Objective To explore the construction of heart preservation model of empty beating donor based on extracorporeal membrane oxygenation (ECMO). Methods From January 2022 to August 2023, 20 Guangxi Bama miniature pigs weighing 25-30 kg were selected, half male and half female. Under general anesthesia and heparinization, a midline thoracotomy was performed. The pericardium was cut after freeing the anterior and posterior vena cavae, and a perfusion needle was inserted near the brachiocephalic artery in the ascending aorta, connected to a blood collection bag to collect 500-600 mL of blood. The anterior and posterior vena cavae were ligated, the aorta was blocked and perfused with HTK solution to stop the heart beating. The superior and inferior vena cavae were cut off, the right pulmonary vein was decompressed, the aorta and left and right pulmonary arteries and veins were cut off, and the whole heart was removed. An ECMO device was used to continuously perfuse a cardioprotective solution mainly composed of oxygenated warm blood, maintaining the isolated pig heart beating for 8 hours, monitoring (once/hour) ECMO perfusion parameters, blood gas indicators, perfusate electrolytes, inflammatory factors, myocardial enzymes, myoglobin, and troponin levels. Myocardial tissue was taken for hematoxylin-eosin (HE) staining to observe myocardial cell damage and evaluate the quality of heart preservation. Results Among the 20 isolated beating pig hearts, 17 successfully resumed beating, 3 experienced ventricular fibrillation, resuscitated after intracardiac electrical defibrillation, and all 20 pig hearts successfully beat for 8 hours. There was no statistical difference in ECMO perfusion parameters, blood gas indicators, perfusate electrolytes, and inflammatory factors at each time point (P>0.05). There were statistical increases in myocardial enzymes, myoglobin, and troponin levels (P<0.05). HE staining results suggested that there was no severe myocardial damage. Conclusion ECMO technology can be used for pig heart preservation with good results, and this study provides experimental evidence for improving heart preservation research in clinical heart transplantation.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

Background: Adrenocortical hormones, particularly 11-oxygenated androgens, are pivotal in female reproductive health and fertility. Standardized detection kits and population-specific reference intervals are lacking in China, hindering related clinical applications. Methods: A HPLC-tandem mass spectrometry (HPLC-MS/MS) pipeline was developed, rigorously validated, and applied to simultaneously quantify corticosterone, cortisone, cortisol, 18-OH cortisol, androstenedione (A4), 11β-hydroxyandrostenedione (11-OH A4), dehydroepiandrosterone, and dehydroepiandrosterone sulfate in serum samples from 455 reproductive-aged women (18–45 yrs) in Guangxi, China. Age-dependent concentration trends were analyzed, and reference intervals stratified by age (2.5th to 97.5th percentiles) were established. Correlations with body-composition metrics, ethnicity, and the menstrual cycle were investigated. Results: The HPLC-MS/MS method demonstrated high precision (intra- and inter-assay CVs < 15%), accuracy, and sensitivity. All eight hormones exhibited significant age-related declines (P < 0.001 for seven hormones; P = 0.001 for 11-OH A4). Notably, 11-OH A4 levels were significantly lower in the 35–45-yr (3.05 nmol/L) and 25–34-yr (3.09 nmol/L) age groups than in the 18–24-yr (3.57 nmol/L) age group, whereas no significant difference was observed between the 35–45-yr and 25–34-yr age groups. Weak negative correlations were observed between the body mass index and corticosterone and cortisone levels, whereas ethnicity and the menstrual cycle showed no significant associations with hormone levels. Conclusions We developed an HPLC-MS/MS-based method for simultaneously quantifying eight adrenocortical hormones, including 11-OH A4, and defined age-specific reference intervals for reproductive-aged Chinese women. These findings advance the clinical utility of adrenocortical hormones in diagnosing and managing reproductive disorders.

ObjectiveTo investigate the efficacy and underlying mechanisms of Gynostemma pentaphyllum alcohol extract in improving glucose and lipid metabolism disorders in db/db mice through transcriptomics and gut microbiota analysis. MethodsEighteen db/db mice were randomly assigned to the model（DM） group， metformin（MET） group， and G. pentaphyllum alcohol extract（GP） group， with six mice in each group， based on stratification of fasting blood glucose and body weight. An additional six db/m mice were selected as the normal control（NC） group. Mice in the NC and DM groups were administered deionized water （10 mL·kg^-1） daily. The MET group received metformin （0.195 g·kg^-1） by gavage. The GP group was treated with G. pentaphyllum alcohol extract （3.9 g·kg^-1） by gavage for six weeks. Fasting blood glucose was measured every two weeks. After six weeks of intervention， serum levels of total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein cholesterol （LDL-C）， high-density lipoprotein cholesterol （HDL-C）， aspartate aminotransferase （AST）， alanine aminotransferase （ALT）， creatinine （CREA）， and blood urea nitrogen （BUN） were assessed. Enzyme-linked immunosorbent assay （ELISA） was used to measure insulin （FINS）， adiponectin （ADP）， and tumor necrosis factor-α （TNF-α）. Hematoxylin-eosin （HE） staining was used to observe liver histomorphology， periodic acid-Schiff （PAS） staining was employed to assess hepatic glycogen synthesis， and Oil Red O staining was used to detect hepatic lipid deposition. Liver transcriptomic data were used to identify differentially expressed genes in the liver and conduct enrichment analysis. Real-time PCR was employed to verify the expression levels of adiponectin gene （Adipoq）， peroxisome proliferator-activated receptor gamma coactivator-1α （PGC-1α）， AMP-activated protein kinase （AMPK）， peroxisome proliferator-activated receptor α （PPARα）， glucokinase （GCK）， forkhead box （Fox）O1， FoxO3， phosphoenolpyruvate carboxykinase （PEPCK）， and glucose-6-phosphatase （G6PC）. Metagenomic sequencing was conducted to analyze changes in gut microbiota composition. ResultsCompared with the NC group， the DM group exhibited significantly elevated fasting blood glucose （P<0.01）， serum AST， ALT， TC， TG， LDL-C， and HDL-C （P<0.01）. FINS， homeostatic model assessment for insulin resistance （HOMA-IR）， and the inflammatory cytokine TNF-α were significantly increased （P<0.01）， while ADP was significantly decreased （P<0.05）. Histological analysis confirmed severe hepatic steatosis and excessive lipid accumulation in the DM group， along with markedly reduced glycogen synthesis. Compared with the DM group， the GP group showed significantly decreased fasting blood glucose （P<0.01）， reduced serum TC， LDL-C， and HDL-C levels （P<0.05）， significantly decreased serum TG and AST levels （P<0.01）， significantly reduced FINS， HOMA-IR， and TNF-α levels （P<0.01）， and significantly increased ADP （P<0.01）. Hepatic steatosis and lipid deposition were significantly alleviated， while glycogen synthesis was markedly enhanced. Transcriptomic differential and enrichment analyses suggested that the mechanisms by which G. pentaphyllum alcohol extract improved hepatic glucose and lipid metabolism in db/db mice may involve regulation of the AMPK and FoxO signaling pathways. Real-time PCR results confirmed that expression of PGC-1α， PEPCK， G6PC， FoxO1， and FoxO3 was significantly downregulated following treatment with G. pentaphyllum alcohol extract （P<0.05， P<0.01）， whereas mRNA expression of Adipoq， PPARα， GCK， and AMPK was significantly upregulated （P<0.05， P<0.01）. Metagenomic analysis showed that the relative abundance of Lactobacillus， Alistipes， and Akkermansia species was higher in the GP group than in the DM group. ConclusionG. pentaphyllum alcohol extract may improve glucose and lipid metabolism disorders in db/db mice by regulating the hepatic AMPK/PPARα pathway to suppress lipid deposition and alleviate hepatic steatosis， by inhibiting gluconeogenesis through the AMPK/PGC-1α and FoxO pathways to lower fasting blood glucose， and by increasing the abundance of beneficial gut bacteria such as Lactobacillus， Alistipes， and Akkermansia to restore gut microbiota balance.

ObjectiveTo investigate the efficacy and underlying mechanisms of Gynostemma pentaphyllum alcohol extract in improving glucose and lipid metabolism disorders in db/db mice through transcriptomics and gut microbiota analysis. MethodsEighteen db/db mice were randomly assigned to the model（DM） group， metformin（MET） group， and G. pentaphyllum alcohol extract（GP） group， with six mice in each group， based on stratification of fasting blood glucose and body weight. An additional six db/m mice were selected as the normal control（NC） group. Mice in the NC and DM groups were administered deionized water （10 mL·kg^-1） daily. The MET group received metformin （0.195 g·kg^-1） by gavage. The GP group was treated with G. pentaphyllum alcohol extract （3.9 g·kg^-1） by gavage for six weeks. Fasting blood glucose was measured every two weeks. After six weeks of intervention， serum levels of total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein cholesterol （LDL-C）， high-density lipoprotein cholesterol （HDL-C）， aspartate aminotransferase （AST）， alanine aminotransferase （ALT）， creatinine （CREA）， and blood urea nitrogen （BUN） were assessed. Enzyme-linked immunosorbent assay （ELISA） was used to measure insulin （FINS）， adiponectin （ADP）， and tumor necrosis factor-α （TNF-α）. Hematoxylin-eosin （HE） staining was used to observe liver histomorphology， periodic acid-Schiff （PAS） staining was employed to assess hepatic glycogen synthesis， and Oil Red O staining was used to detect hepatic lipid deposition. Liver transcriptomic data were used to identify differentially expressed genes in the liver and conduct enrichment analysis. Real-time PCR was employed to verify the expression levels of adiponectin gene （Adipoq）， peroxisome proliferator-activated receptor gamma coactivator-1α （PGC-1α）， AMP-activated protein kinase （AMPK）， peroxisome proliferator-activated receptor α （PPARα）， glucokinase （GCK）， forkhead box （Fox）O1， FoxO3， phosphoenolpyruvate carboxykinase （PEPCK）， and glucose-6-phosphatase （G6PC）. Metagenomic sequencing was conducted to analyze changes in gut microbiota composition. ResultsCompared with the NC group， the DM group exhibited significantly elevated fasting blood glucose （P<0.01）， serum AST， ALT， TC， TG， LDL-C， and HDL-C （P<0.01）. FINS， homeostatic model assessment for insulin resistance （HOMA-IR）， and the inflammatory cytokine TNF-α were significantly increased （P<0.01）， while ADP was significantly decreased （P<0.05）. Histological analysis confirmed severe hepatic steatosis and excessive lipid accumulation in the DM group， along with markedly reduced glycogen synthesis. Compared with the DM group， the GP group showed significantly decreased fasting blood glucose （P<0.01）， reduced serum TC， LDL-C， and HDL-C levels （P<0.05）， significantly decreased serum TG and AST levels （P<0.01）， significantly reduced FINS， HOMA-IR， and TNF-α levels （P<0.01）， and significantly increased ADP （P<0.01）. Hepatic steatosis and lipid deposition were significantly alleviated， while glycogen synthesis was markedly enhanced. Transcriptomic differential and enrichment analyses suggested that the mechanisms by which G. pentaphyllum alcohol extract improved hepatic glucose and lipid metabolism in db/db mice may involve regulation of the AMPK and FoxO signaling pathways. Real-time PCR results confirmed that expression of PGC-1α， PEPCK， G6PC， FoxO1， and FoxO3 was significantly downregulated following treatment with G. pentaphyllum alcohol extract （P<0.05， P<0.01）， whereas mRNA expression of Adipoq， PPARα， GCK， and AMPK was significantly upregulated （P<0.05， P<0.01）. Metagenomic analysis showed that the relative abundance of Lactobacillus， Alistipes， and Akkermansia species was higher in the GP group than in the DM group. ConclusionG. pentaphyllum alcohol extract may improve glucose and lipid metabolism disorders in db/db mice by regulating the hepatic AMPK/PPARα pathway to suppress lipid deposition and alleviate hepatic steatosis， by inhibiting gluconeogenesis through the AMPK/PGC-1α and FoxO pathways to lower fasting blood glucose， and by increasing the abundance of beneficial gut bacteria such as Lactobacillus， Alistipes， and Akkermansia to restore gut microbiota balance.

ObjectiveTo evaluate the therapeutic effects of modified Buwangsan on cognitive dysfunction in the rat model of type 2 diabetes mellitus with mild cognitive impairment （T2DM-MCI） and explore the underlying mechanism. MethodsThirty-six 5-week-old SPF-grade SD rats were randomly assigned into 6 groups： Normal （Con， fed with a normal diet）， model （DM， fed with a high-sugar and high-fat diet）， low-dose modified Buwangsan （L-BWS， 1.86 g·kg^-1）， medium-dose modified Buwangsan （M-BWS， 3.72 g·kg^-1）， high-dose modified Buwangsan （H-BWS，7.44 g·kg^-1）， and huperzine A （SSJJ， 0.018 mg·kg^-1）. The rats were treated by gavage once a day for 12 weeks. The body weight and blood glucose level were monitored dynamically. Morris water maze was employed to test the cognitive function of rats. Hematoxylin-eosin and Nissl staining were employed to observe the pathological changes of the hippocampus. The levels of tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6） in the serum and hippocampus were assessed by enzyme-linked immunosorbent assay. Western blotting was employed to determine the expression levels of key autophagy-related proteins including microtubule-associated protein 1 light chain 3 （LC3）， type Ⅲ phosphatidylinositol 3-kinase complex regulatory subunit （Beclin1）， and phosphorylated UNC-51-like kinase （p-ULK） 1/2 in the hippocampus. Immunofluorescence staining was employed to observe the regulation of p-PI3K/PI3K， p-mTOR/mTOR， and p-Akt/Akt ratios. ResultsCompared with the DM group， the L-BWS， M-BWS， H-BWS， and SSJJ groups showed increases in body weight at the end of the experiment （P<0.05）， and the M-BWS， H-BWS and SSJJ groups showed declines in fasting blood glucose level （P<0.05）. In the water maze test， compared with the DM group， the M-BWS， H-BWS， and SSJJ groups presented shortened escape latency （P<0.001）. The L-BWS， M-BWS， H-BWS， and SSJJ group showcased regularly arranged cells in the hippocampus and cortex， markedly increased number of neurons， and significantly recovered Nissl bodies. Compared with the DM group， the L-BWS， M-BWS， H-BWS， and SSJJ groups had reductions in the levels of IL-1β and IL-6 in the serum and hippocampus （P<0.05）， increases in the LC3-II/LC3-I ratio and expression level of beclin1 in the hippocampus （P<0.05） and the p-ULK level （P<0.05）. The p-PI3K/PI3K， p-Akt/Akt， and p-mTOR/mTOR ratios in the hippocampus decreased in the M-BWS， H-BWS， and SSJJ groups （P<0.01）. ConclusionModified Buwangsan significantly ameliorates cognitive dysfunction and neurological damage in the rat model of T2DM through multiple mechanisms. It regulates metabolic disorders， lowers the blood glucose level， improves lipid metabolism， and alleviates oxidative stress. It promotes the protection and repair of neurons by inhibiting inflammatory responses and activating the autophagy pathway in the hippocampus. At the same time， modified Buwangsan relieves autophagy inhibition by regulating the PI3K/Akt/mTOR signaling pathway to alleviate the brain tissue injury.

ObjectiveTo evaluate the therapeutic effects of modified Buwangsan on cognitive dysfunction in the rat model of type 2 diabetes mellitus with mild cognitive impairment （T2DM-MCI） and explore the underlying mechanism. MethodsThirty-six 5-week-old SPF-grade SD rats were randomly assigned into 6 groups： Normal （Con， fed with a normal diet）， model （DM， fed with a high-sugar and high-fat diet）， low-dose modified Buwangsan （L-BWS， 1.86 g·kg^-1）， medium-dose modified Buwangsan （M-BWS， 3.72 g·kg^-1）， high-dose modified Buwangsan （H-BWS，7.44 g·kg^-1）， and huperzine A （SSJJ， 0.018 mg·kg^-1）. The rats were treated by gavage once a day for 12 weeks. The body weight and blood glucose level were monitored dynamically. Morris water maze was employed to test the cognitive function of rats. Hematoxylin-eosin and Nissl staining were employed to observe the pathological changes of the hippocampus. The levels of tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6） in the serum and hippocampus were assessed by enzyme-linked immunosorbent assay. Western blotting was employed to determine the expression levels of key autophagy-related proteins including microtubule-associated protein 1 light chain 3 （LC3）， type Ⅲ phosphatidylinositol 3-kinase complex regulatory subunit （Beclin1）， and phosphorylated UNC-51-like kinase （p-ULK） 1/2 in the hippocampus. Immunofluorescence staining was employed to observe the regulation of p-PI3K/PI3K， p-mTOR/mTOR， and p-Akt/Akt ratios. ResultsCompared with the DM group， the L-BWS， M-BWS， H-BWS， and SSJJ groups showed increases in body weight at the end of the experiment （P<0.05）， and the M-BWS， H-BWS and SSJJ groups showed declines in fasting blood glucose level （P<0.05）. In the water maze test， compared with the DM group， the M-BWS， H-BWS， and SSJJ groups presented shortened escape latency （P<0.001）. The L-BWS， M-BWS， H-BWS， and SSJJ group showcased regularly arranged cells in the hippocampus and cortex， markedly increased number of neurons， and significantly recovered Nissl bodies. Compared with the DM group， the L-BWS， M-BWS， H-BWS， and SSJJ groups had reductions in the levels of IL-1β and IL-6 in the serum and hippocampus （P<0.05）， increases in the LC3-II/LC3-I ratio and expression level of beclin1 in the hippocampus （P<0.05） and the p-ULK level （P<0.05）. The p-PI3K/PI3K， p-Akt/Akt， and p-mTOR/mTOR ratios in the hippocampus decreased in the M-BWS， H-BWS， and SSJJ groups （P<0.01）. ConclusionModified Buwangsan significantly ameliorates cognitive dysfunction and neurological damage in the rat model of T2DM through multiple mechanisms. It regulates metabolic disorders， lowers the blood glucose level， improves lipid metabolism， and alleviates oxidative stress. It promotes the protection and repair of neurons by inhibiting inflammatory responses and activating the autophagy pathway in the hippocampus. At the same time， modified Buwangsan relieves autophagy inhibition by regulating the PI3K/Akt/mTOR signaling pathway to alleviate the brain tissue injury.

Organophosphorus nerve agents are the most threatening chemical warfare agents and terrorist agents.The number of nerve agents and their related chemicals involved in the verification of Chemical Weapon Convention(CWC)exceeds ten million,with the majority being isomers.Accurate structural identification of these chemicals has always been one of the challenges in CWC related verification analysis.In this work,a total of 17 kinds of alkyl phosphonate isomers and structural analogs from 5 groups were designed and synthesized,and then analyzed by gas chromatography-mass spectrometry(GC-MS)and gas chromatography-infrared spectroscopy(GC-FTIR).The spectra of isomers or structural analogs obtained from two techniques as well as the structural information provided therein were compared and analyzed.The results showed that for isomers or structural analogs with similar MS spectra,FTIR spectra could provided more structural fingerprint information of compounds and had advantages in confirming structures.Combined with the excellent separation ability of GC,GC-FTIR can be used to assist GC-MS in the structural confirmation of alkyl phosphates,achieving rapid and accurate identification of isomers or structural analogues.

Objective To compare the application effects of plankton multiplex polymerase chain reac-tion-capillary electrophoresis(PCR-CE),SYBR Green Ⅰ real-time quantitative PCR(qPCR)and microwave digestion-vacuum filtration-automated scanning electron microscopy(MD-VF-Auto SEM)in the diagnosis of drowning.Methods Lung,liver and kidney tissues from 212 drowned corpses and 30 non-drowned corpses were examined respectively by the three drowning-related plankton testing methods,and the detection rates of plankton in each tissue by three methods were compared.Results In drowned corpses,the total detection rates of PCR-CE,qPCR,and MD-VF-Auto SEM were 93.9%,96.2%,and 95.3%,respectively,with no statistically significant difference(P>0.05).The detection rate of lung tissue by MD-VF-Auto SEM(100%)was higher than those of PCR-CE and qPCR(P<0.05),and there was no significant difference in the detection rates of the three methods in liver or kidney tissues(P>0.05).In non-drowning corpses,a small number of diatoms(less than 10 cells/10 g)were detected by MD-VF-Auto SEM method,only in liver and kidney tissues,while the other two methods yielded negative results for all tissues.Conclusion All three methods have good efficacy in the examination of drowned corpses.The MD-VF-Auto SEM method directly observes diatom morpho-logical characteristics through scanning electron microscopy,and the qualitative and quantitative analy-ses are intuitive and accurate.It has great advantages in the examination of difficult degradation samples.The PCR-CE method and qPCR method have a low sample demand(0.5 g),are easy to operate and have short detection time(4-7 h).They are easy to be applied in the grassroots depart-ments and are suitable for the rapid determination of drowned corpses in routin cases.The combina-tion of the two DNA methods with the MD-VF-Auto SEM method can increase the detection rate of plankton,ensuring the reliability of examination results.This combined use is of significant importance in the application of drowning diagnosis.