consolidating kidney essence, and controlling bowel movements to treat conditions such as steatorrhea, frequent urination, bleeding, and diarrhea\u003csup\u003e7\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eRecent studies have shown that RLF possesses multiple pharmacological activities, including antioxidant, anti-inflammatory, antimicrobial, and lipid-lowering effects\u003csup\u003e8\u003c/sup\u003e. It also plays a significant role in immune regulation, providing benefits for liver and kidney protection as well as lipid reduction. Research conducted by Liu et al. demonstrated that the flavonoids in RLF exhibit scavenging properties against free radicals, such as 2,2-diphenyl-1-picrylhydrazyl (DPPH)\u003csup\u003e9\u003c/sup\u003e, hydroxyl radicals, and superoxide anions, showcasing significant reducing capabilities\u003csup\u003e10\u003c/sup\u003e. Oral administration of RLF extract at doses of 25 and 50 mg/kg/day for four weeks in mice fed a high-fat diet resulted in a notable increase in various antioxidant levels in the liver, including catalase (CAT), SOD, GSH, and glutathione peroxidase (GPX)\u003csup\u003e11\u003c/sup\u003e. Furthermore, total flavonoids from RLF dose-dependently reduced the concentration of hepatic MDA. Traditional Chinese Medicine is characterized by its \u0026ldquo;multicomponent, multitarget, and multipath way\u0026rdquo; effects, which collectively regulate biological networks in the body to achieve a synergistic therapeutic function. Understanding the mechanisms of traditional Chinese medicine through conventional experiments can be challenging; therefore, a systematic analysis of these mechanisms is essential\u003csup\u003e12, 13\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eNetwork pharmacology is a novel and comprehensive research approach that utilizes techniques such as bioinformatics, systems biology, and computational chemistry to explore the interactions between traditional Chinese medicine and the molecular, cellular, and tissue components within organisms\u003csup\u003e14\u003c/sup\u003e. By integrating vast amounts of bioinformatics, cheminformatics, and pharmacological data, it aims to understand drug mechanisms at a systemic level and uncover interactions between drugs and multiple targets\u003csup\u003e15, 16\u003c/sup\u003e. This approach provides a theoretical basis for the design of multi-target drugs\u003csup\u003e17\u003c/sup\u003e. In traditional Chinese medicine, most single herbs and formulas exhibit both multicomponent and multitarget properties. However, elucidating the scientific foundations of traditional Chinese medicine from molecular and systemic perspectives remains a significant challenge. Thus, this field lends itself well to integration with network pharmacology.\u003c/p\u003e\u003cp\u003eThis study employed HPLC-QTOF-MS/MS technology to analyze the chemical composition of RLF\u003csup\u003e18\u003c/sup\u003e. Using network pharmacology approaches, it predicted the mechanism of action of RLF in combating NAFLD, identifying a total of 48 compounds, 126 protein targets, and 20 signaling pathways. Additionally, the study constructed both a compound-target network and a pathway-target network\u003csup\u003e19\u003c/sup\u003e. Gene Ontology (GO) analysis and KEGG enrichment analysis were conducted to gather biological insights. Furthermore, the outcomes of the network analysis were corroborated through in vitro biological experiments\u003csup\u003e20\u003c/sup\u003e. Overall, this study provides scientific evidence to support the use of RLF in the treatment of NAFLD and demonstrates the effectiveness of modern technology in exploring the value of traditional Chinese medicine\u003csup\u003e21\u003c/sup\u003e.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Chemicals reagents and materials\u003c/h2\u003e\u003cp\u003e\u003cem\u003eRosa laevigata\u003c/em\u003e fruits were harvested from Bo Zhou, Anhui. Phosphate-buffered solution (PBS) was purchased from Boster Biological Technology Co., Ltd. (Wuhan, China). The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium bromide (MTT) was obtained from Beijing Solarbio Science \u0026amp; Technology Co., Ltd. (Beijing, China). Fetal bovine serum (FBS) was sourced from Clark Bioscience (Richmond, VA, USA). Dimethyl sulfoxide (DMSO), Dulbecco\u0026rsquo;s Modified Eagle\u0026rsquo;s Medium (high glucose) (DMEM), trypsin, penicillin (10 kU/mL), and streptomycin (10 mg/mL) were purchased from Thermo Fisher Scientific Co., Ltd. (Beijing, China). Oleic acid (OA), 2,2-Diphenyl-1-picrylhydrazyl (DPPH), and 2,2'-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) were obtained from Shanghai Macklin Biochemical Co., Ltd. (Shanghai, China). Kits for detecting total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) were purchased from Jiancheng Technology Co., Ltd. (Nanjing, China). The Bicinchoninic Acid (BCA) protein assay kit, superoxide dismutase (SOD) assay kit, malondialdehyde (MDA) assay kit, total antioxidant capacity (T-AOC) assay kit, and Oil Red O staining kit (ORO) were sourced from Beyotime Biotechnology Co., Ltd. (Shanghai, China). The secondary antibody was obtained from Beijing Bioss Biotechnology Co., Ltd. (Beijing, China). All other analytical-grade reagents were purchased locally.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Sample Preparation\u003c/h2\u003e\u003cp\u003e\u003cem\u003eRosa laevigata\u003c/em\u003e fruit samples were cut into fragments and subjected to ethanol extraction at a sample-to-ethanol ratio of 1:10 (g/mL) at 60\u0026deg;C for 3 hours. The extract was then filtered and concentrated to a thick paste using a rotary evaporator at 60\u0026deg;C under vacuum. This thick paste was dried in a controlled oven until the weight remained constant, yielding ethanol extracts from RLF, which were then stored at \u0026minus;\u0026thinsp;20\u0026deg;C\u003csup\u003e22\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 RLF by HPLC-Q-TOF-MS/MS\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the gradient elution procedure for chromatographic analysis. Solvent A consists of 0.1% formic acid, while solvent B is acetonitrile. The temperature of the chromatographic column (Sepax GP-C18 Column) was set to 40\u0026deg;C, with a flow rate of 0.3 mL/min. In positive ion mode, the spray voltage and nebulizer temperature were set to 5500 V and 500\u0026deg;C, respectively. In negative ion mode, these settings were adjusted to 4400 V and 450\u0026deg;C, respectively. The scanning range for the first-order mass spectrum was m/z 100\u0026ndash;1200, while the second-order mass spectrum scanned from m/z 50-1000. The collision-induced dissociation (CID) voltage was set to \u0026plusmn;\u0026thinsp;60 V, with a collision energy of 35\u0026thinsp;\u0026plusmn;\u0026thinsp;15 eV\u003csup\u003e23, 24\u003c/sup\u003e.\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\u003eChromatographic gradient elution procedure.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTime(min)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eB(%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\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=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e70\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=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e100\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=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e100\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=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\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=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 RLF-NAFLD Network Pharmacology Analysis\u003c/h2\u003e\u003cp\u003eUsing UPLC-Q-TOF-MS/MS analysis to identify the chemical composition of RLF, we gathered compound targets from several databases, including TCMSP, HERB, PubChem, STITCH, Swiss Target Prediction, Similarity Ensemble Approach (SEA), and TargetNet\u003csup\u003e25\u003c/sup\u003e. We retrieved keywords such as \"NAFLD,\" \"nonalcoholic fatty liver,\" and \"fatty liver\" from OMIM, PharmGKB, GeneCards, DrugBank, and the Therapeutic Target Database (TTD) to identify relevant disease targets\u003csup\u003e26, 27\u003c/sup\u003e. The direct disease targets were inputted into the String database to broaden the disease network, with a minimum required interaction score set at 0.900 for the highest confidence level. The resulting extended disease targets, along with the direct disease targets, were then utilized as wound-related disease targets\u003csup\u003e28\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSubsequently, the results from the aforementioned databases were compiled, deduplicated, and standardized in UniProt to derive the RLF-related compound targets and NAFLD disease targets. Common targets between the compounds and the disease were identified using the OmicShare tool. These shared targets were then analyzed through a protein-protein interaction (PPI) network using the String database\u003csup\u003e29\u003c/sup\u003e, with the species set to \"Homo sapiens\" and a confidence threshold of over 0.900. All networks were visualized using Cytoscape 3.6.0 software (Bethesda, MD, USA). The network construction proceeded as follows: (1) the PPI network for common targets and (2) the RLF-Compound-Target network\u003csup\u003e30\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 KEGG and GO Enrichment Analysis\u003c/h2\u003e\u003cp\u003eGO and KEGG are widely used methods for identifying common functions among genes based on biological ontologies\u003csup\u003e31\u003c/sup\u003e. NAFLD-related disease targets were submitted to the Metascape online platform to perform KEGG and GO enrichment analyses. The option 'H sapiens' (human) was selected for custom analysis under the 'Input/Analysis as Species' section. Under the 'Functional Set,' 'Pathway,' and 'Structural Complex' options, KEGG and GO analyses were chosen for their respective evaluations. The results of the GO functional and KEGG pathway enrichment analyses were then exported as a ZIP file for visualization and graphical analysis using an online bioinformatics platform\u003csup\u003e32\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Establishment NAFLD cells model with HepG2 cells\u003c/h2\u003e\u003cp\u003eHuman HepG2 liver cancer cells were purchased from the Chinese Academy of Sciences (Beijing) Cell Bank (Beijing, China). HepG2 cells were plated in 6-well plates at a density of 10,000 to 30,000 cells per well in high-glucose DMEM containing 10% FBS and then incubated at 37\u0026deg;C with 5% CO2 for 24 hours. The supernatant of the control group was replaced with 2 mL of culture medium, while the model group was treated with 2 mL of culture medium containing 0.15 mmol/L oleic acid (OA) and incubated for an additional 24 hours. The model group was then stained with Oil Red O (ORO) and compared with the control group to determine whether the model was successfully established\u003csup\u003e33\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.7 MTT assay\u003c/h2\u003e\u003cp\u003eCell viability was determined by an MTT assay with some modifications to assess the safety of RLF. Human HepG2 liver cancer cells were seeded at a density of 5 \u0026times; 10\u0026sup3; cells/well in 96-well microculture plates and grown at 37\u0026deg;C with 5% CO2 overnight. The supernatant was then removed. After incubation, the medium was replaced with 100 \u0026micro;L of 1 mg/mL MTT reagent and incubated for another 4 hours at 37\u0026deg;C with 5% CO2. The MTT reagent was removed, and 150 \u0026micro;L of DMSO was added to each well. The plates were shaken for 15 minutes on a table oscillator and analyzed using a microplate reader at 490 nm. Each sample was analyzed three times, and the values were averaged\u003csup\u003e34\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.8 Measurement of intracellular lipid-lowering levels of RLF\u003c/h2\u003e\u003cp\u003eHepG2 cells were incubated at a density of 2 \u0026times; 10⁵ cells/mL in 6-well plates. Two milliliters of culture medium were added to the control group; 2 mL of oleic acid (OA) at 0.15 mmol/L was added to the model group; 2 mL of atorvastatin at 0.15 mmol/L was added to the positive group; 1 mL of RLF at 2 mg/mL and 1 mL of OA at 0.3 mmol/L were added to the RLF-L group; 1 mL of RLF at 4 mg/mL and 1 mL of OA at 0.3 mmol/L were added to the RLF-M group; and 1 mL of RLF at 8 mg/mL and 1 mL of OA at 0.3 mmol/L were added to the RLF-H group. After 24 hours of culture, PBS was used to wash the excess culture medium three times. IP cell lysis buffer was then added, and the cells were lysed in an ice bath for 30 minutes. The levels of TG, T-CHO, LDL-C, ALT, and AST were measured following the instructions provided by the manufacturers of the detection kits. The protein concentration in each well was measured using a BCA protein assay kit to standardize the data\u003csup\u003e35\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e2.9 Measurement of vitro Antioxidant levels of RLF\u003c/h2\u003e\u003cp\u003eDPPH and ABTS radicals were used to investigate the in vitro antioxidant capacity. DPPH and ABTS were dissolved in ethanol to prepare stock solutions. For the DPPH radical scavenging assay, the control group received a mixture of DPPH solution and 50% ethanol. The sample group received a mixture of DPPH solution with sample solutions at concentrations of 0.005, 0.02, 0.08, 0.3, 0.8, 2, and 5 mg/mL. The sample background group received a mixture of DPPH solution with sample solutions at the same concentrations, along with anhydrous ethanol. Reactions for the DPPH radical scavenging assay were conducted in the dark for 30 minutes, after which the absorbance was measured at 517 nm, and the radical scavenging activity was calculated according to Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). For the ABTS radical scavenging assay, reactions were conducted in the dark for 10 minutes, with absorbance measured at 734 nm, and the radical scavenging activity calculated according to Eq.\u0026nbsp;(2):\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003e2.10 Measurement of vivo Antioxidant levels of RLF\u003c/h2\u003e\n \u003cp\u003eHepG2 cells were incubated at a density of 2 × 10⁵ cells/mL in 6-well plates. Two milliliters of culture medium were added to the control group; 2 mL of oleic acid (OA) at 0.15 mmol/L was added to the model group; 1 mL of RLF at 2 mg/mL and 1 mL of OA at 0.3 mmol/L were added to the RLF-L group; 1 mL of RLF at 4 mg/mL and 1 mL of OA at 0.3 mmol/L were added to the RLF-M group; and 1 mL of RLF at 8 mg/mL and 1 mL of OA at 0.3 mmol/L were added to the RLF-H group. After 24 hours of culture, PBS was used to wash the excess culture medium three times. IP cell lysis buffer was then added, and the cells were lysed in an ice bath for 30 minutes. The levels of T-AOC, SOD, and MDA were measured according to the instructions provided by the manufacturers of the detection kits. The protein concentration in each well was measured using a BCA protein assay kit to standardize the data.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \u003ch2\u003e2.11 Western Blotting\u003c/h2\u003e\n \u003cp\u003eIP cell lysis buffer was used to lyse cells from the Control, RLF-L, RLF-M, and RLF-H groups. The protein concentration was measured using a BCA protein assay kit. The protein samples were then stored at -80°C until further analysis. Western blotting was performed to determine the expression levels of AKT, phosphorylated AKT (p-AKT), and β-actin in each group.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003e2.12 Statistical analysis\u003c/h2\u003e\n \u003cp\u003eEach experiment was performed in triplicate for each group. The data were presented as mean ± standard deviation (SD) values and statistically analyzed with one-way analysis of variance, followed by Tukey’s multiple-comparisons tests. P \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003ch2\u003e3.1 Substance composition of RLF by HPLC-Q-TOF-MS/MS\u003c/h2\u003e\n\u003cp\u003eTotal ion chromatography of RLF extracts obtained via HPLC-Q-TOF-MS/MS in both positive and negative ion modes is presented in Attached Figure S1. Based on mass spectrometry data compared with the MzCloud, mzVault, and ChemSpider databases as well as relevant literature, a total of 48 compounds were identified in the RLF extract\u003csup\u003e36, 37\u003c/sup\u003e. These include 10 flavonoids and their glycosides, 10 organic acids, 6 triterpenes, 5 monosaccharides, 4 phenolic acids, and 2 sphingolipids. The relative percentage content of the identified compounds was calculated using the area normalization method. Among these, 9 compounds had a relative percentage content greater than 0.5%, including 2 flavonoids, 4 saponins, and 3 other compounds. The compound with the highest relative percentage content was Compound 33 (Tiliroside), with a relative percentage of 6.6%. Detailed information on the names, molecular formulas, molecular weights, and fragment ions of the compounds is summarized in Attached Table S1.\u003c/p\u003e\n\u003ch2\u003e3.2 Results of Network Pharmacology Study on RLF\u003c/h2\u003e\n\u003cp\u003eA total of 244 proteins related to RLF compound targets were identified, with detailed information provided in Attached Table S2. For NAFLD disease targets, 1,928 target proteins were screened, and the number of targets, along with their database sources, is illustrated in Fig. 1A. The RLF-related compound targets and NAFLD disease targets were imported into Venny 2.1 to create a Venn diagram, as shown in Fig. 1B. The overlap between RLF-related compound targets and NAFLD disease targets revealed 126 common targets. These targets were then imported into the STRING database for protein-protein interaction (PPI) network prediction\u003csup\u003e38\u003c/sup\u003e. The resulting network was analyzed and visualized using Cytoscape 3.2.1, with topology analysis performed using the \"Network Analyzer\" function. Nodes with larger sizes and darker colors indicate higher degrees of connectivity. The results, presented in Fig. 1C, show that the top six targets with the highest degree values were AKT, INS, TNF, IL6, TP53, and IL1B, with degree values of 99, 98, 96, 95, 92, and 92, respectively. Using a degree value cutoff of 38, 65 targets with degree values ≥ 38 were identified as key targets for the interaction between RLF and NAFLD (detailed degree values are listed in Attached Table S3). Furthermore, a \"drug-component-target\" network was constructed by mapping the 126 target proteins with RLF compounds, as shown in Fig. 1D. The results suggest that RLF extract has potential therapeutic effects on NAFLD, primarily acting on the targets AKT, INS, TNF, IL6, TP53, and IL1B.\u003c/p\u003e\n\u003ch2\u003e3.3 Results of KEGG and GO Enrichment Analysis\u003c/h2\u003e\n\u003cp\u003eGO functional enrichment analysis can be utilized to describe the functions of gene targets across three aspects: Biological Process (BP), Cellular Component (CC), and Molecular Function (MF). In the GO enrichment analysis, a total of 1,340 terms were identified, with 1,219 terms related to BP, 35 terms related to CC, and 86 terms related to MF. The top 20 terms in BP, CC, and MF were selected and visualized using a bioinformatics online platform, as shown in Fig. 2A. The BP terms primarily involve processes such as monooxygenase activity, glial cell apoptotic process, inflammatory response, and response to UV-A. The CC terms mainly include transcription repressor complex, caveola, euchromatin, and plasma membrane raft. The MF terms predominantly relate to death receptor binding, transcription coactivator binding, tumor necrosis factor receptor binding, and tumor necrosis factor receptor superfamily binding\u003csup\u003e38\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eKEGG pathway analysis can predict the roles of protein target interaction networks in various cellular activities and identify key protein targets along with their associated pathways. In the KEGG enrichment analysis, a total of 167 major pathways were identified, and the top 20 pathways were visualized using the bioinformatics online platform, as shown in Fig. 2B. The enriched pathways primarily include Pathways in Cancer, Lipid and Atherosclerosis, Human Cytomegalovirus Infection, Fluid Shear Stress and Atherosclerosis, AGE-RAGE Signaling Pathway in Diabetic Complications, Hepatitis C, Hepatitis B, TNF Signaling Pathway, IL-17 Signaling Pathway, Prostate Cancer, Kaposi Sarcoma-Associated Herpesvirus Infection, Epstein-Barr Virus Infection, Influenza A, Measles, Chagas Disease, Toxoplasmosis, PI3K-Akt Signaling Pathway, Proteoglycans in Cancer, FoxO Signaling Pathway, and Tuberculosis. The results indicate that the biomolecular processes involved in RLF treatment for NAFLD include monooxygenase activity, transcription repressor complex, and death receptor binding, while the relevant pathways include Lipid and Atherosclerosis and the PI3K-Akt signaling pathway.\u003c/p\u003e\n\u003ch2\u003e3.4 \u003cem\u003eChanges in NAFLD HepG2 cells model morphology after ORO staining\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eORO is a lipid-soluble azo dye renowned for its strong fat-staining capabilities. While it stains phospholipids and cholesterol weakly, it specifically colors neutral lipids such as triglycerides within cells, rendering them red or orange. HepG2 cells were cultured for 24 hours in both control and model groups and subsequently stained with ORO. Microscopic observations of these cells are presented in Figs. 4A and 4B. Figure 3A shows the control group cells, which are densely distributed in a rhomboid arrangement. In contrast, Fig. 3B depicts the model group cells, where no significant changes in cell morphology are observed; however, numerous lipid droplets in the intercellular matrix are stained red by ORO. Hematoxylin, a natural dye that becomes an acidic dye known as hematoxylin red upon oxidation, binds to the negatively charged deoxyribonucleic acid (DNA) in the cell nucleus, coloring it blue-purple. After ORO staining, the cells were subjected to a secondary staining with hematoxylin. Figures 3C and 3D illustrate that the nuclei of the cells were stained blue-purple by hematoxylin. The control group cells exhibit clear membrane boundaries and a clean intercellular matrix, whereas the model group cells show numerous lipid droplets distributed both within the cell membrane and in the intercellular matrix. The experimental results indicate that after 24 hours of OA treatment, HepG2 cells exhibit significant accumulation of lipid droplets within the cell membrane and intercellular matrix. This cell model effectively simulates the pathological lipid accumulation observed in hepatocytes in non-alcoholic fatty liver disease (NAFLD).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.5 Effects of RLF Extract on Lipid Reduction in Oleic Acid-Induced HepG2 Cells in a NAFLD Model\u003c/em\u003e\u003c/p\u003e\n\u003ch2\u003e3.5.1 MTT Assay\u003c/h2\u003e\n\u003cp\u003eAssessment of the Effects of Different Concentrations of RLF Extract on the NAFLD Cell Model Using the MTT Assay. A cell viability rate exceeding 80% was considered safe for use. As shown in Fig. 4, the cell viability decreased in a dose-dependent manner after 48 hours of treatment with different concentrations of RLF extract. At extract concentrations of 4 mg/mL and 4.5 mg/mL, the cell viability dropped to 81.9% and 74.6%, respectively. Therefore, a maximum concentration of 4 mg/mL RLF extract was selected for subsequent experiments.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003e3.5.2\u003c/em\u003e ORO \u003cem\u003eStaining Assay\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eFigure 5 illustrates the effect of RLF extract on lipid reduction in the NAFLD cell model, as observed through ORO staining. In Fig. 5A, the control group cells exhibit intact cell membranes, with nuclei stained purple by hematoxylin and a clear intercellular matrix. Figure 5B shows the model group cells, where numerous red lipid droplets are distributed both inside and outside the cell membranes. In Fig. 5C, the positive drug group demonstrates complete clearance of lipid droplets from the intercellular matrix, although some residual droplets remain within the cell membranes. Figures 5D-F illustrate the effects of different concentrations of RLF extract. As the concentration increases from low to high, there is a notable decrease in the intracellular lipid droplet content. Additionally, in the high-concentration treatment group, some lipid droplets within the cell membranes are also partially cleared.\u003c/p\u003e\n\u003ch2\u003e3.5.3 Evaluation of lipid-lowering activity of RLF extract\u003c/h2\u003e\n\u003cp\u003eTG and total T-CHO can be obtained from dietary sources as well as synthesized in the liver. These lipids serve as energy reserves stored in body and liver tissues, directly reflecting lipid levels in the body. Compared to the control group, the OA-induced NAFLD model exhibited significantly elevated levels of TG, T-CHO, LDL, ALT, and AST, as shown in Figs. 6A and 6B. Specifically, the TG and T-CHO contents in the model cells were 0.297 and 0.186 mmol/g protein, respectively, whereas in the RLF-H group, these values were reduced to 0.131 and 0.117 mmol/g protein, respectively. This indicates that RLF extract effectively reduces lipid levels in the model cells, with reductions of 55.9% in TG and 37.1% in T-CHO.\u003c/p\u003e\n\u003cp\u003eLDL is the primary form of cholesterol transport in the body. Elevated levels of LDL can lead to metabolic diseases and increase the risk of cardiovascular disease. As depicted in Fig. 6C, the LDL content in the model cells was approximately 0.194 mmol/g protein, while in the RLF-H group, it decreased to 0.145 mmol/g protein, representing a 25.3% reduction compared to the model group.\u003c/p\u003e\n\u003cp\u003eALT and AST are crucial transaminases involved in amino acid metabolism. In cases of acute liver damage, ALT and AST are released from liver cells into the bloodstream, resulting in elevated levels. Figures 6D and 6E illustrate that the ALT and AST levels in the model cells were 9.43 and 18.04 U/g protein, respectively, whereas in the RLF-H group, these levels were reduced to 3.06 and 8.81 U/g protein, respectively, showing decreases of 67.5% and 51.1% compared to the model group. This indicates that RLF extract can regulate the elevation of ALT and AST caused by damage, thereby improving lipid levels, and mitigating oxidative or inflammatory damage induced by lipid accumulation in the cells.\u003c/p\u003e\n\u003ch2\u003e3.6 Assessment of Antioxidant Activity of RLF Extract\u003c/h2\u003e\n\u003ch2\u003e3.6.1 Extracellular Antioxidant Activity\u003c/h2\u003e\n\u003cp\u003eThe DPPH assay measures the reduction of free radicals, while the ABTS assay evaluates antioxidant capacity by reacting generated free radicals with antioxidants. These are two commonly used methods for assessing antioxidant activity. As shown in Fig. 7A, the RLF extract demonstrated significant DPPH free radical reduction, with its scavenging activity exhibiting a concentration-dependent effect. At a concentration of 5 mg/mL, the DPPH free radical reduction capability of the RLF extract was 98.86%, approaching that of Vitamin C (99.49%). As illustrated in Fig. 7B, the RLF extract also exhibited strong ABTS free radical scavenging ability, achieving 100% ABTS scavenging capacity at 5 mg/mL, which is equivalent to the positive control, Vitamin C (100%). These results indicate that the RLF extract possesses substantial free radical reduction and scavenging abilities, suggesting potential antioxidant activity.\u003c/p\u003e\n\u003cp\u003e3.6.2 Intracellular Antioxidant Activity\u003c/p\u003e\n\u003cp\u003eFurther investigation into the lipid-lowering mechanism of RLF extract was conducted. T-AOC represents the overall amount of antioxidant substances in the body and is used to assess overall antioxidant capacity. As shown in Fig. 8A, the antioxidant capacity of the model group cells was reduced, with an intracellular T-AOC activity of approximately 0.058 mmol/g. In contrast, the T-AOC activity in the RLF-H group cells was approximately 0.243 mmol/g, representing an increase of 182.5%. SOD is a crucial antioxidant enzyme that plays a key role in protecting cells from oxidative damage. As depicted in Fig. 8B, SOD activity in the model group cells decreased, increasing the likelihood of oxidative stress. The SOD activity in the model group cells was approximately 4.04 U/mg protein, whereas in the RLF-H group cells, it was approximately 9.57 U/mg protein, reflecting an increase of 136.8%. MDA is an oxidative product generated from lipid peroxidation and is commonly used as an indicator of oxidative damage. As illustrated in Fig. 8C, the NAFLD cell model exhibited elevated lipid levels, exacerbating oxidative damage. The MDA content in the model group cells was approximately 0.708 mmol/mg protein, while in the RLF-H group cells, it was approximately 0.373 mmol/mg protein, representing a decrease of 47.3% compared to the model group. These results indicate that RLF extract can modulate oxidative damage induced by elevated lipid levels.\u003c/p\u003e\n\u003ch2\u003e3.7 RLF extracts promote the decrease of intracellular lipid levels by activating the PI3K-AKT signaling pathway.\u003c/h2\u003e\n\u003cp\u003eBased on network pharmacology and KEGG/GO pathway enrichment analysis, we hypothesize that RLF extract activates the AKT signaling pathway, with the PI3K-AKT pathway being involved in lipid metabolism in NAFLD hepatocytes. Through in vitro and in vivo antioxidant assays, we have determined that oxidative stress is involved in the onset and progression of NAFLD. To further investigate, we measured the protein expression levels of the PI3K-AKT signaling pathway in oleic acid-induced NAFLD hepatocyte lipid accumulation models. The results from WB analysis are shown in Fig. 9A. After normalizing the WB band intensity, as illustrated in Fig. 9B, the expression levels of AKT protein were consistent among the five experimental groups, indicating no significant inter-group differences in AKT protein content, which warrants further investigation into its phosphorylated form. Figure 9C D demonstrate that RLF extract significantly inhibited the overexpression of p-AKT and PI3K induced by oleic acid, with maximum inhibition rates reaching 63.6% and 70.28%, respectively. These experimental results suggest that RLF extract may exert its lipid-lowering effect through the PI3K-AKT signaling pathway, confirming the key pathway predicted by network pharmacology.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eNAFLD is characterized by the accumulation of lipids in the liver, independent of alcohol intake. This liver disease is quite common and can progress pathologically from simple fatty liver to steatohepatitis, fibrosis, and potentially to cirrhosis and liver cancer. The pathogenesis of NAFLD involves a complex interplay of multiple mechanisms. In recent years, the 'multiple hit' hypothesis has gained significant recognition\u003csup\u003e39\u003c/sup\u003e. This hypothesis posits that the development of NAFLD is a multifaceted process. Initial fat accumulation, triggered by poor dietary habits and obesity as the 'first hit,' induces hepatic lesions. Subsequently, 'multiple parallel hits'\u0026mdash;such as metabolic syndrome, drug toxicity, and insulin resistance\u0026mdash;further damage the liver, leading to inflammation and oxidative stress that accelerate disease progression. Currently, treatment options for NAFLD are relatively limited, focusing primarily on controlling underlying conditions, improving metabolic status, and mitigating liver damage\u003csup\u003e40\u003c/sup\u003e. Treatment approaches include lifestyle modifications, pharmacotherapy, and surgical interventions. However, long-term pharmacotherapy can lead to drug resistance and adverse effects\u003csup\u003e41\u003c/sup\u003e, while surgical interventions carry intraoperative risks and potential postoperative complications. Natural medicines, known for their eco-friendliness, high safety profile, and lower risk of resistance, have become a prominent area of interest for developing treatments for NAFLD\u003csup\u003e42\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn recent years, RLF has garnered increasing attention due to its lipid-lowering activity. Studies have shown that RLF extracts reduce the expression of key molecules involved in the fatty acid synthesis pathway, enhancing fatty acid β-oxidation and consequently alleviating hepatic lipid buildup caused by a high-fat diet in animal models\u003csup\u003e43\u003c/sup\u003e. Furthermore, research has demonstrated that total flavonoids and low-molecular-weight polysaccharides derived from RLF can lower blood lipid levels and enhance high-density lipoprotein cholesterol (HDL) levels by modulating the antioxidant system\u003csup\u003e44\u003c/sup\u003e. In this study, HPLC-QTOF-MS/MS was employed to identify the primary components of RLF extracts. Based on comparisons with literature and databases, 48 compounds were identified, including 10 flavonoids and their glycosides, 10 organic acids, 6 terpenes, 5 monosaccharides, 4 phenolic acids, and 2 ceramide compounds. Using area normalization, the relative percentage content of each component identified by liquid chromatography-mass spectrometry was calculated. Nine compounds in the RLF extract had a relative percentage content greater than 0.5\u0026permil;, including 2 flavonoids, 4 saponins, and 3 other compounds. We hypothesize that the lipid-lowering activity of RLF extracts may be attributed to the diverse range of flavonoid components, which aligns with findings reported in the literature. However, due to the complexity of lipid synthesis mechanisms, it remains challenging to pinpoint a specific primary factor or mechanism responsible for the lipid-lowering effects of RLF, necessitating further research in this area\u003csup\u003e45, 46\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe concept of 'network pharmacology' was first introduced in 2007\u003csup\u003e47\u003c/sup\u003e. It is an emerging discipline based on multidisciplinary concepts, including molecular biology, biochemistry, and bioinformatics. This field utilizes network-based information and systems biology techniques to study drug mechanisms, interactions, and targets\u003csup\u003e48\u003c/sup\u003e. By integrating extensive bioinformatics, cheminformatics, and pharmacological data, network pharmacology aims to understand drug mechanisms from a systems perspective, revealing interactions between drugs and multiple targets, thereby providing a theoretical foundation for the design of multi-target drugs\u003csup\u003e49\u003c/sup\u003e. In this study, network pharmacology was applied to predict the targets and pathways of \u003cem\u003eRosa laevigata\u003c/em\u003e Michx extract (RLFE) in the treatment of NAFLD. Database searches identified 244 RLFE-related targets and 1,928 NAFLD-related targets, with 126 targets overlapping between RLFE and NAFLD. These targets were imported into Cytoscape for protein-protein interaction (PPI) network analysis, which identified 65 key targets based on degree centrality. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted on the key targets. The GO enrichment analysis yielded a total of 1,340 entries, including 1,219 in biological processes (BP), 35 in cellular components (CC), and 86 in molecular functions (MF). Major processes included apoptosis, transcriptional repression, and autophagy receptor binding. The KEGG enrichment analysis identified 167 major pathways, including those related to cancer, lipid metabolism, atherosclerosis, and the PI3K-Akt signaling pathway. Multi-target drug therapies are becoming an important trend in this field.\u003c/p\u003e\u003cp\u003eThis study utilized OA to induce lipid accumulation in HepG2 human liver cancer cells, thereby establishing a cell model for NAFLD. The effect of OA on lipid accumulation in the NAFLD liver cell model was directly observed using ORO staining. The control group cells exhibited intact membranes, with nuclei stained purple by hematoxylin and clear interstitial areas. In contrast, the model group displayed numerous red lipid droplets distributed both inside and outside the cell membranes, confirming the successful construction of the NAFLD liver cell model. The impact of RLF extract on the cell model was then examined. It was found that as the concentration of the extract increased, lipid levels within the cells significantly decreased in the RLF-L, RLF-M, and RLF-H groups, providing preliminary evidence of the lipid-lowering activity of RLF extract. Subsequent experiments measured the effects of RLF extract on the NAFLD liver cell model using assay kits for TG, TC, LDL, ALT, and AST. The results indicated that in the RLF-H group, intracellular levels of TG, TC, and LDL were 0.131, 0.117, and 0.145 mmol/g protein, respectively, while ALT and AST levels were 3.06 and 8.81 U/g protein, respectively. Compared to the model group, intracellular lipid levels decreased by 55.9%, 37.1%, and 25.3%, respectively, while enzyme activity levels decreased by 67.5% and 51.1%. These results align with predictions from network pharmacology, demonstrating that RLF extract has significant lipid-lowering potential and can be used for the treatment of NAFLD. RLF extract notably reduces the levels of TG, TC, and LDL in diseased liver cells. Additionally, the inclusion of RLF extract lowered intracellular ALT and AST activity levels compared to the model group, indicating a modulation of liver cell damage induced by NAFLD and an improvement in cellular oxidative damage or inflammatory injury associated with elevated lipid levels.\u003c/p\u003e\u003cp\u003eResearch has demonstrated that RLF possesses remarkable antioxidant capabilities, with its high content of total flavonoids closely associated with its antioxidant activity, as confirmed by HPLC-Q-TOF-MS/MS analysis. The study also found that RLF total flavonoids significantly increased the concentrations of various antioxidant compounds, such as catalase (CAT), superoxide dismutase (SOD), glutathione (GSH), and glutathione peroxidase (GPX), in the liver of obese mice. Based on predictions from network pharmacology and KEGG and GO enrichment pathway analyses, it is hypothesized that RLF extract treats NAFLD through antioxidant pathways. To further investigate the antioxidant properties of RLF extract, subsequent experiments employed DPPH and ABTS assays to evaluate its free radical scavenging capacity, as well as T-AOC, SOD, and MDA assay kits to assess the antioxidant capability of the model cells after RLF extract treatment. The results showed that RLF extract exhibited strong free radical scavenging activity, with a concentration of 5 mg/mL achieving DPPH and ABTS scavenging effects comparable to those of vitamin C. Additionally, RLF extract increased the overall antioxidant capacity of HepG2 cells by 182.5%, enhanced intracellular SOD activity by 136.8%, and decreased the production of the lipid peroxidation product MDA by 47.3%, thus safeguarding the cells against oxidative damage. Serine/threonine kinase (AKT) has garnered significant attention in the medical field due to its essential role in regulating various cellular functions, including metabolism, growth, proliferation, survival, transcription, and protein synthesis\u003csup\u003e50\u003c/sup\u003e. Signals that activate or inhibit AKT can originate from receptor tyrosine kinases, integrins, B-cell and T-cell receptors, cytokine receptors, G protein-coupled receptors, and various stimuli that trigger the production of phosphatidylinositol (3,4,5)-trisphosphate (PIP3) via phosphatidylinositol 3-kinase (PI3K)\u003csup\u003e51\u003c/sup\u003e. The biomarker of the PI3K-AKT signaling pathway is reflected through the dynamic regulation of total PI3K and AKT proteins, as well as their phosphorylated forms\u003csup\u003e52\u003c/sup\u003e. The regulatory function of this pathway is linked to a variety of human diseases, including cancer, diabetes, lipid metabolism disorders, cardiovascular diseases, and neurological conditions. The PI3K-AKT signaling pathway was identified in the pathway enrichment predictions derived from network pharmacology. Consequently, this study employed Western blot analysis to evaluate the expression levels of PI3K, AKT, and phosphorylated AKT (p-AKT) proteins in NAFLD model cells treated with RLF. The experimental results indicated that RLF extract downregulated PI3K expression, activated the PI3K-AKT signaling pathway, and decreased the expression of p-AKT, effectively blocking the phosphorylation of the AKT protein. Specifically, the relative expression levels of PI3K and p-AKT in the cells were reduced by 63.6% and 70.28%, respectively. These findings suggest that consistent with predictions from network pharmacology and pathway enrichment analysis, RLF extract may modulate lipid metabolism by downregulating PI3K protein expression and inhibiting AKT phosphorylation, thereby affecting nuclear factor E2 (NF-E2) and regulating the downstream protein Nrf2\u003csup\u003e53\u003c/sup\u003e. This action contributes to the suppression of oxidative stress responses. These findings offer a fresh perspective on the application of RLF as both a medicinal and dietary plant for the treatment of NAFLD.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003econflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAcknowledgements This work was supported by National Natural Science Foundation of China (81703377), Young Top Talents in \u0026ldquo;Xing Liao Talent Program\u0026rdquo; (XLYC2007168) of Liaoning province of P. R. China, Foundation (LJKMZ20220786) from the Project of Education Department of Liaoning Province of P. R. China, Young and Middle-aged Scientific and Technological Innovation Talents in Shenyang (RC210148) of Liaoning province of P. R. China, Foundation (No. 2023JH2/101600021) from the Project of Science and Technology Department of Liaoning province of P. R. China, Foundation (2022YQ008) from the Excellent youth promotion project of Shenyang University of Chemical Technology, National-Local Joint Engineering Laboratory for Development of Boron and Magnesium Resources and Fine Chemical Technology (LJ232410149002).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eno funding\u003c/p\u003e\n\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eS. K. Erickson, Nonalcoholic fatty liver disease, \u003cem\u003eJournal of Lipid Research\u003c/em\u003e, 2009, \u003cstrong\u003e50 Suppl\u003c/strong\u003e, S412.\u003c/li\u003e\n\u003cli\u003eC. D. Byrne and G. Targher, NAFLD: a multisystem disease, \u003cem\u003eJ Hepatol\u003c/em\u003e, 2015, \u003cstrong\u003e62\u003c/strong\u003e, S47-64.\u003c/li\u003e\n\u003cli\u003eP. R. Maria, C. 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The fruit of \u003cem\u003eRosa laevigata\u003c/em\u003e Michx (RLF) is recognized for its diverse bioactive properties and has garnered significant attention for its potential use in developing dietary supplements for NAFLD treatment. However, its lipid-lowering efficacy and underlying mechanisms remain unclear. To investigate this, we developed an NAFLD cell model by treating HepG2 cells with oleic acid and evaluated the lipid-lowering effects of RLF extract. The effectiveness was measured using five indicators: triglycerides (TG), total cholesterol (T-CHO), low-density lipoprotein cholesterol (LDL-C), aspartate transaminase (AST), and alanine transaminase (ALT). The lipid-lowering mechanism was predicted using HPLC-MS alongside network pharmacology. Antioxidant ability was evaluated using DPPH and ABTS assays, with three indicators\u0026mdash;total antioxidant capacity (T-AOC), superoxide dismutase (SOD), and malondialdehyde (MDA)\u0026mdash;used to assess antioxidant effects. Additionally, Western blotting (WB) was employed to validate the network pharmacology predictions. Results indicated that, compared to the model group, the RLF extract significantly reduced TG, T-CHO, LDL, AST, and ALT levels by 55.9%, 37.1%, 25.3%, 67.5%, and 51.1%, respectively. T-AOC and SOD levels were significantly increased by 182.5% and 136.8%, respectively, while MDA content was reduced by 47.3%. WB analysis indicated that the RLF extract alleviated abnormalities in lipid metabolism and antioxidant-related genes PI3K and p-AKT. These findings suggest that the therapeutic effects of RLF extract on NAFLD may be mediated by the modulation of oxidative damage responses via the PI3K-AKT signaling pathway.\u003c/p\u003e","manuscriptTitle":"Inhibition of Lipid Accumulation in NAFLD Liver by Extract of Rosa laevigata Fruit Extract through Activation of the PI3K-AKT Signaling Pathway","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-01 21:36:44","doi":"10.21203/rs.3.rs-6926759/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fa157ae9-0212-4cac-95ed-6aa1990057e8","owner":[],"postedDate":"August 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":52321785,"name":"Biological sciences/Drug discovery/Target identification"},{"id":52321787,"name":"Biological sciences/Drug discovery/Target validation"},{"id":52321789,"name":"Health sciences/Diseases/Metabolic disorders"}],"tags":[],"updatedAt":"2026-05-15T06:24:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-01 21:36:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6926759","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6926759","identity":"rs-6926759","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}