Postoperative cognitive dysfunction in aged mice after sevoflurane inhalation: crosstalk of gut microbiota, metabolomics, and proteomics

Postoperative cognitive dysfunction in aged mice after sevoflurane inhalation: crosstalk of gut microbiota, metabolomics, and proteomics | 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 Research Article Postoperative cognitive dysfunction in aged mice after sevoflurane inhalation: crosstalk of gut microbiota, metabolomics, and proteomics Xutong Qu, Hongxu Li, Huiping Li, Zhenkun Dong, Hongyu Liu, Yu Xin, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4597888/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 Background: General anaesthesia, especially sevoflurane inhalation anaesthesia, is an independent risk factor for postoperative cognitive dysfunction. However, the molecular mechanism by which sevoflurane inhalation alters postoperative cognitive function remains unclear. Methods: According to the water maze behaviour experiment, sixteen-month-old mice receiving sevoflurane inhalation were divided into postoperative cognitive dysfunction and none cognitive dysfunction groups. Faecal samples were collected from two groups one day before intervention and 1, 3, and 7 days after. Moreover, hippocampal and serum samples were collected seven days after intervention. Faecal samples were analysed at the microbiome and metabolomics levels. The hippocampal samples were analysed using proteomics and metabolomics. Moreover, serum samples were analysed using metabolomics. Further, bioinformatics technology was used to integrate and analyse the omics. Results: The significantly downregulated Ohtaekwangia (P=0.022) and Odoribacter (P=0.016) in the intestinal microbes of aged mice with ostoperative cognitive function had a significant positive correlation with the faecal metabolite, guanosine-5'-monophosphate (P=0.008). At the same time, guanosine-5-monophosphate showed the same downward trend in stool and serum samples. In addition, 1,7-dimethylxanthine was significantly downregulated in the hippocampus of aged mice with ostoperative cognitive function and was positively correlated with calpastatin, whose expression was downregulated (P=0.013). Conclusions: Significant changes in microorganisms, proteins, and metabolites were detected in the faecal, serum, and hippocampal samples of aged mice with ostoperative cognitive function induced by sevoflurane inhalation. Moreover, there was a correlation between the three samples. These findings provide new insights into the mechanisms of ostoperative cognitive function. postoperative cognitive dysfunction sevoflurane hippocampus gut-brain axis proteomics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Highlights Our study applied multi-omics techniques to perform a joint analysis of multiple biological samples to explore the mechanism of sevoflurane-induced postoperative cognitive dysfunction. Significant changes in microorganisms, proteins, and metabolites were detected in the faecal, serum, and hippocampal samples of aged mice with POCD induced by sevoflurane inhalation. These findings provide new insights into the mechanisms of POCD. Introduction Postoperative cognitive dysfunction (POCD) is a common complication of anaesthesia and surgery, including mental disorders, anxiety, personality changes, and memory impairment[ 1 ]. Ageing and general anaesthesia, especially sevoflurane inhalation, are independent risk factors for POCD occurrence[ 2 , 3 ]. However, the underlying mechanisms of POCD remain unclear. Evidence has shown that the high incidence of POCD in older adults may be related to an imbalance in the inflammatory response, microcirculation disturbance, microembolism formation, and abnormal activation of microglial cells[ 4 – 6 ]. However, therapeutic strategies targeting inflammation, improving cerebrovascular circulation, inhibiting microembolism formation, and regulating activated microglial cells have not achieved satisfactory clinical effects[ 7 , 8 ]. The intestinal flora is a complex microbial community in the digestive tract that maintains the essential physiological functions of the intestine by participating in metabolism and other methods[ 9 ]. In addition, the intestinal flora can significantly influence the nervous system through the microbe-enterobrain axis[ 10 ]. In recent years, an imbalance of intestinal homeostasis has been related to various neurodegenerative diseases such as depression and Parkinson's disease[ 11 , 12 ]. Intestinal microbial metabolites, such as short-chain fatty acids, are essential transmission vectors along the microbe-entero-brain axis[ 13 ]. Increasing evidence suggests that gut microbes may affect the brain and behaviour through metabolism and immunity along the gut-brain axis[ 14 ]. Our earlier study found that sevoflurane inhalation anaesthesia was more significantly disturbed than propofol anaesthesia[ 15 ]. Furthermore, we found that delayed neurocognitive recovery after surgery was related to the preoperative intestinal flora and its related metabolite composition[ 16 ]. However, whether the intestinal flora and its metabolites are involved in developing POCD induced by sevoflurane inhalation anaesthesia is unclear. Studies on the hippocampus have always been at the core of human memory research[ 17 ]. Multiple animal studies have shown that hippocampal gene knockout or drug anaesthesia leads to learning and memory loss. Additionally, the hippocampus is associated with cognitive function and memory impairment during ag[ 18 ]. Evidence has shown that neuroinflammation caused by hippocampal microglial activation plays a crucial role in the pathogenesis of POCD[ 1 , 19 ]. Some studies attempted to apply proteomic and metabolomic techniques to study the mechanism of POCD, but there still needs to be more relevant studies based on multi-omics combined analysis[ 20 ]. Our study used multi-omics technology to analyse various biological samples jointly. Further, using bioinformatics technology, we explored the mechanism of postoperative cognitive dysfunction caused by sevoflurane inhalation in multiple dimensions to provide new intervention targets for its prevention and treatment. Materials and methods Animals Forty 16-month-old C57BL/6J male mice (40–50 g) were used in this experiment, provided by Jiangsu Wukong Biotechnology Co., LTD. According to the water maze behaviour experiment, sixteen-month-old mice anaesthetised with sevoflurane were divided into POCD and NCD (none cognitive dysfunction) groups. The mice were kept in standard cages on alternating 12 h light/dark cycles and were fed and watered ad libitum. This study was approved by the Ethics Committee of Harbin Medical University Cancer Hospital (Ethical Approval: KY2022 − 03) and complied with the Guide for the Care and Use of Laboratory Animals. Sevoflurane inhalation anaesthesia management The experimental mice were anaesthetised after seven days of adaptive rearing, as described in the experimental flowchart (Fig. 1 ). They were placed in an anaesthesia box and connected to an animal anaesthesia machine to continuously deliver sevoflurane at 5 L.min − 1 for 4 hours. The gas flow rate is continuously monitored and adjusted to maintain an oxygen concentration of 20% and a stable MAC(minimum alveolar concentration) value of 1.3, equivalent to 2.21% sevoflurane. A heating blanket was used to maintain the average body temperature(37°C ± 0.5°C) during sevoflurane inhalation anaesthesia, and the rectal temperature of mice was measured at 30-minute intervals. Moreover, the animals were continuously monitored for spontaneous breathing. After sevoflurane inhalation, the mice were fully awakened and returned to their cages. Morris water maze test The Morris water maze is often used to assess the spatial learning and memory function in rodents, which is divided into three parts: visual platform test, positioning navigation test, and spatial exploration test. A circular pool of 120 cm in diameter and 50 cm in height was divided into four quadrants. Place a 10 cm diameter white platform within the target quadrant. Data was recorded using a digital camera over a circular sink. Before intervention, the platform was placed 1cm above the water surface, and mice with visual and swimming impairments were excluded by a visual plateau test. On the third to sixth day after intervention, the white platform was concealed 1cm below the water surface for the positioning navigation test. Mice were allowed to swim and discover the hidden platform for 60 seconds. When the mice reached the platform, they were allowed to stay on it for 3 s, recording the time to find the hidden platform (to escape the latency period). On the seventh day, the platform was removed, and the mice were allowed to swim by themselves in the pool for the 60s. The number of locations across the original platform and the duration in the target quadrant were recorded. Samples collection Faecal samples were collected simultaneously on day one before the intervention and on days 1, 3, and 7 after and labelled S0, S1, S3, and S7, respectively. Mice were placed on sterile gauze in the laboratory’s centre of the operating table. Samples were collected in sterile freezer tubes with sterile cotton swabs immediately after the mice defecation were observed, labelled and stored in a -80℃ refrigerator. Serum and hippocampal specimens were collected on the seventh day after sevoflurane inhalation. Blood was collected from vessels without anticoagulant and precipitated at 37 ℃ for 60 min. The supernatant (serum) was obtained by centrifugation at 3000 rpm for 10 min at 4 ℃. The mice were then killed. The brain tissue was isolated, and the hippocampal tissue was isolated in frozen phosphate-buffered saline (PBS) solution. All samples were collected in sterile freeze-storage tubes, labelled, and stored in a -80 ℃ refrigerator. Microbiome analysis DNA was extracted using a DNA extraction kit (Thermo Fisher Scientific, MA, USA) for the corresponding sample. The length and concentration of the polymerase chain reaction (PCR) products were determined using 1% agarose gel electrophoresis. Samples with bright main strips were used for further experiments. Metabolomics analysis The sample stored in a -80°C refrigerator was thawed on ice. The sample was sonicated in an ice bath for 10 min and vortexed for 1 min. It was then placed in -20°C of ice for 30 min. After placing on ice for 15 min, the sample was centrifuged at 12000 rpm for 10 min (4°C). Exactly 300 µL of the supernatant was collected and placed in -20°C ice for 30 min. The sample was centrifuged at 12000 rpm for 3 min (4°C). Then, 200 µL aliquots of the supernatant were transferred for liquid chromatograph mass spectrometer (LC-MS) analysis. Proteomics analysis The sample was ground with liquid nitrogen into a cell powder and then transferred to a 5 mL centrifuge tube. After that, four volumes of lysis buffer (8 M urea, 1% protease inhibitor cocktail) were added to the cell powder, followed by sonication thrice on ice using a high-intensity ultrasonic processor (Scientz). Statistical analysis OTU (operational taxonomic units) was one of the most common terms in microbiology. The differences between groups were analysed by alpha diversity index using R software. Beta diversity analysis was used to evaluate differences of samples in species complexity through 9 algorithms, including bray_curtis, Euclidean, abund_jaccard, Canberra, chisq, chord, Gower, weighted_unifrac and unweighted_unifrac by R software. LDA Effect Size(LEfSe) analyses were used to find the biomarker of each group based on homogeneous OTU_table. Unsupervised PCA (principal component analysis) was performed by statistics function prcomp within R ( www.r-project.org ). The HCA (hierarchical cluster analysis) results of samples and metabolites were presented as heatmaps with dendrograms. In contrast, Pearson correlation coefficients (PCC) between samples were calculated by the cor function in R and presented as only heatmaps. For two-group analysis, differential metabolites were determined by VIP (VIP ≥ 1) and absolute Log2FC (|Log2FC| ≥ 1.0). VIP values were extracted from the OPLS-DA result, which contains score and permutation plots and was generated using the R package MetaboAnalystR. KEGG connects general information on molecular interaction networks, such as pathways and complexes, genes and proteins generated by genome projects, and biochemical compounds and reactions. It was, firstly, using KEGG online service tool KAAS to annotate the protein's KEGG database description. Then mapping, the annotation result on the KEGG pathway database using KEGG online service tool KEGG mapper. The escape latency of training, the number of platform crossings, and the duration within the target quadrant on the last day were used for hierarchical clustering analysis. Cluster analysis using SPSS21.0 divided the mice into the POCD and NCD groups (Fig. 2 ). In this study, the Cast expression of the subjects was used as the primary outcome measure, and the Cast expression in the NCD group was 931.39 ± 283.01, and in the POCD group was 474.35 ± 59.09, setting two-sided α = 0.05, and the confidence was 90%. The sample size was N1 = 6 for the POCD group and N2 = 6 for the NCD group, with at least 12 experimental animals. The chi-square test and variable analysis assessed the significance of continuous variables consistent with a normal distribution. Statistical significance was set at P < 0.05. Results Morris water maze test results between the POCD and NCD groups The Morris water maze test (MWMT) was used to assess cognitive behaviour in the mice. Mice were classified into the POCD and NCD groups by hierarchical clustering analysis based on escape latency, platform crossing times, and time spent in the target quadrant in the water maze(Fig 2). The two groups had no significant differences in body weight or swimming speed. Moreover, mice in the POCD group showed a significantly increased escape latency and significantly reduced platform crossings and time spent in the target quadrant (Table 1). Microbiome analysis of faecal samples The Venn diagram (Fig 3A) shows 693 standard operational taxonomic units (OTU) in the eight groups. In addition, the number of specific OTUs in the POCD and NCD groups tended to increase and decrease at S0, S1, and S3. The number of specific OTUs was almost similar between the NS7 and NS0 groups, whereas that in the PS7 group was significantly lower compared to the PS0 group. This indicates that the POCD group had the same dynamic trend as the NCD group during the three days of sevoflurane inhalation. The number of OTUs in the NCD group returned to pre-intervention levels on the seventh day after the intervention, whereas that in the POCD group decreased significantly after the seventh day. For alpha diversity, the Chao1 index showed no significant difference between the PS0, PS1, PS3, and PS7 groups (P> 0.05) (Fig 3B), and there was no significant difference between the NS0, NS1, NS3, and NS7 groups (P> 0.05) (Fig 3C). This indicates a slight variation in species richness and microbial community diversity between the POCD and NCD groups. For beta diversity, the unweighted UniFrac algorithm was used to analyse the differences among the groups using principal coordinate analysis (PCoA). The results showed that the PS0-PS1 (P=0.615) and PS1-PS3 (P=0.127) groups clustered significantly, indicating that the microbial species composition of the POCD group changed little within three days after intervention. However, the PCoA results showed that the PS7-PS0 (P=0.048), PS7-PS1 (P=0.015), and PS7-PS3 (P=0.021) groups were significantly isolated, indicating that the microbial species composition of the POCD group changed significantly on the seventh day after the intervention (Fig 3D). In the NCD group, NS0-NS1 (P=0.306), NS1-NS3 (P=0.313) and NS3-NS7 (P=0.289) were significantly clustered, and only the NS0-NS7 group was significantly separated (P=0.026) (Fig 3E). Therefore, based on the significant aggregation in the PS0-NS0 group (P=0.438), the microbial differences in the PS7-PS0 group and NS7-NS0 group were noteworthy, which may have been due to microbial differences between the POCD and NCD groups (Fig 3F-H). Table 2 shows the differential microorganisms between the groups (PS7-PS0 and NS7-NS0), with 40 differences in the PS7-PS0 group and 27 differences in the NS7-NS0 group. At the genus level, Butyrivibrio and Candidatus_Saccharimonas were co-enriched in the PS0 and NS0 groups but not in the PS7 and NS7 groups. The anaesthetic intervention may have affected the POCD and NCD groups. In addition, Odoribacter, Ohtaekwangia, Conexibacter, and the CL500_29_marine_group were not significantly different in the PS0-NS0 and NS7-NS0 groups but were significantly different in the PS7-PS0 group. Odoribacter, Ohtaekwangia, and CL500_29_marine_group were enriched in the PS0 group, and Conexibacter was significantly enriched in the PS7 group. Metabolomics analysis of the faecal samples The results of the principal component analysis showed a significant separation of the NS0-NS1 group samples and the relative aggregation of the NS1-NS3 and NS3-NS7 groups (Fig 4A-C). In contrast, the PS0-PS1, PS1-PS3, and PS3-PS7 groups were relatively significantly separated (Fig 4D-F). This indicates that the metabolites in the NCD group changed only considerably within one day after intervention and changed less from the first day to the seventh day after intervention. The POCD group continued to change significantly during the seven days after intervention, and the most significant change occurred between days one and three after intervention. Volcano maps showed the distribution of differential metabolites between the POCD and NCD groups (Fig 4G-L). The differential metabolites in the NS0-NS1, NS1-NS3, and NS3-NS7 groups were 43, 9, and four, respectively. The numbers of differential metabolites in the PS0-PS1, PS1-PS3, and PS3-PS7 groups were 24, 42, and 23, respectively. We found that some differential metabolites showed continuous changes; for example, the 3,4-dihydroxyphenylacetate content continuously decreased in the first three days in the NCD group, showing an upward trend from the third day to the seventh day, and returned to pre-intervention levels. Conversely, its content first increased and then decreased in the POCD group and was significantly lower than the pre-intervention level. We brought the differential metabolites into an authoritative metabolite database, such as the Kyoto Encyclopedia of Genes and Genomes (KEGG), for search and metabolic pathway analysis, which was reflected as a bubble map[21]. We found that caffeine metabolism was the only metabolic pathway jointly enriched for the differential metabolites between the POCD and NCD groups in the hippocampal, serum, and faecal samples. Metabolomics analysis of serum samples The orthogonal partial least squares-discriminant analysis (OPLS-DA) results showed that the samples were significantly separated between the POCD-NCD and NCD groups (Fig 5A). The differential metabolite screening conditions were: variable importance in projection (VIP) >1 with a p-value 2 or <0.5 indicated significantly upregulated or significantly downregulated differential metabolites, respectively. We used volcano maps to visualise the distribution of differential metabolites in serum samples between the POCD and NCD groups (Fig 5B). Table 3 shows five differential metabolites, 3-methylxanthine, asn-glu, glycerol 2-phosphate, l-saccharopine, and leu-asp, were significantly upregulated. Seven differential metabolites, 4-methyl-5-thiazole-ethanol, adrenosterone, ammelide, guanosine-5'-monophosphate, lys-ile, taurocholic acid, and xanthosine, were significantly downregulated. KEGG pathway enrichment analysis was performed based on the differential metabolite results of the serum samples from the POCD-NCD group. The top 20 pathways are presented in a bubble chart (Fig 5C). Notably, the enrichment of purine and nucleotide metabolism pathways were associated with three downregulated metabolites: guanosine-5'-monophosphate, guanosine, and xanthosine. Moreover, the caffeine metabolism pathway is a common metabolic pathway between the hippocampal and serum samples. Metabolomic analysis of the hippocampal samples The results of the OPLS-DA showed that the samples were significantly separated between the POCD-NCD groups. Meanwhile, the metabolites in the POCD group were significantly dispersed compared with the sample aggregation trend in the NCD group (Fig 6A). We used volcano plots to visualise the distribution of differential metabolites in the hippocampal samples between the POCD and NCD groups (Fig 6B). Table 4 shows that three differential metabolites, asterina-330, hydantoin-5-propionic acid, and val-his, were significantly upregulated. Four differential metabolites, 1,7-dimethylxanthine, 6-methylaminopurine, l-ascorbate, and theophylline, were significantly downregulated. The results showed that 14 metabolic pathways were enriched, including the caffeine metabolism and HIF-1 signalling pathways(Fig 6C). Among these, the enrichment of the caffeine metabolism pathway was associated with two downregulated metabolites: 1,7-dimethylxanthine and theophylline. A combined proteomics-metabolomic analysis was performed to explorewhether there is a common pathway between differentially expressed proteins and metabolites. Pearson's correlation analysis was performed with a correlation coefficient >0.80 and a p-value <0.05. Fig 6D shows that 11 metabolites were significantly associated with 12 proteins. Among them, the differential metabolites 1,7-dimethylxanthine and theophylline, showed a significant positive correlation with calpastatin. Proteomics analysis of the hippocampal samples Exactly 7,746 proteins were identified in the 12 hippocampal samples, of which 6,780 were quantifiable (Fig 7A). The principal component analysis (PCA) results showed significant differences between the two groups of hippocampal samples (Fig 7B). To identify the proteins involved in POCD, we compared the differential protein expression between the POCD and NCD groups in the hippocampal samples. When the p-value was <0.05, a fold change above 1.5 indicated significant upregulation and a fold change less than 1/1.5 indicated significant downregulation. The results showed that 34 proteins were differentially expressed in the hippocampal samples, including 12 upregulated and 22 downregulated proteins. Detailed information on the differentially expressed proteins between the POCD and NCD groups, including protein accession, corresponding gene names, fold changes, p-values, regulatory type, and subcellular localisation, is presented in Table 5. Discussion Our study applied multi-omics techniques to perform a joint analysis of multiple biological samples to explore the mechanism of sevoflurane-induced postoperative cognitive dysfunction. The results showed that compared with the non-POCD group, significant changes in microorganisms, proteins, and metabolites were detected in the stool, serum, and hippocampal samples of aged mice with POCD, and there was a correlation among the three groups of samples. Compared with the non-POCD group, the intestinal microorganisms of the Ohtaekwangia, Odoribacter, and CLB500_29 marine groups were significantly downregulated in aged mice with POCD. Ohtaekwangia and Odoribacter were significantly and positively correlated with the faecal metabolite guanosine-5-monophosphate. Meanwhile, guanosine-5-monophosphate was also downregulated in serum samples of aged mice with POCD; guanosine-5-monophosphate showed the same downward trend in faecal and serum samples. In addition, xanthosine, an intermediate of purine metabolism and an upstream substrate of caffeine metabolism was significantly downregulated in the serum of aged mice with POCD. Studies have shown that caffeine metabolites, such as theophylline and theobromine, are associated with neurodegenerative diseases such as Alzheimer's and Parkinson's diseases[ 22 ]. In our study, 1,7-dimethylxanthine, a caffeine metabolite, was associated with POCD development. 1,7-dimethylxanthine is a metabolite significantly downregulated in the hippocampus of aged mice with POCD, suggesting that 1,7-dimethylxanthine (paraxanthine) may be a key factor in exerting anti-sevoflurane anaesthesia-induced POCD. 1,7-dimethylxanthine is an adenosine A2A receptor antagonist. It has been shown that overexpression of the adenosine A2A receptor can be activated by the Gs-AC-cAMP pathway and then facilitate GSK-3β to promote tau hyperphosphorylation[ 23 ]. In addition, 1,7-dimethylxanthine in the hippocampus of POCD mice was found to be significantly and positively correlated with calpastatin, and calpastatin expression was downregulated. Calpastatin is an intrinsically unstructured protein that reversibly binds to and inhibits calpain[ 24 ]. Several studies have shown that the overexpression of calpastatin has a protective effect on neurons and slows the occurrence of degenerative diseases, such as Alzheimer's disease and Huntington's disease[ 25 , 26 ]. Our study is the first to find an association between calpastatin and POCD. The overexpression of calpain cleaves and activates GSK-3β, phosphorylating tau, leading to neurodegenerative diseases[ 27 ]. In addition, calpain can cleave p35 into p25, and the p25 generated over-activates cyclin-dependent kinase 5 (CDK5), leading to the intracellular accumulation of the microtubule-associated protein tau, which is related to the occurrence and development of neurodegeneration[ 27 ]. The tau protein is a cytoskeletal protein whose abnormal accumulation in cells damages learning and memory function, and its hyperphosphorylation is involved in the pathogenesis of various progressive neurological diseases[ 28 , 29 ]. There is a common signalling pathway (GSK-3β signalling pathway) between 1,7-dimethylxanthine and calpastatin in the mechanism of tau hyperphosphorylation mediating sevoflurane anaesthesia induced-POCD. Therefore, it is reasonable to speculate that the metabolite, 1,7-dimethylxanthine, activates calpastatin to reduce tau hyperphosphorylation mediated by GSK-3β and CDK5 signalling pathways, thereby alleviating POCD caused by sevoflurane anaesthesia. The neurophysiological basis of learning and memory includes long-term potentiation (LTP) and long-term depression (LTD), representing enhanced and decreased synaptic functional strength. Interestingly, we found that both adenosine A2A receptor and calpain can affect LTP and LTD indirectly by affecting synaptic function. The mechanism of LTP occurrence lies in the activation of the ERK signalling pathway by multiple pathways, while LTD lies in the activation of the PKC pathway. LTP and LTD differ because four pathways mediate calcium (glutamate receptor, voltage-gated calcium channel, NMDA receptor, and sodium exchange channel)[ 30 ]. In contrast to LTD, NDMAR is a unique receptor in the LTP pathway, resulting in significantly higher intracellular calcium concentration in LTP cells[ 31 ]. In LTD cells, low concentrations of calcium ions are highly susceptible to activating phosphatases, namely PKC. Overexpression of calpain-2 inhibited the ERK pathway, which in turn terminated LTP[ 27 ]. This makes us believe that calpastatin downregulation causing overexpression of calpain, plays a crucial role in the development of POCD. In addition, studies have shown that although adenosine A2A receptors play an active role in the regulation of LTP and memory in the hippocampus, ageing or overactivation of adenosine A2A receptors can trigger harmful synaptic effects that lead to LTP to LTD transition and reduce hippocampal-dependent learning and memory processes[ 32 ]. This confirms the role of the down-regulated metabolite 1,7 dimethylxanthine and the low-expressed protein calpastatin in POCD. Therefore, we speculate that the down-regulation of 1,7 dimethylxanthine and the low expression of calpastatin leads to the hyperactivation of adenosine A2A receptor and calpain, respectively, both involved in the occurrence of LTD, leading to the impairment of hippocampal learning and cognitive function. Our study had some limitations. First, because human hippocampal tissue is challenging to obtain, we only used old mice to explore the mechanism of POCD. Second, We did not verify the differential bacterial flora, metabolites and proteins in the occurrence of POCD caused by sevoflurane anesthesia, which is included in our next research plan. Significant changes in microorganisms, proteins, and metabolites were detected in mice’s faecal, serum, and hippocampal samples with POCD induced by sevoflurane anaesthesia. Moreover, there was a correlation between the three samples. These findings provide new insights into the mechanisms of POCD. Abbreviations HCA hierarchical cluster analysis KEGG Kyoto Encyclopedia of Genes and Genomes LC-MS liquid chromatograph mass spectrometer LTD long-term depression LTP long-term potentiation MAC minimum alveolar concentration MWMT The Morris water maze test NCD none cognitive dysfunction OPLS-DA The orthogonal partial least squares-discriminant analysis OTU operational taxonomic units PBS phosphate-buffered saline PCA principal component analysis PCC Pearson correlation coefficients POCD postoperative cognitive dysfunction VIP variable importance in projection Declarations Funding Supported by the Outstanding Youth Project Foundation of Harbin Medical University Cancer Hospital (JCQN2021-05), Haiyan Research Foundation of Harbin Medical University Cancer Hospital (JJZD2022-04), and the Natural Science Foundation of Heilongjiang Province (JJ2020YX0472). Competing Interests There are no conflicts of interest to declare. Auther contributions ZDZ, CSW, and XTQ designed this work. XTQ wrote the manuscript. XTQ, HPL, HXL, YX and YXZ performed the experiments. XTQ and HYL, ZKD analyzed the data. JYL, SFW, MQL, XYZ and XQY reviewed and edited the manuscript. All authors approved the present version of the manuscript and agreed to be accountable for all aspects of the work, including any questions related to the accuracy or integrity of any part of the work. Data Availability The datasets generated during and/or analysed during the current study are not publicly available due to [REASON(S) WHY DATA ARE NOT PUBLIC] but are available from the corresponding author on reasonable request.]. Ethics approval and consent to participate This study was approved by the Ethics Committee of Harbin Medical University Cancer Hospital (Ethical Approval: KY2022−03) and complied with the Guide for the Care and Use of Laboratory Animals. Consent for publication Not applicable. Acknowledgements This research receives no specific grant from funding agencies in the public, commercial, or not-for-profit sectors. All authors have read and understood your journal’s policies and believe that neither the manuscript nor the study violates any of these. There are no conflicts of interest to declare. References Luo AL et al (2019) Postoperative cognitive dysfunction in the aged: the collision of neuroinflammaging with perioperative neuroinflammation. INFLAMMOPHARMACOLOGY (Suppl 1) Bhushan S et al (2021) Progress of research in postoperative cognitive dysfunction in cardiac surgery patients: A review article. Int J Surg 95:106163 Wang CM et al (2021) Update on the Mechanism and Treatment of Sevoflurane-Induced Postoperative Cognitive Dysfunction. Front Aging Neurosci 13 Fan W et al (2020) The Role of Microglia in Perioperative Neurocognitive Disorders. 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Neural Regen Res 18(6):1213–1219 Zuo CL et al (2018) Isoflurane anesthesia in aged mice and effects of A1 adenosine receptors on cognitive impairment. CNS Neurosci Ther 24(3):212–221 Malenka RC, Bear MF (2004) LTP and LTD: an embarrassment of riches. Neuron 44(1):5–21 Artola A, Singer W (1993) Long-term depression of excitatory synaptic transmission and its relationship to long. 16(11):480–487 Gessi S et al (2021) A2A Adenosine Receptor as a Potential Biomarker and a Possible Therapeutic Target in Alzheimer's Disease. Cells 10(9) Tables Table 1. Characteristics of the animals Characteristics of the animals Characteristics POCD Group NCD Group P-value Body weight (g) 42.87±5.13 44.90±7.28 0.311 Swimming speed （ m/s ） 0.10±0.04 0.12±0.03 0.476 Escape latency (s) 42.68±13.18 5.02±0.95 0.009 Platform crossing 0.67±0.82 5.67±1.21 0.002 Time spent in the target quadrant (s) 16.57±7.72 36.92±3.11 0.002 Table 1: Significant comparison results of differences in body weight, swimming speed, escape latency, number of platform crossing, and time spent in the target quadrant between the NCD and POCD groups. P <0.05 indicates statistically significant differences. Table 2. Differential microorganisms in faecal samples biomarker ID Group LDA p-value f_Ilumatobacteraceae PS0 3.553522144 0.036048708 g_CL500_29_marine_group PS0 3.554559091 0.036048708 s_metagenome PS0 3.546063594 0.036048708 g_Enterorhabdus.uncultured_bacterium PS7 3.073131945 0.016309172 c_Thermoleophilia PS7 3.485439346 0.037040731 o_Solirubrobacterales PS7 3.485439346 0.037040731 f_Solirubrobacteraceae PS7 3.450206679 0.022486683 g_Conexibacter PS7 3.582288204 0.022229618 f_Marinifilaceae PS0 3.971636472 0.016309172 g_Odoribacter PS0 3.972239408 0.016309172 f_Rikenellaceae PS0 4.281527705 0.037372988 g_Alistipes.uncultured_bacterium PS0 3.509221225 0.01040562 g_Rikenellaceae_RC9_gut_group PS0 4.104646262 0.037372988 g_Rikenellaceae_RC9_gut_group.uncultured_bacterium PS0 4.104646262 0.037372988 f_Microscillaceae PS0 3.66832202 0.022229618 g_Ohtaekwangia PS0 3.670305613 0.022229618 c_Anaerolineae PS7 3.059196505 0.037372988 o_RBG_13_54_9 PS7 3.072388399 0.005587505 p_Firmicutes PS7 4.912249244 0.024974679 g_Defluviitaleaceae_UCG_011.uncultured_bacterium PS0 3.462890711 0.022229618 f_Lachnospiraceae PS0 4.407837846 0.037372988 g_Butyrivibrio PS0 3.370240017 0.024974679 g_Butyrivibrio.uncultured_bacterium PS0 3.370240017 0.024974679 g_Lachnospiraceae_NK4A136_group.uncultured_bacterium PS0 4.023009383 0.037372988 g_Lachnospiraceae_UCG_004 PS7 3.329031988 0.036048708 g_Lachnospiraceae_UCG_004.uncultured_bacterium PS7 3.319621663 0.036048708 f_Ruminococcaceae.uncultured PS0 3.303382901 0.024974679 p_Patescibacteria PS0 4.554204037 0.01040562 o_Saccharimonadia PS0 4.554226607 0.01040562 f_Saccharimonadales PS0 4.554226607 0.01040562 g_Saccharimonadaceae PS0 4.554122062 0.01040562 g_Candidatus_Saccharimonas PS0 4.554122062 0.01040562 g_Candidatus_Saccharimonas.uncultured_bacterium PS0 4.578665051 0.01040562 o_Micavibrionales PS0 3.217512761 0.046319841 o_Micavibrionales.uncultured PS0 3.21888866 0.046319841 f_Hyphomicrobiaceae PS7 3.048603048 0.023968274 f_Desulfovibrionaceae.uncultured PS0 3.792295384 0.003947752 f_Desulfovibrionaceae.uncultured.uncultured_bacterium PS0 3.787585717 0.003947752 c_Gammaproteobacteria PS7 4.190561275 0.01040562 g_966_1 PS7 3.856100637 0.049336176 g_Butyrivibrio NS0 3.541786514 0.024974679 g_Butyrivibrio.uncultured_bacterium NS0 3.541786514 0.024974679 g_Tyzzerella_3 NS0 3.205501216 0.022229618 g_Tyzzerella_3.uncultured_bacterium NS0 3.205075096 0.022229618 g_Ruminiclostridium_6 NS0 3.548603119 0.01040562 g_Ruminiclostridium_6.uncultured_bacterium NS0 3.548603119 0.01040562 p_Nitrospirae NS7 3.036479554 0.024974679 c_Nitrospira NS7 3.036479554 0.024974679 o_Nitrospirales NS7 3.036479554 0.024974679 f_Nitrospiraceae NS7 3.036479554 0.024974679 g_Nitrospira NS7 3.036479554 0.024974679 p_Patescibacteria NS0 4.49069674 0.024974679 c_Saccharimonadia NS0 4.490737375 0.024974679 o_Saccharimonadales NS0 4.490737375 0.024974679 f_Saccharimonadaceae NS0 4.490759623 0.024974679 g_Candidatus_Saccharimonas NS0 4.490759623 0.024974679 g_Candidatus_Saccharimonas.uncultured_bacterium NS0 4.466910366 0.024974679 p_Planctomycetes NS0 3.061987175 0.013195103 c_Planctomycetacia NS0 3.075370776 0.049510167 o_Gemmatales NS0 3.427979079 0.022229618 f_Gemmataceae NS0 3.42615159 0.022229618 f_Gemmataceae.uncultured NS0 3.427332997 0.022229618 f_Gemmataceae.uncultured.uncultured_bacterium NS0 3.429701721 0.022229618 g_Rhodoplanes NS0 3.330347491 0.022229618 f_Nitrosomonadaceae.966_1 NS0 3.430297423 0.022229618 f_SC_I_84 NS7 3.696940915 0.021025213 g_Escherichia_Shigella NS7 4.504038153 0.037372988 Table 2: Detailed information on differential microorganisms in faecal samples. The criteria for differential microorganisms were LDA > 2. Table 3. Differential metabolites in serum samples Formula Compounds VIP P-value Fold_Change Log2FC Type C6H6N4O2 3-Methylxanthine 2.972 0.009 803.310 9.650 up C9H15N3O6 Asn-Glu 2.975 0.002 832.221 9.701 up C3H9O6P Glucerol 2-phosphate 2.142 0.044 367.972 8.523 up C11H20N2O6 L-Saccharopine 2.970 0.005 6202.677 12.599 up C10H18N2O5 Leu-Asp 2.971 0.003 705.573 9.463 up C6H9NOS 4-methyl-5-thiazole-ethanol 2.928 0.037 0.001 -9.754 down C19H24O3 Adrenosterone 2.952 0.012 0.002 -9.099 down C3H4N4O2 Ammelide 2.966 0.004 0.002 -9.337 down C10H14N5O8P Guanosine-5'-monophosphate 2.966 0.008 0.002 -8.928 down C12H25N3O3 Lys-Ile 1.969 0.036 0.389 -1.360 down C26H45NO7S Taurocholic acid 2.106 0.015 0.456 -1.132 down C10H12N4O6 Xanthosine 1.964 0.017 0.318 -1.653 down Table 3: Detailed information on differential metabolites between the POCD versus NCD groups in serum samples. Differential metabolite screening conditions were VIP> 1 with a P-value 2 or <0.5 were significantly upregulated or significantly downregulated differential metabolites, respectively. Table 4. Differential metabolites in hippocampal samples Formula Compounds VIP P-value Fold_Change Log2FC Type C12H20N2O6 Asterina-330 3.312 0.000 3636.850 11.828 up C6H8N2O4 Hydantoin-5-propionic acid 3.308 0.003 521.877 9.028 up C11H18N4O3 Val-His 3.302 0.003 759.084 9.568 up C7H8N4O2 1,7-Dimethylxanthine 2.422 0.013 0.465 -1.105 down C6H7N5 6-Methylaminopurine 3.250 0.013 0.003 -8.168 down C6H8O6 L-Ascorbate 2.840 0.005 0.000 -16.783 down C7H8N4O2 Theophylline 2.422 0.013 0.465 -1.105 down Table 4: Detailed information on differential metabolites between the POCD versus NCD groups in hippocampal samples. Differential metabolite screening conditions were VIP> 1 with a P-value 2 or <0.5 were significantly upregulated or significantly downregulated differential metabolites, respectively. Table 5. Differentially expressed proteins of hippocampal samples Protein accession Gene name P/N Ratio P/N P value Regulated Type Subcellular localisation P52432 Polr1c 1.582 0.045635508 Up cytoplasm O08601 Mttp 1.813 0.037428808 Up endoplasmic reticulum Q8BH73 Qpctl 1.588 0.046340584 Up endoplasmic reticulum Q9EPK6 Sil1 1.577 0.013465678 Up extracellular Q8JZM4 Dner 3.262 0.002038935 Up extracellular Q9WUZ9 Entpd5 1.717 0.013442506 Up extracellular Q9JMB8 Cntn6 1.906 0.010264835 Up extracellular Q64299 Ccn3 1.618 0.034414975 Up extracellular Q06770 Serpina6 2.03 0.001718079 Up extracellular P48986 Neurod6 1.707 0.046623701 Up nucleus Q9JJG6 Tmem47 1.54 0.013017069 Up plasma membrane Q8VCB1 Ndc1 2.39 0.001601161 Up plasma membrane Q9Z2P8 Vamp5 0.633 0.021418616 Down cytoplasm O88843 Cradd 0.52 0.040237402 Down cytoplasm Q8CI33 Cwf19l1 0.387 0.000863387 Down cytoplasm Q6Q899 Ddx58 0.65 0.023261916 Down cytoplasm Q6A037 N4bp1 0.602 0.031125432 Down cytoplasm Q9D6Y4 Borcs8 0.657 0.017121825 Down cytoplasm, nucleus P24456 Cyp2d10 0.551 0.028771748 Down endoplasmic reticulum Q3UPR9 Sbspon 0.532 0.032850969 Down extracellular P27573 Mpz 0.508 0.031274911 Down extracellular Q5SUC9 Sco1 0.521 0.003330537 Down mitochondria Q91W29 Cox4i2 0.623 0.032274786 Down mitochondria P59041 Dnajc30 0.507 0.002733886 Down mitochondria Q9CPX8 Uqcr11 0.587 0.044425442 Down mitochondria Q8BX02 Kank2 0.535 0.025434849 Down nucleus P48437 Prox1 0.563 0.045585033 Down nucleus P51125 Cast 0.569 0.047152037 Down nucleus P63058 Thra 0.637 0.03590968 Down nucleus Q3THK3 Gtf2f1 0.638 0.016581782 Down nucleus Q6KCD5 Nipbl 0.587 0.007491123 Down plasma membrane P03903 Mtnd4l 0.562 0.018354136 Down plasma membrane Q7TQK1 Ints7 0.663 0.012800196 Down plasma membrane Q3UEZ8 Slc10a4 0.618 0.040137689 Down plasma membrane Table 5 ： Details of the differentially expressed proteins between the POCD and NCD groups in the hippocampal samples. Fold change> 1.5 and P <0.05 were considered statistically significant. 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-4597888","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":319088269,"identity":"837ed39b-139e-450c-8916-aeb38dc7bf85","order_by":0,"name":"Xutong Qu","email":"","orcid":"","institution":"Harbin Medical University Cancer Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xutong","middleName":"","lastName":"Qu","suffix":""},{"id":319088270,"identity":"4db5e120-791d-49d3-895f-d205f4af2ced","order_by":1,"name":"Hongxu Li","email":"","orcid":"","institution":"First Affiliated Hospital of Harbin Medical 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06:50:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4597888/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4597888/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60492401,"identity":"9d1c339c-880c-495e-898d-71a7f9c0580c","added_by":"auto","created_at":"2024-07-17 10:59:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":7338495,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of the study. Mice were acclimatised for seven days before intervention and visual platform experiments. Days 1 and 2 were recovery days. Positioning and navigation experiments were performed on days 3-6. Space exploration experiments were performed on day 7. Stool samples were collected simultaneously on day one before intervention and days 1, 3 and 7 after. Serum and hippocampal samples were collected on day seven post-intervention.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4597888/v1/388e94657a50af05c8522320.png"},{"id":60492406,"identity":"4ada889f-d72a-4261-973e-5b5375607b24","added_by":"auto","created_at":"2024-07-17 10:59:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5260667,"visible":true,"origin":"","legend":"\u003cp\u003eHierarchical clustering analysis according to the Morris water maze results.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4597888/v1/22505bf4412a0f4d3458d447.png"},{"id":60492404,"identity":"6dd87669-d269-4d8c-8651-3c6d057885d3","added_by":"auto","created_at":"2024-07-17 10:59:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":10948938,"visible":true,"origin":"","legend":"\u003cp\u003eA) The Venn diagram of the OTU numbers of the eight groups. Different colours represent different groups, overlapping areas represent the number of OTUs shared by the group, and non-overlapping areas represent the number of OTUs unique to the group. (B, C) The alpha diversity analysis (Chao 1 index) of PS0, PS1, PS3, and PS7 groups and NS0, NS1, NS3, and NS7 groups. (D, E) The beta diversity analysis (PCoA) of the PS0-NS0 and PS7-NS7 groups. (F, G, H) The alpha diversity analysis (Chao 1 index) of the PS0-NS0 groups, the PS0-PS7 groups and the NS0-NS7 groups. The \"*\" indicates a statistically significant difference at P\u0026lt;0.05, and the \"NS\" indicates no significant difference at P\u0026gt;0.05. n=6 per group.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4597888/v1/cb14a743209fbb7904067bed.png"},{"id":60492407,"identity":"33aa8282-80a9-4315-bd17-95b926180c36","added_by":"auto","created_at":"2024-07-17 10:59:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4584454,"visible":true,"origin":"","legend":"\u003cp\u003e(A-C) Principal component analysis diagram of NS0-NS1-NS3-NS7 groups. (D-F) Principal component analysis diagram of PS0-PS1-PS3-PS7 groups. (G-L) Volcano plots were mainly used to show the differences in the relative content of metabolites in the six sets of samples and the statistically significant differences.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4597888/v1/fa871a750e7214b30451b455.png"},{"id":60492412,"identity":"2cd4cb2e-5277-4f9b-98e3-4f9980334d64","added_by":"auto","created_at":"2024-07-17 10:59:23","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":7407372,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Orthogonal partial least squares discriminant analysis plot of serum samples from the POCD and NCD groups. The abscissa coordinates show the gap between the groups, and the ordinate coordinates show the gap within the group. n=6 per group. (B) Volcano plots were mainly used to show the differences in the relative content of metabolites in the two sample sets and the statistically significant differences. (C) Bubble diagram of metabolic pathways of different metabolites.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4597888/v1/dcd7b9275e6dcbd086da3466.png"},{"id":60492403,"identity":"92b76730-5c81-44ed-90d3-cd3b853610ed","added_by":"auto","created_at":"2024-07-17 10:59:23","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":7656096,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Orthogonal partial least squares discriminant analysis plot of hippocampal samples from the POCD and NCD groups. The abscissa coordinates show the gap between the groups, and the ordinate coordinates show the gap within the group. n=6 per group. (B) Volcano plots were mainly used to show the differences in the relative content of metabolites in the two sample sets and the statistically significant differences. (C) Bubble diagram of metabolic pathways of different metabolites. (D) Pearson correlation analysis for the nine-quadrant plot. The third quadrant is consistent with the seventh quadrant of protein and metabolites, i.e. a positive correlation, and the first quadrant is the differential expression pattern of protein and metabolites, i.e., a negative correlation.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-4597888/v1/177982cb344baca63c26a0e4.png"},{"id":60492408,"identity":"9ef8f811-7076-42eb-b7cb-876aaa44bd70","added_by":"auto","created_at":"2024-07-17 10:59:23","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":2499699,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Identified peptides: number of peptide sequences resolved by the matching result. Identified proteins: number of proteins resolved by the specific peptides. (B) The protein quantitative PCA of the samples is shown, and the degree of aggregation between samples represents the size of the sample difference.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-4597888/v1/a637ed0cd7b29eb2d4196b7c.png"}],"financialInterests":"","formattedTitle":"Postoperative cognitive dysfunction in aged mice after sevoflurane inhalation: crosstalk of gut microbiota, metabolomics, and proteomics","fulltext":[{"header":"Highlights","content":"\u003cul\u003e\n \u003cli\u003eOur study applied multi-omics techniques to perform a joint analysis of multiple biological samples to explore the mechanism of sevoflurane-induced postoperative cognitive dysfunction.\u003c/li\u003e\n \u003cli\u003eSignificant changes in microorganisms, proteins, and metabolites were detected in the faecal, serum, and hippocampal samples of\u0026nbsp;aged mice\u0026nbsp;with POCD induced by sevoflurane\u0026nbsp;inhalation.\u003c/li\u003e\n \u003cli\u003eThese findings provide new insights into the mechanisms of POCD.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003ePostoperative cognitive dysfunction (POCD) is a common complication of anaesthesia and surgery, including mental disorders, anxiety, personality changes, and memory impairment[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Ageing and general anaesthesia, especially sevoflurane inhalation, are independent risk factors for POCD occurrence[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, the underlying mechanisms of POCD remain unclear. Evidence has shown that the high incidence of POCD in older adults may be related to an imbalance in the inflammatory response, microcirculation disturbance, microembolism formation, and abnormal activation of microglial cells[\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, therapeutic strategies targeting inflammation, improving cerebrovascular circulation, inhibiting microembolism formation, and regulating activated microglial cells have not achieved satisfactory clinical effects[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe intestinal flora is a complex microbial community in the digestive tract that maintains the essential physiological functions of the intestine by participating in metabolism and other methods[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In addition, the intestinal flora can significantly influence the nervous system through the microbe-enterobrain axis[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In recent years, an imbalance of intestinal homeostasis has been related to various neurodegenerative diseases such as depression and Parkinson's disease[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Intestinal microbial metabolites, such as short-chain fatty acids, are essential transmission vectors along the microbe-entero-brain axis[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Increasing evidence suggests that gut microbes may affect the brain and behaviour through metabolism and immunity along the gut-brain axis[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Our earlier study found that sevoflurane inhalation anaesthesia was more significantly disturbed than propofol anaesthesia[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Furthermore, we found that delayed neurocognitive recovery after surgery was related to the preoperative intestinal flora and its related metabolite composition[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, whether the intestinal flora and its metabolites are involved in developing POCD induced by sevoflurane inhalation anaesthesia is unclear.\u003c/p\u003e \u003cp\u003eStudies on the hippocampus have always been at the core of human memory research[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Multiple animal studies have shown that hippocampal gene knockout or drug anaesthesia leads to learning and memory loss. Additionally, the hippocampus is associated with cognitive function and memory impairment during ag[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Evidence has shown that neuroinflammation caused by hippocampal microglial activation plays a crucial role in the pathogenesis of POCD[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Some studies attempted to apply proteomic and metabolomic techniques to study the mechanism of POCD, but there still needs to be more relevant studies based on multi-omics combined analysis[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study used multi-omics technology to analyse various biological samples jointly. Further, using bioinformatics technology, we explored the mechanism of postoperative cognitive dysfunction caused by sevoflurane inhalation in multiple dimensions to provide new intervention targets for its prevention and treatment.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAnimals\u003c/h2\u003e \u003cp\u003eForty 16-month-old C57BL/6J male mice (40\u0026ndash;50 g) were used in this experiment, provided by Jiangsu Wukong Biotechnology Co., LTD. According to the water maze behaviour experiment, sixteen-month-old mice anaesthetised with sevoflurane were divided into POCD and NCD (none cognitive dysfunction) groups. The mice were kept in standard cages on alternating 12 h light/dark cycles and were fed and watered ad libitum. This study was approved by the Ethics Committee of Harbin Medical University Cancer Hospital (Ethical Approval: KY2022\u0026thinsp;\u0026minus;\u0026thinsp;03) and complied with the Guide for the Care and Use of Laboratory Animals.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSevoflurane inhalation anaesthesia management\u003c/h2\u003e \u003cp\u003eThe experimental mice were anaesthetised after seven days of adaptive rearing, as described in the experimental flowchart (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). They were placed in an anaesthesia box and connected to an animal anaesthesia machine to continuously deliver sevoflurane at 5 L.min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for 4 hours. The gas flow rate is continuously monitored and adjusted to maintain an oxygen concentration of 20% and a stable MAC(minimum alveolar concentration) value of 1.3, equivalent to 2.21% sevoflurane. A heating blanket was used to maintain the average body temperature(37\u0026deg;C\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u0026deg;C) during sevoflurane inhalation anaesthesia, and the rectal temperature of mice was measured at 30-minute intervals. Moreover, the animals were continuously monitored for spontaneous breathing. After sevoflurane inhalation, the mice were fully awakened and returned to their cages.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMorris water maze test\u003c/h2\u003e \u003cp\u003eThe Morris water maze is often used to assess the spatial learning and memory function in rodents, which is divided into three parts: visual platform test, positioning navigation test, and spatial exploration test. A circular pool of 120 cm in diameter and 50 cm in height was divided into four quadrants. Place a 10 cm diameter white platform within the target quadrant. Data was recorded using a digital camera over a circular sink. Before intervention, the platform was placed 1cm above the water surface, and mice with visual and swimming impairments were excluded by a visual plateau test. On the third to sixth day after intervention, the white platform was concealed 1cm below the water surface for the positioning navigation test. Mice were allowed to swim and discover the hidden platform for 60 seconds. When the mice reached the platform, they were allowed to stay on it for 3 s, recording the time to find the hidden platform (to escape the latency period). On the seventh day, the platform was removed, and the mice were allowed to swim by themselves in the pool for the 60s. The number of locations across the original platform and the duration in the target quadrant were recorded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSamples collection\u003c/h2\u003e \u003cp\u003eFaecal samples were collected simultaneously on day one before the intervention and on days 1, 3, and 7 after and labelled S0, S1, S3, and S7, respectively. Mice were placed on sterile gauze in the laboratory\u0026rsquo;s centre of the operating table. Samples were collected in sterile freezer tubes with sterile cotton swabs immediately after the mice defecation were observed, labelled and stored in a -80℃ refrigerator.\u003c/p\u003e \u003cp\u003eSerum and hippocampal specimens were collected on the seventh day after sevoflurane inhalation. Blood was collected from vessels without anticoagulant and precipitated at 37 ℃ for 60 min. The supernatant (serum) was obtained by centrifugation at 3000 rpm for 10 min at 4 ℃. The mice were then killed. The brain tissue was isolated, and the hippocampal tissue was isolated in frozen phosphate-buffered saline (PBS) solution. All samples were collected in sterile freeze-storage tubes, labelled, and stored in a -80 ℃ refrigerator.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eMicrobiome analysis\u003c/h2\u003e \u003cp\u003eDNA was extracted using a DNA extraction kit (Thermo Fisher Scientific, MA, USA) for the corresponding sample. The length and concentration of the polymerase chain reaction (PCR) products were determined using 1% agarose gel electrophoresis. Samples with bright main strips were used for further experiments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMetabolomics analysis\u003c/h2\u003e \u003cp\u003eThe sample stored in a -80\u0026deg;C refrigerator was thawed on ice. The sample was sonicated in an ice bath for 10 min and vortexed for 1 min. It was then placed in -20\u0026deg;C of ice for 30 min. After placing on ice for 15 min, the sample was centrifuged at 12000 rpm for 10 min (4\u0026deg;C). Exactly 300 \u0026micro;L of the supernatant was collected and placed in -20\u0026deg;C ice for 30 min. The sample was centrifuged at 12000 rpm for 3 min (4\u0026deg;C). Then, 200 \u0026micro;L aliquots of the supernatant were transferred for liquid chromatograph mass spectrometer (LC-MS) analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eProteomics analysis\u003c/h2\u003e \u003cp\u003eThe sample was ground with liquid nitrogen into a cell powder and then transferred to a 5 mL centrifuge tube. After that, four volumes of lysis buffer (8 M urea, 1% protease inhibitor cocktail) were added to the cell powder, followed by sonication thrice on ice using a high-intensity ultrasonic processor (Scientz).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eOTU (operational taxonomic units) was one of the most common terms in microbiology. The differences between groups were analysed by alpha diversity index using R software. Beta diversity analysis was used to evaluate differences of samples in species complexity through 9 algorithms, including bray_curtis, Euclidean, abund_jaccard, Canberra, chisq, chord, Gower, weighted_unifrac and unweighted_unifrac by R software. LDA Effect Size(LEfSe) analyses were used to find the biomarker of each group based on homogeneous OTU_table. Unsupervised PCA (principal component analysis) was performed by statistics function prcomp within R (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.r-project.org\" target=\"_blank\"\u003ewww.r-project.org\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.r-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The HCA (hierarchical cluster analysis) results of samples and metabolites were presented as heatmaps with dendrograms. In contrast, Pearson correlation coefficients (PCC) between samples were calculated by the cor function in R and presented as only heatmaps. For two-group analysis, differential metabolites were determined by VIP (VIP\u0026thinsp;\u0026ge;\u0026thinsp;1) and absolute Log2FC (|Log2FC| \u0026ge; 1.0). VIP values were extracted from the OPLS-DA result, which contains score and permutation plots and was generated using the R package MetaboAnalystR. KEGG connects general information on molecular interaction networks, such as pathways and complexes, genes and proteins generated by genome projects, and biochemical compounds and reactions. It was, firstly, using KEGG online service tool KAAS to annotate the protein's KEGG database description. Then mapping, the annotation result on the KEGG pathway database using KEGG online service tool KEGG mapper.\u003c/p\u003e \u003cp\u003eThe escape latency of training, the number of platform crossings, and the duration within the target quadrant on the last day were used for hierarchical clustering analysis. Cluster analysis using SPSS21.0 divided the mice into the POCD and NCD groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In this study, the Cast expression of the subjects was used as the primary outcome measure, and the Cast expression in the NCD group was 931.39\u0026thinsp;\u0026plusmn;\u0026thinsp;283.01, and in the POCD group was 474.35\u0026thinsp;\u0026plusmn;\u0026thinsp;59.09, setting two-sided α\u0026thinsp;=\u0026thinsp;0.05, and the confidence was 90%. The sample size was N1\u0026thinsp;=\u0026thinsp;6 for the POCD group and N2\u0026thinsp;=\u0026thinsp;6 for the NCD group, with at least 12 experimental animals. The chi-square test and variable analysis assessed the significance of continuous variables consistent with a normal distribution. Statistical significance was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eMorris water maze test results between the POCD and NCD groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Morris water maze test (MWMT) was used to assess cognitive behaviour\u0026nbsp;in the mice.\u0026nbsp;Mice\u0026nbsp;were classified\u0026nbsp;into the\u0026nbsp;POCD and NCD groups\u0026nbsp;by\u0026nbsp;hierarchical clustering analysis based on escape latency, platform crossing\u0026nbsp;times, and time spent in the target quadrant\u0026nbsp;in the water maze(Fig 2).\u0026nbsp;The two groups had\u0026nbsp;no significant differences in body weight\u0026nbsp;or swimming speed. Moreover, mice in the POCD group showed\u0026nbsp;a\u0026nbsp;significantly increased escape latency and significantly reduced platform crossings and\u0026nbsp;time\u0026nbsp;spent in the target quadrant (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMicrobiome analysis of faecal samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Venn diagram (Fig\u0026nbsp;3A) shows 693\u0026nbsp;standard\u0026nbsp;operational taxonomic units (OTU) in the eight groups. In addition, the number of specific OTUs in the POCD and NCD groups tended to\u0026nbsp;increase\u0026nbsp;and decrease at S0, S1, and S3. The number of specific OTUs was almost similar between the NS7 and NS0 groups, whereas that in the PS7 group was significantly lower compared to the PS0 group. This indicates that the POCD group had the same dynamic trend as the NCD group during the three days\u0026nbsp;of sevoflurane inhalation. The number of OTUs in the NCD group returned to pre-intervention\u0026nbsp;levels on the seventh day after the\u0026nbsp;intervention,\u0026nbsp;whereas\u0026nbsp;that in\u0026nbsp;the POCD group decreased significantly after the seventh day.\u003c/p\u003e\n\u003cp\u003eFor alpha diversity, the Chao1 index showed no significant difference between the PS0, PS1, PS3, and PS7 groups (P\u0026gt; 0.05) (Fig\u0026nbsp;3B), and there was no significant difference between the NS0, NS1, NS3, and NS7 groups (P\u0026gt; 0.05) (Fig\u0026nbsp;3C). This indicates\u0026nbsp;a slight\u0026nbsp;variation in species richness and microbial community diversity\u0026nbsp;between the POCD and NCD groups. For beta diversity, the unweighted UniFrac algorithm was used to analyse the differences among the groups using principal coordinate analysis (PCoA). The results showed that\u0026nbsp;the PS0-PS1 (P=0.615) and PS1-PS3 (P=0.127) groups clustered significantly, indicating that the microbial species composition of the POCD group changed little within\u0026nbsp;three days after\u0026nbsp;intervention. However, the PCoA results showed that\u0026nbsp;the\u0026nbsp;PS7-PS0 (P=0.048), PS7-PS1 (P=0.015),\u0026nbsp;and PS7-PS3 (P=0.021) groups\u0026nbsp;were significantly isolated, indicating that the microbial species composition of\u0026nbsp;the POCD group changed significantly on the seventh day after the intervention (Fig\u0026nbsp;3D).\u0026nbsp;In the NCD group, NS0-NS1 (P=0.306), NS1-NS3 (P=0.313) and NS3-NS7 (P=0.289) were significantly clustered, and only the NS0-NS7 group was significantly separated (P=0.026) (Fig\u0026nbsp;3E). Therefore, based on the significant aggregation in\u0026nbsp;the\u0026nbsp;PS0-NS0 group (P=0.438), the microbial differences in the PS7-PS0 group and NS7-NS0 group\u0026nbsp;were noteworthy, which may have been due to microbial differences between\u0026nbsp;the POCD and NCD groups (Fig\u0026nbsp;3F-H).\u003c/p\u003e\n\u003cp\u003eTable 2 shows the differential microorganisms between the groups (PS7-PS0 and NS7-NS0), with 40 differences in the PS7-PS0 group and 27 differences in the NS7-NS0 group. At the genus level, Butyrivibrio and Candidatus_Saccharimonas were co-enriched in the PS0 and NS0 groups but not in the PS7 and NS7 groups. The anaesthetic intervention may have affected the POCD and NCD groups. In addition, Odoribacter, Ohtaekwangia, Conexibacter, and the CL500_29_marine_group were not significantly different in the PS0-NS0 and NS7-NS0 groups but were significantly different in the PS7-PS0 group. Odoribacter, Ohtaekwangia, and CL500_29_marine_group were enriched in the PS0 group, and Conexibacter was significantly enriched in the PS7 group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMetabolomics analysis of the faecal samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of the principal component analysis showed a significant separation of the NS0-NS1 group samples and the relative aggregation of the NS1-NS3 and NS3-NS7 groups (Fig 4A-C). In contrast, the PS0-PS1, PS1-PS3, and PS3-PS7 groups were relatively significantly separated (Fig 4D-F). This indicates that the metabolites in the NCD group changed only considerably within one day after intervention and changed less from the first day to the seventh day after intervention. The POCD group continued to change significantly during the seven days after intervention, and the most significant change occurred between days one and three after intervention. Volcano maps showed the distribution of differential metabolites between the POCD and NCD groups (Fig 4G-L). The differential metabolites in the NS0-NS1, NS1-NS3, and NS3-NS7 groups were 43, 9, and four, respectively. The numbers of differential metabolites in the PS0-PS1, PS1-PS3, and PS3-PS7 groups were 24, 42, and 23, respectively. We found that some differential metabolites showed continuous changes; for example, the 3,4-dihydroxyphenylacetate content continuously decreased in the first three days in the NCD group, showing an upward trend from the third day to the seventh day, and returned to pre-intervention levels. Conversely, its content first increased and then decreased in the POCD group and was significantly lower than the pre-intervention level. We brought the differential metabolites into an authoritative metabolite database, such as the Kyoto Encyclopedia of Genes and Genomes (KEGG), for search and metabolic pathway analysis, which was reflected as a bubble map[21]. We found that caffeine metabolism was the only metabolic pathway jointly enriched for the differential metabolites between the POCD and NCD groups in the hippocampal, serum, and faecal samples.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMetabolomics analysis of serum samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe orthogonal partial least squares-discriminant analysis (OPLS-DA) results showed that the samples were significantly separated between the POCD-NCD\u0026nbsp;and NCD groups (Fig\u0026nbsp;5A). The differential metabolite screening conditions were:\u0026nbsp;variable\u0026nbsp;importance in\u0026nbsp;projection (VIP)\u0026nbsp;\u0026gt;1 with a\u0026nbsp;p-value \u0026lt;0.05. Fold changes \u0026gt;2 or \u0026lt;0.5\u0026nbsp;indicated significantly upregulated or significantly downregulated differential metabolites, respectively. We used volcano maps to visualise the distribution of differential metabolites in serum samples between\u0026nbsp;the POCD and NCD groups (Fig\u0026nbsp;5B).\u0026nbsp;Table 3 shows five differential metabolites, 3-methylxanthine, asn-glu, glycerol 2-phosphate, l-saccharopine, and leu-asp, were significantly upregulated. Seven differential metabolites, 4-methyl-5-thiazole-ethanol, adrenosterone, ammelide, guanosine-5\u0026apos;-monophosphate, lys-ile, taurocholic acid, and xanthosine, were significantly downregulated. KEGG pathway enrichment analysis was performed based on the differential metabolite results of\u0026nbsp;the serum samples from the POCD-NCD group. The top 20 pathways are presented\u0026nbsp;in a bubble chart (Fig\u0026nbsp;5C). Notably, the enrichment of purine and nucleotide metabolism pathways were associated with three downregulated metabolites: guanosine-5\u0026apos;-monophosphate, guanosine, and xanthosine. Moreover,\u0026nbsp;the caffeine metabolism pathway is a common metabolic pathway between\u0026nbsp;the hippocampal\u0026nbsp;and serum samples.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMetabolomic analysis of the hippocampal samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of the OPLS-DA showed that\u0026nbsp;the\u0026nbsp;samples were significantly separated between the POCD-NCD groups. Meanwhile, the metabolites in the POCD group were significantly dispersed compared\u0026nbsp;with the sample aggregation trend in the NCD group (Fig\u0026nbsp;6A). We used volcano plots to visualise the distribution of differential metabolites in\u0026nbsp;the\u0026nbsp;hippocampal samples between the POCD and NCD groups (Fig\u0026nbsp;6B).\u0026nbsp;Table 4 shows that three differential metabolites, asterina-330, hydantoin-5-propionic acid, and\u0026nbsp;val-his, were significantly upregulated.\u0026nbsp;Four differential metabolites, 1,7-dimethylxanthine, 6-methylaminopurine, l-ascorbate, and theophylline, were significantly downregulated. The results showed that\u0026nbsp;14 metabolic pathways\u0026nbsp;were enriched, including the caffeine metabolism and HIF-1 signalling pathways(Fig\u0026nbsp;6C). Among these, the enrichment of the caffeine metabolism pathway was associated with two downregulated metabolites: 1,7-dimethylxanthine and theophylline.\u0026nbsp;A\u0026nbsp;combined proteomics-metabolomic analysis was performed\u0026nbsp;to\u0026nbsp;explorewhether there is a common pathway between differentially expressed proteins and metabolites. Pearson\u0026apos;s correlation analysis was performed with a correlation coefficient \u0026gt;0.80 and a p-value \u0026lt;0.05. Fig\u0026nbsp;6D\u0026nbsp;shows that\u0026nbsp;11 metabolites were significantly associated with 12 proteins. Among them, the differential metabolites 1,7-dimethylxanthine and theophylline, showed a significant positive correlation with calpastatin.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProteomics analysis of the hippocampal samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExactly 7,746 proteins were identified in the 12 hippocampal samples, of which 6,780 were quantifiable (Fig 7A). The principal component analysis (PCA) results showed significant differences between the two groups of hippocampal samples (Fig 7B). To identify the proteins involved in POCD, we compared the differential protein expression between the POCD and NCD groups in the hippocampal samples. When the p-value was \u0026lt;0.05, a fold change above 1.5 indicated significant upregulation and a fold change less than 1/1.5 indicated significant downregulation. The results showed that 34 proteins were differentially expressed in the hippocampal samples, including 12 upregulated and 22 downregulated proteins. Detailed information on the differentially expressed proteins between the POCD and NCD groups, including protein accession, corresponding gene names, fold changes, p-values, regulatory type, and subcellular localisation, is presented in Table 5.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study applied multi-omics techniques to perform a joint analysis of multiple biological samples to explore the mechanism of sevoflurane-induced postoperative cognitive dysfunction. The results showed that compared with the non-POCD group, significant changes in microorganisms, proteins, and metabolites were detected in the stool, serum, and hippocampal samples of aged mice with POCD, and there was a correlation among the three groups of samples.\u003c/p\u003e \u003cp\u003eCompared with the non-POCD group, the intestinal microorganisms of the Ohtaekwangia, Odoribacter, and CLB500_29 marine groups were significantly downregulated in aged mice with POCD. Ohtaekwangia and Odoribacter were significantly and positively correlated with the faecal metabolite guanosine-5-monophosphate. Meanwhile, guanosine-5-monophosphate was also downregulated in serum samples of aged mice with POCD; guanosine-5-monophosphate showed the same downward trend in faecal and serum samples. In addition, xanthosine, an intermediate of purine metabolism and an upstream substrate of caffeine metabolism was significantly downregulated in the serum of aged mice with POCD. Studies have shown that caffeine metabolites, such as theophylline and theobromine, are associated with neurodegenerative diseases such as Alzheimer's and Parkinson's diseases[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our study, 1,7-dimethylxanthine, a caffeine metabolite, was associated with POCD development. 1,7-dimethylxanthine is a metabolite significantly downregulated in the hippocampus of aged mice with POCD, suggesting that 1,7-dimethylxanthine (paraxanthine) may be a key factor in exerting anti-sevoflurane anaesthesia-induced POCD. 1,7-dimethylxanthine is an adenosine A2A receptor antagonist. It has been shown that overexpression of the adenosine A2A receptor can be activated by the Gs-AC-cAMP pathway and then facilitate GSK-3β to promote tau hyperphosphorylation[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In addition, 1,7-dimethylxanthine in the hippocampus of POCD mice was found to be significantly and positively correlated with calpastatin, and calpastatin expression was downregulated. Calpastatin is an intrinsically unstructured protein that reversibly binds to and inhibits calpain[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Several studies have shown that the overexpression of calpastatin has a protective effect on neurons and slows the occurrence of degenerative diseases, such as Alzheimer's disease and Huntington's disease[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Our study is the first to find an association between calpastatin and POCD. The overexpression of calpain cleaves and activates GSK-3β, phosphorylating tau, leading to neurodegenerative diseases[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In addition, calpain can cleave p35 into p25, and the p25 generated over-activates cyclin-dependent kinase 5 (CDK5), leading to the intracellular accumulation of the microtubule-associated protein tau, which is related to the occurrence and development of neurodegeneration[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The tau protein is a cytoskeletal protein whose abnormal accumulation in cells damages learning and memory function, and its hyperphosphorylation is involved in the pathogenesis of various progressive neurological diseases[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. There is a common signalling pathway (GSK-3β signalling pathway) between 1,7-dimethylxanthine and calpastatin in the mechanism of tau hyperphosphorylation mediating sevoflurane anaesthesia induced-POCD. Therefore, it is reasonable to speculate that the metabolite, 1,7-dimethylxanthine, activates calpastatin to reduce tau hyperphosphorylation mediated by GSK-3β and CDK5 signalling pathways, thereby alleviating POCD caused by sevoflurane anaesthesia.\u003c/p\u003e \u003cp\u003eThe neurophysiological basis of learning and memory includes long-term potentiation (LTP) and long-term depression (LTD), representing enhanced and decreased synaptic functional strength. Interestingly, we found that both adenosine A2A receptor and calpain can affect LTP and LTD indirectly by affecting synaptic function. The mechanism of LTP occurrence lies in the activation of the ERK signalling pathway by multiple pathways, while LTD lies in the activation of the PKC pathway. LTP and LTD differ because four pathways mediate calcium (glutamate receptor, voltage-gated calcium channel, NMDA receptor, and sodium exchange channel)[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In contrast to LTD, NDMAR is a unique receptor in the LTP pathway, resulting in significantly higher intracellular calcium concentration in LTP cells[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In LTD cells, low concentrations of calcium ions are highly susceptible to activating phosphatases, namely PKC. Overexpression of calpain-2 inhibited the ERK pathway, which in turn terminated LTP[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This makes us believe that calpastatin downregulation causing overexpression of calpain, plays a crucial role in the development of POCD. In addition, studies have shown that although adenosine A2A receptors play an active role in the regulation of LTP and memory in the hippocampus, ageing or overactivation of adenosine A2A receptors can trigger harmful synaptic effects that lead to LTP to LTD transition and reduce hippocampal-dependent learning and memory processes[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This confirms the role of the down-regulated metabolite 1,7 dimethylxanthine and the low-expressed protein calpastatin in POCD. Therefore, we speculate that the down-regulation of 1,7 dimethylxanthine and the low expression of calpastatin leads to the hyperactivation of adenosine A2A receptor and calpain, respectively, both involved in the occurrence of LTD, leading to the impairment of hippocampal learning and cognitive function.\u003c/p\u003e \u003cp\u003eOur study had some limitations. First, because human hippocampal tissue is challenging to obtain, we only used old mice to explore the mechanism of POCD. Second, We did not verify the differential bacterial flora, metabolites and proteins in the occurrence of POCD caused by sevoflurane anesthesia, which is included in our next research plan.\u003c/p\u003e \u003cp\u003eSignificant changes in microorganisms, proteins, and metabolites were detected in mice\u0026rsquo;s faecal, serum, and hippocampal samples with POCD induced by sevoflurane anaesthesia. Moreover, there was a correlation between the three samples. These findings provide new insights into the mechanisms of POCD.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHCA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehierarchical cluster analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKEGG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKyoto Encyclopedia of Genes and Genomes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLC-MS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eliquid chromatograph mass spectrometer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLTD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elong-term depression\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLTP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elong-term potentiation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMAC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eminimum alveolar concentration\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMWMT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThe Morris water maze test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNCD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enone cognitive dysfunction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOPLS-DA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThe orthogonal partial least squares-discriminant analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOTU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eoperational taxonomic units\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ephosphate-buffered saline\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprincipal component analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePearson correlation coefficients\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePOCD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epostoperative cognitive dysfunction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVIP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003evariable importance in projection\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupported by the Outstanding Youth Project Foundation of Harbin Medical University Cancer Hospital (JCQN2021-05), Haiyan Research Foundation of Harbin Medical University Cancer Hospital (JJZD2022-04), and the Natural Science Foundation of Heilongjiang Province (JJ2020YX0472).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere are no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuther contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZDZ, CSW, and XTQ designed this work. XTQ wrote the manuscript. XTQ, HPL, HXL, YX and YXZ performed the experiments. XTQ and HYL, ZKD analyzed the data. JYL, SFW, MQL, XYZ and XQY reviewed and edited the manuscript. All authors approved the present version of the manuscript and agreed to be accountable for all aspects of the work, including any questions related to the accuracy or integrity of any part of the work.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are not publicly available due to [REASON(S) WHY DATA ARE NOT PUBLIC] but are available from the corresponding author on reasonable request.].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Harbin Medical University Cancer Hospital (Ethical Approval: KY2022\u0026minus;03) and complied with the Guide for the Care and Use of Laboratory Animals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research receives no specific grant from funding agencies in the public, commercial, or not-for-profit sectors. All authors have read and understood your journal\u0026rsquo;s policies and believe that neither the manuscript nor the study violates any of these. There are no conflicts of interest to declare.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLuo AL et al (2019) Postoperative cognitive dysfunction in the aged: the collision of neuroinflammaging with perioperative neuroinflammation. INFLAMMOPHARMACOLOGY (Suppl 1)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhushan S et al (2021) Progress of research in postoperative cognitive dysfunction in cardiac surgery patients: A review article. Int J Surg 95:106163\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang CM et al (2021) Update on the Mechanism and Treatment of Sevoflurane-Induced Postoperative Cognitive Dysfunction. 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Med Res Rev 39(2):608\u0026ndash;630\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaudry M, Bi X (2016) Calpain-1 and Calpain-2: The Yin and Yang of Synaptic Plasticity and Neurodegeneration. Trends Neurosci 39(4):235\u0026ndash;245\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu Z et al (2023) Do tau-synaptic long-term depression interactions in the hippocampus play a pivotal role in the progression of Alzheimer's disease. Neural Regen Res 18(6):1213\u0026ndash;1219\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZuo CL et al (2018) Isoflurane anesthesia in aged mice and effects of A1 adenosine receptors on cognitive impairment. CNS Neurosci Ther 24(3):212\u0026ndash;221\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMalenka RC, Bear MF (2004) LTP and LTD: an embarrassment of riches. Neuron 44(1):5\u0026ndash;21\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArtola A, Singer W (1993) Long-term depression of excitatory synaptic transmission and its relationship to long. 16(11):480\u0026ndash;487\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGessi S et al (2021) A2A Adenosine Receptor as a Potential Biomarker and a Possible Therapeutic Target in Alzheimer's Disease. Cells 10(9)\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Characteristics of the animals\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"567\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics of the animals\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.40282685512368%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.434628975265017%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ePOCD Group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.024734982332156%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eNCD Group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.137809187279153%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.40282685512368%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eBody weight (g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.434628975265017%\" valign=\"bottom\"\u003e\n \u003cp\u003e42.87\u0026plusmn;5.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.024734982332156%\" valign=\"bottom\"\u003e\n \u003cp\u003e44.90\u0026plusmn;7.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.137809187279153%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.40282685512368%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSwimming speed\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003em/s\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.434628975265017%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.10\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.024734982332156%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.12\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.137809187279153%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.476\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.40282685512368%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eEscape latency (s)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.434628975265017%\" valign=\"bottom\"\u003e\n \u003cp\u003e42.68\u0026plusmn;13.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.024734982332156%\" valign=\"bottom\"\u003e\n \u003cp\u003e5.02\u0026plusmn;0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.137809187279153%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.40282685512368%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlatform crossing\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.434628975265017%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.67\u0026plusmn;0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.024734982332156%\" valign=\"bottom\"\u003e\n \u003cp\u003e5.67\u0026plusmn;1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.137809187279153%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.40282685512368%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime spent in the target quadrant (s)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.434628975265017%\" valign=\"bottom\"\u003e\n \u003cp\u003e16.57\u0026plusmn;7.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.024734982332156%\" valign=\"bottom\"\u003e\n \u003cp\u003e36.92\u0026plusmn;3.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.137809187279153%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eSignificant comparison results of differences in body weight, swimming speed, escape latency, number of platform crossing, and time spent in the target quadrant between the NCD and POCD groups. P \u0026lt;0.05 indicates statistically significant differences.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eDifferential microorganisms in faecal samples\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"690\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003e\u003cstrong\u003ebiomarker ID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLDA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003ef_Ilumatobacteraceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.553522144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.036048708\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_CL500_29_marine_group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.554559091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.036048708\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003es_metagenome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.546063594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.036048708\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_Enterorhabdus.uncultured_bacterium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.073131945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.016309172\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003ec_Thermoleophilia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.485439346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.037040731\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eo_Solirubrobacterales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.485439346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.037040731\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003ef_Solirubrobacteraceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.450206679\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.022486683\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_Conexibacter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.582288204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.022229618\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003ef_Marinifilaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.971636472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.016309172\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_Odoribacter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.972239408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.016309172\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003ef_Rikenellaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e4.281527705\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.037372988\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_Alistipes.uncultured_bacterium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.509221225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.01040562\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_Rikenellaceae_RC9_gut_group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e4.104646262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.037372988\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_Rikenellaceae_RC9_gut_group.uncultured_bacterium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e4.104646262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.037372988\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003ef_Microscillaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.66832202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.022229618\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_Ohtaekwangia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.670305613\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.022229618\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003ec_Anaerolineae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.059196505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.037372988\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eo_RBG_13_54_9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.072388399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.005587505\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003ep_Firmicutes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e4.912249244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_Defluviitaleaceae_UCG_011.uncultured_bacterium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.462890711\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.022229618\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003ef_Lachnospiraceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e4.407837846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.037372988\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_Butyrivibrio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.370240017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_Butyrivibrio.uncultured_bacterium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.370240017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_Lachnospiraceae_NK4A136_group.uncultured_bacterium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e4.023009383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.037372988\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_Lachnospiraceae_UCG_004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.329031988\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.036048708\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_Lachnospiraceae_UCG_004.uncultured_bacterium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.319621663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.036048708\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003ef_Ruminococcaceae.uncultured\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.303382901\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003ep_Patescibacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e4.554204037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.01040562\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eo_Saccharimonadia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e4.554226607\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.01040562\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003ef_Saccharimonadales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e4.554226607\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.01040562\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_Saccharimonadaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e4.554122062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.01040562\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_Candidatus_Saccharimonas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e4.554122062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.01040562\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_Candidatus_Saccharimonas.uncultured_bacterium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e4.578665051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.01040562\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eo_Micavibrionales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.217512761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.046319841\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eo_Micavibrionales.uncultured\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.21888866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.046319841\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003ef_Hyphomicrobiaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.048603048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.023968274\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003ef_Desulfovibrionaceae.uncultured\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.792295384\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.003947752\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003ef_Desulfovibrionaceae.uncultured.uncultured_bacterium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.787585717\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.003947752\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003ec_Gammaproteobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e4.190561275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.01040562\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.666666666666664%\"\u003e\n \u003cp\u003eg_966_1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.594202898550725%\"\u003e\n \u003cp\u003ePS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.797101449275363%\"\u003e\n \u003cp\u003e3.856100637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\"\u003e\n \u003cp\u003e0.049336176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"688\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003eg_Butyrivibrio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.541786514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003eg_Butyrivibrio.uncultured_bacterium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.541786514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003eg_Tyzzerella_3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.205501216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.022229618\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003eg_Tyzzerella_3.uncultured_bacterium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.205075096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.022229618\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003eg_Ruminiclostridium_6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.548603119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.01040562\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003eg_Ruminiclostridium_6.uncultured_bacterium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.548603119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.01040562\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003ep_Nitrospirae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.036479554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003ec_Nitrospira\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.036479554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003eo_Nitrospirales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.036479554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003ef_Nitrospiraceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.036479554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003eg_Nitrospira\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.036479554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003ep_Patescibacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e4.49069674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003ec_Saccharimonadia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e4.490737375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003eo_Saccharimonadales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e4.490737375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003ef_Saccharimonadaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e4.490759623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003eg_Candidatus_Saccharimonas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e4.490759623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003eg_Candidatus_Saccharimonas.uncultured_bacterium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e4.466910366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.024974679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003ep_Planctomycetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.061987175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.013195103\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003ec_Planctomycetacia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.075370776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.049510167\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003eo_Gemmatales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.427979079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.022229618\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003ef_Gemmataceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.42615159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.022229618\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003ef_Gemmataceae.uncultured\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.427332997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.022229618\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003ef_Gemmataceae.uncultured.uncultured_bacterium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.429701721\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.022229618\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003eg_Rhodoplanes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.330347491\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.022229618\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003ef_Nitrosomonadaceae.966_1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.430297423\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.022229618\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003ef_SC_I_84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e3.696940915\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.021025213\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.83139534883721%\"\u003e\n \u003cp\u003eg_Escherichia_Shigella\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.773255813953488%\"\u003e\n \u003cp\u003eNS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e4.504038153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.69767441860465%\"\u003e\n \u003cp\u003e0.037372988\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eDetailed information on differential microorganisms in faecal samples. The criteria for differential microorganisms were LDA \u0026gt; 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eDifferential metabolites in serum samples\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"709\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.348377997179124%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFormula\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.067700987306065%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCompounds\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eVIP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.963328631875882%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFold_Change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eLog2FC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eType\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.348377997179124%\" valign=\"bottom\"\u003e\n \u003cp\u003eC6H6N4O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.067700987306065%\" valign=\"bottom\"\u003e\n \u003cp\u003e3-Methylxanthine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.972\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.009\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.963328631875882%\" valign=\"bottom\"\u003e\n \u003cp\u003e803.310\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e9.650\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.348377997179124%\" valign=\"bottom\"\u003e\n \u003cp\u003eC9H15N3O6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.067700987306065%\" valign=\"bottom\"\u003e\n \u003cp\u003eAsn-Glu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.975\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.002\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.963328631875882%\" valign=\"bottom\"\u003e\n \u003cp\u003e832.221\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e9.701\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.348377997179124%\" valign=\"bottom\"\u003e\n \u003cp\u003eC3H9O6P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.067700987306065%\" valign=\"bottom\"\u003e\n \u003cp\u003eGlucerol 2-phosphate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.142\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.044\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.963328631875882%\" valign=\"bottom\"\u003e\n \u003cp\u003e367.972\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e8.523\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.348377997179124%\" valign=\"bottom\"\u003e\n \u003cp\u003eC11H20N2O6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.067700987306065%\" valign=\"bottom\"\u003e\n \u003cp\u003eL-Saccharopine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.970\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.005\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.963328631875882%\" valign=\"bottom\"\u003e\n \u003cp\u003e6202.677\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e12.599\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.348377997179124%\" valign=\"bottom\"\u003e\n \u003cp\u003eC10H18N2O5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.067700987306065%\" valign=\"bottom\"\u003e\n \u003cp\u003eLeu-Asp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.971\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.003\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.963328631875882%\" valign=\"bottom\"\u003e\n \u003cp\u003e705.573\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e9.463\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.348377997179124%\" valign=\"bottom\"\u003e\n \u003cp\u003eC6H9NOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.067700987306065%\" valign=\"bottom\"\u003e\n \u003cp\u003e4-methyl-5-thiazole-ethanol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.928\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.037\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.963328631875882%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.001\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e-9.754\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.348377997179124%\" valign=\"bottom\"\u003e\n \u003cp\u003eC19H24O3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.067700987306065%\" valign=\"bottom\"\u003e\n \u003cp\u003eAdrenosterone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.952\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.012\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.963328631875882%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.002\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e-9.099\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.348377997179124%\" valign=\"bottom\"\u003e\n \u003cp\u003eC3H4N4O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.067700987306065%\" valign=\"bottom\"\u003e\n \u003cp\u003eAmmelide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.966\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.004\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.963328631875882%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.002\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e-9.337\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.348377997179124%\" valign=\"bottom\"\u003e\n \u003cp\u003eC10H14N5O8P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.067700987306065%\" valign=\"bottom\"\u003e\n \u003cp\u003eGuanosine-5\u0026apos;-monophosphate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.966\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.008\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.963328631875882%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.002\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e-8.928\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.348377997179124%\" valign=\"bottom\"\u003e\n \u003cp\u003eC12H25N3O3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.067700987306065%\" valign=\"bottom\"\u003e\n \u003cp\u003eLys-Ile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.969\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.036\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.963328631875882%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.389\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.360\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.348377997179124%\" valign=\"bottom\"\u003e\n \u003cp\u003eC26H45NO7S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.067700987306065%\" valign=\"bottom\"\u003e\n \u003cp\u003eTaurocholic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.106\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.015\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.963328631875882%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.456\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.132\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.348377997179124%\" valign=\"bottom\"\u003e\n \u003cp\u003eC10H12N4O6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.067700987306065%\" valign=\"bottom\"\u003e\n \u003cp\u003eXanthosine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.964\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.017\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.963328631875882%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.318\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.653\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.155148095909732%\" valign=\"bottom\"\u003e\n \u003cp\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003eDetailed information on differential metabolites between the POCD versus NCD groups in serum samples. Differential metabolite screening conditions were VIP\u0026gt; 1 with a P-value \u0026lt;0.05. Fold change\u0026gt; 2 or \u0026lt;0.5 were significantly upregulated or significantly downregulated differential metabolites, respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eDifferential metabolites in hippocampal samples\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"689\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.9811320754717%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFormula\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.850507982583455%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCompounds\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eVIP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.368650217706822%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFold_Change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eLog2FC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eType\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.9811320754717%\" valign=\"bottom\"\u003e\n \u003cp\u003eC12H20N2O6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.850507982583455%\" valign=\"bottom\"\u003e\n \u003cp\u003eAsterina-330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.312\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.368650217706822%\" valign=\"bottom\"\u003e\n \u003cp\u003e3636.850\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e11.828\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.9811320754717%\" valign=\"bottom\"\u003e\n \u003cp\u003eC6H8N2O4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.850507982583455%\" valign=\"bottom\"\u003e\n \u003cp\u003eHydantoin-5-propionic acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.308\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.003\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.368650217706822%\" valign=\"bottom\"\u003e\n \u003cp\u003e521.877\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e9.028\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.9811320754717%\" valign=\"bottom\"\u003e\n \u003cp\u003eC11H18N4O3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.850507982583455%\" valign=\"bottom\"\u003e\n \u003cp\u003eVal-His\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.302\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.003\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.368650217706822%\" valign=\"bottom\"\u003e\n \u003cp\u003e759.084\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e9.568\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003eup\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.9811320754717%\" valign=\"bottom\"\u003e\n \u003cp\u003eC7H8N4O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.850507982583455%\" valign=\"bottom\"\u003e\n \u003cp\u003e1,7-Dimethylxanthine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.422\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.013\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.368650217706822%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.465\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.105\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.9811320754717%\" valign=\"bottom\"\u003e\n \u003cp\u003eC6H7N5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.850507982583455%\" valign=\"bottom\"\u003e\n \u003cp\u003e6-Methylaminopurine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.250\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.013\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.368650217706822%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.003\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e-8.168\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.9811320754717%\" valign=\"bottom\"\u003e\n \u003cp\u003eC6H8O6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.850507982583455%\" valign=\"bottom\"\u003e\n \u003cp\u003eL-Ascorbate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.840\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.005\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.368650217706822%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e-16.783\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.9811320754717%\" valign=\"bottom\"\u003e\n \u003cp\u003eC7H8N4O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.850507982583455%\" valign=\"bottom\"\u003e\n \u003cp\u003eTheophylline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.422\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.013\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.368650217706822%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.465\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.105\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.449927431059507%\" valign=\"bottom\"\u003e\n \u003cp\u003edown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4:\u0026nbsp;\u003c/strong\u003eDetailed information on differential metabolites between the POCD versus NCD groups in hippocampal samples. Differential metabolite screening conditions were VIP\u0026gt; 1 with a P-value \u0026lt;0.05. Fold change\u0026gt; 2 or \u0026lt;0.5 were significantly upregulated or significantly downregulated differential metabolites, respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u0026nbsp;\u003c/strong\u003eDifferentially expressed proteins of hippocampal samples\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eProtein accession\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eGene name\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eP/N Ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eP/N P value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRegulated Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSubcellular localisation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eP52432\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePolr1c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.582\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.045635508\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eUp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ecytoplasm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eO08601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMttp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.813\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.037428808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eUp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eendoplasmic reticulum\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ8BH73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQpctl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.588\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.046340584\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eUp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eendoplasmic reticulum\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ9EPK6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSil1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.577\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.013465678\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eUp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eextracellular\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ8JZM4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e3.262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.002038935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eUp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eextracellular\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ9WUZ9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eEntpd5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.717\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.013442506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eUp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eextracellular\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ9JMB8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCntn6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.906\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.010264835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eUp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eextracellular\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ64299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCcn3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.034414975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eUp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eextracellular\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ06770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSerpina6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.001718079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eUp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eextracellular\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eP48986\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNeurod6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.707\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.046623701\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eUp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003enucleus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ9JJG6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eTmem47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.013017069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eUp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eplasma membrane\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ8VCB1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNdc1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.001601161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eUp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eplasma membrane\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ9Z2P8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eVamp5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.021418616\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ecytoplasm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eO88843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCradd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.040237402\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ecytoplasm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ8CI33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCwf19l1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.000863387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ecytoplasm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ6Q899\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDdx58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.023261916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ecytoplasm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ6A037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eN4bp1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.602\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.031125432\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ecytoplasm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ9D6Y4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eBorcs8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.017121825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ecytoplasm, nucleus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eP24456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCyp2d10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.028771748\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eendoplasmic reticulum\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ3UPR9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSbspon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.032850969\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eextracellular\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eP27573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMpz\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.508\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.031274911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eextracellular\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ5SUC9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSco1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.003330537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003emitochondria\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ91W29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCox4i2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.032274786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003emitochondria\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eP59041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDnajc30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.507\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.002733886\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003emitochondria\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ9CPX8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eUqcr11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.587\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.044425442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003emitochondria\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ8BX02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eKank2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.535\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.025434849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003enucleus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eP48437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eProx1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.045585033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003enucleus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eP51125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.047152037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003enucleus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eP63058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eThra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.03590968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003enucleus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ3THK3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eGtf2f1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.016581782\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003enucleus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ6KCD5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNipbl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.587\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.007491123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eplasma membrane\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eP03903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMtnd4l\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.562\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.018354136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eplasma membrane\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ7TQK1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInts7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.012800196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eplasma membrane\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eQ3UEZ8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSlc10a4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.040137689\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eplasma membrane\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eDetails of the differentially expressed proteins between the POCD and NCD groups in the hippocampal samples. Fold change\u0026gt; 1.5 and P \u0026lt;0.05 were considered statistically significant.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":false,"isWithdrawnOrRetracted":false,"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},"keywords":"postoperative cognitive dysfunction, sevoflurane, hippocampus, gut-brain axis, proteomics","lastPublishedDoi":"10.21203/rs.3.rs-4597888/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4597888/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e General anaesthesia, especially sevoflurane inhalation anaesthesia, is an independent risk factor for postoperative cognitive dysfunction. However, the molecular mechanism by which sevoflurane inhalation alters postoperative cognitive function remains unclear.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e According to the water maze behaviour experiment, sixteen-month-old mice receiving sevoflurane inhalation were divided into postoperative cognitive dysfunction and none cognitive dysfunction groups. Faecal samples were collected from two groups one day before intervention and 1, 3, and 7 days after. Moreover, hippocampal and serum samples were collected seven days after intervention. Faecal samples were analysed at the microbiome and metabolomics levels. The hippocampal samples were analysed using proteomics and metabolomics. Moreover, serum samples were analysed using metabolomics. Further, bioinformatics technology was used to integrate and analyse the omics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe significantly downregulated Ohtaekwangia (P=0.022) and Odoribacter (P=0.016) in the intestinal microbes of aged mice with ostoperative cognitive function had a significant positive correlation with the faecal metabolite, guanosine-5'-monophosphate (P=0.008). At the same time, guanosine-5-monophosphate showed the same downward trend in stool and serum samples. In addition, 1,7-dimethylxanthine was significantly downregulated in the hippocampus of aged mice with ostoperative cognitive function and was positively correlated with calpastatin, whose expression was downregulated (P=0.013).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eSignificant changes in microorganisms, proteins, and metabolites were detected in the faecal, serum, and hippocampal samples of aged mice with ostoperative cognitive function induced by sevoflurane inhalation. Moreover, there was a correlation between the three samples. These findings provide new insights into the mechanisms of ostoperative cognitive function.\u003c/p\u003e","manuscriptTitle":"Postoperative cognitive dysfunction in aged mice after sevoflurane inhalation: crosstalk of gut microbiota, metabolomics, and proteomics","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-17 10:59:16","doi":"10.21203/rs.3.rs-4597888/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":"25d2d7d6-5c6a-40cb-a8bd-974896a2e868","owner":[],"postedDate":"July 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-06T04:53:57+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-17 10:59:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4597888","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4597888","identity":"rs-4597888","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}