OBJECTIVE To establish a method for determining the contents of clopidogrel （CLP）， clopidogrel carboxylate （CLP-C）， clopidogrel acyl-β-D-glucuronide （CLP-G） and contents of clopidogrel active metabolite （CAM） in rat plasma， and to investigate their in vivo pharmacokinetic characteristics. METHODS The Shisedo CAPCELL ADME column was used with a mobile phase consisting of water and acetonitrile （both containing 0.1% formic acid） in a gradient elution. The flow rate was 0.4 mL/min， and the column temperature was maintained at 20 ℃. The injection volume was 2 μL. The analysis was performed in positive ion mode using electrospray ionization with multiple reaction monitoring. The ion pairs for quantitative analysis were m/z 322.1→211.9 （for CLP）， m/z 308.1→197.9 （for CLP-C）， m/z 322.1→154.8 （for CLP-G）， m/z 504.1→154.9 [for racemic CAM derivative （CAMD）]. Six rats were administered a single intragastric dose of CLP （10 mg/kg）. Blood samples were collected before medication and at 0.08， 0.33， 0.66， 1， 2， 4， 6， 10， 23 and 35 hours after medication. The established method was used to detect the serum contents of various components in rats. Pharmacokinetic parameters were then calculated using WinNonlin 6.1 software. RESULTS The linear ranges for CLP， CLP-C and CAMD were 0.08-20.00， 205.00-8 000.00， and 0.04-25.00 ng/mL， respectively （r≥0.990）. The relative standard deviations for both intra-day and inter-day precision tests were all less than 15%， and the relative errors for accuracy ranged from －11.68% to 14.40%. The coefficients of variation for the matrix factors were all less than 15%， meeting the requirements for bioanalytical method validation. The results of the pharmacokinetic study revealed that， following a single intagastric administration of CLP in rats， the exposure to the parent CLP in plasma was extremely low. Both the area under the drug concentration-time curve （AUC0-35 h） and the peak concentration of the parent CLP were lower than those of its metabolites. The AUC0-35 h of the active metabolite CAM was approximately 43 times that of CLP， though it had a shorter half-life （2.53 h）. The inactive metabolite CLP-C exhibited the highest exposure level， but it reached its peak concentration the latest and was eliminated slowly. The AUC0-35 h of CLP-G was about four times that of CAM， and its half-life was similar to that of CLP-C. CONCLUSIONS This study successfully established an liquid chromatography-tandem mass spectrometry method for the determination of CLP and its three metabolites， and revealed their pharmacokinetic characteristics in rats. Specifically， the parent drug CLP was rapidly eliminated， while the inactive metabolites CLP-C and CLP-G exhibited long half-lives， and active metabolite CAM displayed a transient exposure pattern.

This study predicts the quality markers(Q-markers) for the cough-relieving and phlegm-expelling effects of Kening Granules based on pharmacodynamics, plasma drug chemistry, network pharmacology, and pharmacokinetics. Strong ammonia solution spray and phenol red secretion assays were employed to evaluate the cough-relieving and phlegm-expelling effects of Kening Granules. Twentysix absorbed prototype components of Kening Granules were identified by ultra high performance liquid chromatography coupled with QExactive Plus quadrupole/Orbitrap high resolution mass spectrometry(UHPLC-Q-Exactive Plus Orbitrap HRMS). Through network pharmacology, 11 potential active components were screened out for the cough-relieving and phlegm-expelling effects of Kening Granules. The 11 components acted on 40 common targets such as IL6, TLR4, and STAT3, which mainly participated in PI3K/Akt, HIF-1, and EGFR signaling pathways. Pharmacokinetic quantitative analysis was performed for 7 prototype components. Three compounds including azelaic acid, caffeic acid, and vanillin were identified as Q-markers for the cough-relieving and phlegm-expelling effects of Kening Granules based on their effectiveness, transmissibility, and measurability. The results of this study are of great significance for clarifying the pharmacological substance basis, optimizing the quality standards, and promoting the clinical application of Kening Granules.
Drugs, Chinese Herbal/administration & dosage* ; Network Pharmacology ; Cough/blood* ; Male ; Humans ; Animals ; Rats ; Rats, Sprague-Dawley ; Biomarkers/blood* ; Quality Control ; Chromatography, High Pressure Liquid ; Antitussive Agents/chemistry*

This study aims to explore the role and mechanism of berberine in promoting the expression of aquaporin 4(AQP4) in astrocytes by regulating the expression of miR-383-5p in HepG2 cell-derived exosomes under insulin resistance(IR). The IR-HepG2 cell model was established with 1×10~(-6) mol·L~(-1) insulin. With metformin as the positive control, the safe concentrations of berberine and metformin were screened by cell counting kit-8(CCK-8) and lactate dehydrogenase(LDH) leakage assays, and the effect of berberine on the IR of HepG2 cells was evaluated by glucose consumption. NanoSight was used to measure the particle size and concentration of exosomes secreted by HepG2 cells in each group. HepG2 cell-derived exosomes in each group were incubated with astrocytes for 24 h, and the protein and mRNA levels of AQP4 in HA1800 cells were determined by Western blot and qRT-PCR, respectively. qRT-PCR was performed to determine the expression of miR-383-5p in HepG2 cell-derived exosomes and HA1800 cells after co-incubation. Western blotting was employed to determine the expression levels of miRNAs and proteins associated with exosome production and release in HepG2 cells. The results showed that 10 μmol·L~(-1) berberine and 1 mmol·L~(-1) metformin significantly alleviated the IR of HepG2 cells and reduced the concentration of exosomes in HepG2 cells. The exosomes of HepG2 cells treated with berberine and metformin significantly up-regulated the protein and mRNA levels of AQP4 in HA1800 cells. The mRNA level of miR-383-5p in HepG2 cell exosomes and HA1800 cells co-incubated with berberine and metformin decreased significantly. The intervention with berberine and metformin significantly down-regulated the expression of proteins associated with the production of miRNAs(Dicer, Drosha) as well as the production(Alix, Vps4A) and release(Rab35, VAMP3) of exosomes in IR-HepG2 cells. In conclusion, berberine can promote the expression of AQP4 in astrocytes by inhibiting the production and release of miR-383-5p in HepG2-derived exosomes under IR.
Humans ; MicroRNAs/metabolism* ; Berberine/pharmacology* ; Hep G2 Cells ; Exosomes/genetics* ; Aquaporin 4/metabolism* ; Insulin Resistance ; Astrocytes/drug effects*

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

OBJECTIVES: To investigate the effects of methylenetetrahydrofolate reductase (MTHFR) rs1801133 and γ-glutamyl hydrolase (GGH) rs11545078 gene polymorphisms on plasma concentrations and toxicity following high-dose methotrexate (MTX) therapy in children with acute lymphoblastic leukemia (ALL). METHODS: Children with ALL treated at the Xuzhou Children's Hospital of Xuzhou Medical University from January 2021 to April 2024 were selected for this study. Genotypes of MTHFR rs1801133 and GGH rs11545078 were determined using multiplex polymerase chain reaction. MTX plasma concentrations were measured by enzyme-multiplied immunoassay technique, and toxicity was graded according to the Common Terminology Criteria for Adverse Events version 5.0. The relationships between MTHFR rs1801133 and GGH rs11545078 genotypes and both MTX plasma concentrations and associated toxicities were analyzed. RESULTS: In the low-risk ALL group, the MTHFR rs1801133 genotype was associated with increased MTX plasma concentrations at 72 hours (P<0.05). In the intermediate- to high-risk group, the MTHFR rs1801133 genotype was associated with increased MTX plasma concentrations at 48 hours (P<0.05), and the GGH rs11545078 genotype was associated with increased MTX plasma concentrations at 48 hours (P<0.05). In the intermediate- to high-risk group, the MTHFR rs1801133 genotype was associated with the occurrence of reduced hemoglobin (P<0.05), and the GGH rs11545078 genotype was associated with the occurrence of thrombocytopenia (P<0.05). CONCLUSIONS Detection of MTHFR rs1801133 and GGH rs11545078 genotypes can be used to predict increased MTX plasma concentrations and the occurrence of toxic reactions in high-dose MTX treatment of ALL, enabling timely interventions to enhance safety.
Humans ; Methotrexate/toxicity* ; Methylenetetrahydrofolate Reductase (NADPH2)/genetics* ; Precursor Cell Lymphoblastic Leukemia-Lymphoma/blood* ; Male ; Female ; Child ; Child, Preschool ; gamma-Glutamyl Hydrolase/genetics* ; Antimetabolites, Antineoplastic/adverse effects* ; Infant ; Polymorphism, Genetic ; Adolescent ; Genotype ; Polymorphism, Single Nucleotide

OBJECTIVE: To investigate the Wnt signaling pathway and miRNAs mechanism of extracts of Plastrum Testudinis (PT) in the treatment of osteoporosis (OP). METHODS: Thirty female Sprague Dawley rats were randomly divided into 5 groups by random number table method, including sham group, ovariectomized group (OVX), ovariectomized groups treated with high-, medium-, and low-dose PT (160, 80, 40 mg/kg per day, respectively), with 6 rats in each group. Except for the sham group, the other rats underwent bilateral ovariectomy to simulate OP and received PT by oral gavage for 10 consecutive weeks. After treatment, bone mineral density was measured by dual-energy X-ray absorptiometry; bone microstructure was analyzed by micro-computed tomography and hematoxylin and eosin staining; and the expressions of osteogenic differentiation-related factors were detected by immunochemistry, Western blot, and quantitative polymerase chain reaction. In addition, Dickkopf-1 (Dkk-1) was used to inhibit the Wnt signaling pathway in bone marrow mesenchymal stem cells (BMSCs) and miRNA overexpression was used to evaluate the effect of miR-214 on the osteogenic differentiation of BMSCs. Subsequently, PT extract was used to rescue the effects of Dkk-1 and miR-214, and its impacts on the osteogenic differentiation-related factors of BMSCs were evaluated. RESULTS: PT-M and PT-L significantly reduced the weight gain in OVX rats (P<0.05). PT also regulated the bone mass and bone microarchitecture of the femur in OVX rats, and increased the expressions of bone formation-related factors including alkaline phosphatase, bone morphogenetic protein type 2, collagen type I alpha 1, and runt-related transcription factor 2 when compared with the OVX group (P<0.05 or P<0.01). Meanwhile, different doses of PT significantly rescued the inhibition of Wnt signaling pathway-related factors in OVX rats, and increased the mRNA or protein expressions of Wnt3a, β-catenin, glycogen synthase kinase-3β, and low-density lipoprotein receptor-related protein 5 (P<0.05 or P<0.01). PT stimulated the osteogenic differentiation of BMSCs inhibited by Dkk-1 and activated the Wnt signaling pathway. In addition, the expression of miR-214 was decreased in OVX rats (P<0.01), and it was negatively correlated with the osteogenic differentiation of BMSCs (P<0.01). MiR-214 mimic inhibited Wnt signaling pathway in BMSCs (P<0.05 or P<0.01). Conversely, PT effectively counteracted the effect of miR-214 mimic, thereby activating the Wnt signaling pathway and stimulating osteogenic differentiation in BMSCs (P<0.05 or P<0.01). CONCLUSION PT stimulates bone formation in OVX rats through β-catenin-mediated Wnt signaling pathway, which may be related to inhibiting miR-214 in BMSCs.
Animals ; MicroRNAs/genetics* ; Female ; Rats, Sprague-Dawley ; Wnt Signaling Pathway/genetics* ; Osteogenesis/genetics* ; Mesenchymal Stem Cells/cytology* ; Cell Differentiation/drug effects* ; Bone Density/drug effects* ; Ovariectomy ; Osteoporosis/drug therapy* ; beta Catenin/metabolism* ; Rats ; Intercellular Signaling Peptides and Proteins/metabolism* ; Drugs, Chinese Herbal/pharmacology*

Intervertebral disc degeneration (IDD) is largely attributed to impaired endogenous repair. Nucleus pulposus-derived stem cells (NPSCs) senescence leads to endogenous repair failure. Small extracellular vesicles/exosomes derived from mesenchymal stem cells (mExo) have shown great therapeutic potential in IDD, while whether mExo could alleviate NPSCs senescence and its mechanisms remained unknown. We established a compression-induced NPSCs senescence model and rat IDD models to evaluate the therapeutic efficiency of mExo and investigate the mechanisms. We found that mExo significantly alleviated NPSCs senescence and promoted disc regeneration while knocking down thioredoxin (TXN) impaired the protective effects of mExo. TXN was bound to various endosomal sorting complex required for transport (ESCRT) proteins. Autocrine motility factor receptor (AMFR) mediated TXN K63 ubiquitination to promote the binding of TXN on ESCRT proteins and sorting of TXN into mExo. Knocking down exosomal TXN inhibited the transcriptional activity of nuclear factor erythroid 2-related factor 2 (NRF2) and activator protein 1 (AP-1). NRF2 and AP-1 inhibition reduced endogenous TXN production that was promoted by exosomal TXN. Inhibition of NRF2 in vivo diminished the anti-senescence and regenerative effects of mExo. Conclusively, AMFR-mediated TXN ubiquitination promoted the sorting of TXN into mExo, allowing exosomal TXN to promote endogenous TXN production in NPSCs via TXN/NRF2/AP-1 feed-forward circuit to alleviate NPSCs senescence and disc degeneration.

Wastewater-based epidemiology has emerged as a transformative surveillance tool for estimating substance consumption and monitoring disease prevalence, particularly during the COVID-19 pandemic. It enables the population-level monitoring of illicit drug use, pathogen prevalence, and environmental pollutant exposure. In this perspective, we summarize the key challenges specific to the Chinese context: (1) Sampling inconsistencies, necessitating standardized 24-hour composite protocols with high-frequency autosamplers (≤ 15 min/event) to improve the representativeness of samples; (2) Biomarker validation, requiring rigorous assessment of excretion profiles and in-sewer stability; (3) Analytical method disparities, demanding inter-laboratory proficiency testing and the development of automated pretreatment instruments; (4) Catchment population dynamics, reducing estimation uncertainties through mobile phone data, flow-based models, or hydrochemical parameters; and (5) Ethical and data management concerns, including privacy risks for small communities, mitigated through data de-identification and tiered reporting platforms. To address these challenges, we propose an integrated framework that features adaptive sampling networks, multi-scale wastewater sample banks, biomarker databases with multidimensional metadata, and intelligent data dashboards. In summary, wastewater-based epidemiology offers unparalleled scalability for equitable health surveillance and can improve the health of the entire population by providing timely and objective information to guide the development of targeted policies.
China/epidemiology* ; Humans ; Wastewater/analysis* ; COVID-19/epidemiology* ; Public Health ; Wastewater-Based Epidemiological Monitoring ; SARS-CoV-2

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of national bloodstream infection Bacterial Resistant Investigation Collaborative System（BRICS）were collected during January 2022 to December 2022. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute（CLSI）. WHONET 5.6 and SPSS 25.0 software were used to analyze the data.Results:During the study period，9 035 strains of Gram-negative bacteria were collected from 51 hospitals，of which 7 895（87.4%）were Enterobacteriaceae and 1 140（12.6%）were non-fermenting bacteria. The top 5 bacterial species were Escherichia coli（ n=4 510，49.9%）， Klebsiella pneumoniae（ n=2 340，25.9%）， Pseudomonas aeruginosa（ n=534，5.9%）， Acinetobacter baumannii complex（ n=405，4.5%）and Enterobacter cloacae（ n=327，3.6%）. The ESBLs-producing rates in Escherichia coli， Klebsiella pneumoniae and Proteus spp. were 47.1%（2 095/4 452），21.0%（427/2 033）and 41.1%（58/141），respectively. The prevalence of carbapenem-resistant Escherichia coli（CREC）and carbapenem-resistant Klebsiella pneumoniae（CRKP）were 1.3%（58/4 510）and 13.1%（307/2 340）；62.1%（36/58）and 9.8%（30/307）of CREC and CRKP were resistant to ceftazidime/avibactam combination，respectively. The prevalence of carbapenem-resistant Acinetobacter baumannii（CRAB）complex was 59.5%（241/405），while less than 5% of Acinetobacter baumannii complex was resistant to tigecycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa（CRPA）was 18.4%（98/534）. There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of main Gram-negative bacteria resistance among different regions，with statistically significant differences in the prevalence of CRKP and CRPA（ χ2=20.489 and 20.252， P<0.001）. The prevalence of CREC，CRKP，CRPA，CRAB，ESBLs-producing Escherichia coli and Klebsiella pneumoniae were higher in provinicial hospitals than those in municipal hospitals（ χ2=11.953，81.183，10.404，5.915，12.415 and 6.459， P<0.01 or <0.05），while the prevalence of CRPA was higher in economically developed regions（per capita GDP ≥ 92 059 Yuan）than that in economically less-developed regions（per capita GDP <92 059 Yuan）（ χ2=6.240， P=0.012）. Conclusions:The proportion of Gram-negative bacteria in bloodstream infections shows an increasing trend，and Escherichia coli is ranked in the top，while the trend of CRKP decreases continuously with time. Decreasing trends are noted in ESBLs-producing Escherichia coli and Klebsiella pneumoniae. Low prevalence of carbapenem resistance in Escherichia coli and high prevalence in CRAB complex have been observed. The composition ratio and antibacterial spectrum of bloodstream infections in different regions of China are slightly different，and the proportion of main drug resistant bacteria in provincial hospitals is higher than those in municipal hospitals.