Objective To mine and analyze signals of acute kidney injury(AKI)related to drugs,comprehensively summarize the potential risk drugs,and provide a reference for clinically safe medication.Methods The AKI reports from January 2004 to September 2023 in the US FDA Adverse Event Reporting System(FAERS)were retrieved.Disproportionality methods were used to explore the relationship between drugs and AKI,and demographic information,time to onset,and patient outcomes were analyzed.Results Out of 1 253 drugs,159 were identified as AKI signal drugs.Among these,there were 49 antimicrobial agents(30.82%),including 35 antibiotics and 14 antiviral agents;33 antineoplastic agents(20.75%);and 25 hypotensive agents(15.72%).Drug-related AKI occurred mostly in the elderly,and the male-to-female ratio was 124∶100.The median time to onset for AKI related to antibiotics was≤8 d,with the third quartile≤21 d.Rivaroxaban and aspirin had higher proportions of death reports,with 33.03%and 31.44%respectively.Conclusions A multitude of drugs pose a risk for acute kidney injury,necessitating caution in their clinical application and the implementation of monitoring of renal function.The elderly are a high-risk group for drug-related AKI,and there are more males than females.For antibiotics,the first 21 days are the key monitoring period.For drugs that require long-term use,regular monitoring is necessary.

In the context of the development of transplant oncology, it is of great clinical significance to find a drug with both antitumor and immunosuppressive effects for liver transplantation patients with hepatocellular carcinoma (HCC). The antitumor effect of ginkgolic acid (GA) has been confirmed, and some studies suggest that GA may also have an immunosuppressive effect. The immunosuppressive effect of GA was evaluated by histopathology, T-cell subpopulation, and cytokine detection in rat liver transplantation and mouse cardiac transplantation models, and transcriptomic and metabolomic analysis was used to explore the underlying mechanism of the GA immunosuppressive effect. Metabolites, activation, and ferroptosis markers of CD8⁺ T cells were detected in vivo and in vitro. Based on rat liver transplantation and mouse cardiac transplantation models, the immunosuppressive effect of GA was first confirmed by histopathology, T-cell subpopulation, and cytokine detection. In the mouse cardiac transplantation model, transcriptomics combined with metabolomics demonstrated for the first time that GA inhibited lactate dehydrogenase A (LDHA) expression and pyruvate metabolism in CD8⁺ T cells. It was confirmed in vivo and in vitro that GA inhibited pyruvate metabolism of CD8⁺ T cells through LDHA, inhibiting their activation and inducing ferroptosis. Overexpression of LDHA partially reversed the effect of GA on the metabolism, activation, and ferroptosis of CD8⁺ T cells in vitro. GA mediates metabolic reprogramming through LDHA to inhibit the activation and induce ferroptosis of CD8⁺ T cells to exert an immunosuppressive effect, which lays an experimental foundation for the future clinical application of its immunosuppressive effect.

Objective To screen antidepressant-active compounds from Polygonati Rhizoma and explore their effects and possible mechanisms against depression induced by simulated weightlessness.Methods A systems pharmacology approach was used to screen potential antidepressant-active compounds and their targets from Polygonati Rhizoma.The hindlimb unloading(HLU)rat model was employed for the study.Twenty-four healthy male Sprague-Dawley rats were randomly divided into three groups:control group(administered 0.5%carboxymethylcellulose by gavage),HLU group(hindlimb unloading),and HLU+treatment group(hindlimb unloading+active compound gavage),with 8 rats in each group.After 28 days of hindlimb unloading,depressive-like behaviors in rats were evaluated using the forced swimming test and tail suspension test.Hippocampal morphology was examined with H&E staining,and GO and KEGG enrichment analyses were conducted on the targets of active compounds.Results A total of 38 active compounds were screened from Polygonati Rhizoma,among which apigenin had an oral bioavailability of 23.06%and a drug-likeness score of 0.21.Compound-target network analysis indicated that apigenin had the highest degree and betweenness centrality values,suggesting it might be the key active component with antidepressant potential in Polygonati Rhizoma.In the forced swimming and tail suspension tests,rats in the HLU group showed a significant increase in immobility time compared to the control group,indicating successful establishment of the depression model.However,compared to the HLU group,rats in the HLU plus apigenin group exhibited significantly reduced immobility time.The H&E staining results of hippocampal tissue showed a significant reduction in the number of hippocampal neurons,along with numerous shrunken neurons and small vacuoles in nerve fibers in the HLU group.In contrast,the treatment group exhibited an increased number of hippocampal neurons,with improved cellular morphology.Target enrichment analysis indicated that apigenin targets were mainly involved in the regulation of apoptosis and cancer-related signaling pathways.Conclusion Apigenin significantly improved depressive-like behaviors in rats subjected to hindlimb unloading,and it has a protective effect on hippocampal tissue.It may provide a new natural active compound for the treatment of depression caused by spaceflight-induced weightlessness.

In the context of the development of transplant oncology,it is of great clinical significance to find a drug with both antitumor and immunosuppressive effects for liver transplantation patients with hepatocellular carcinoma(HCC).The antitumor effect of ginkgolic acid(GA)has been confirmed,and some studies suggest that GA may also have an immunosuppressive effect.The immunosuppressive effect of GA was evaluated by histopathology,T-cell subpopulation,and cytokine detection in rat liver transplantation and mouse cardiac transplantation models,and transcriptomic and metabolomic analysis was used to explore the underlying mechanism of the GA immunosuppressive effect.Metabolites,activation,and ferroptosis markers of CD8+T cells were detected in vivo and in vitro.Based on rat liver transplantation and mouse cardiac transplantation models,the immunosuppressive effect of GA was first confirmed by histopathology,T-cell subpopulation,and cytokine detection.In the mouse cardiac transplantation model,transcriptomics combined with metabolomics demonstrated for the first time that GA inhibited lactate dehydrogenase A(LDHA)expression and pyruvate metabolism in CD8+T cells.It was confirmed in vivo and in vitro that GA inhibited pyruvate metabolism of CD8+T cells through LDHA,inhibiting their activation and inducing ferroptosis.Over-expression of LDHA partially reversed the effect of GA on the metabolism,activation,and ferroptosis of CD8+T cells in vitro.GA mediates metabolic reprogramming through LDHA to inhibit the activation and induce ferroptosis of CD8+T cells to exert an immunosuppressive effect,which lays an experimental foundation for the future clinical application of its immunosuppressive effect.

Objective:To develop and validate risk prediction models for hypertension comorbidity in community-dwelling patients with type 2 diabetes mellitus(T2DM).Methods:The health records of 2 979 T2DM patients from two community health service centers in Fengtai District of Beijing from January 2023 to January 2024 were collected,including 2 591 cases from Fangzhuang Center(model development group) and 388 cases from Youanmen Center(external validation group). Patients in model development group were randomly assigned in a training set( n=1 813) and an internal validation set(778 cases) at a ratio of 7∶3. The risk factors associated with hypertention comorbidity in T2DM patients were identified with LASSO regression analysis,based on which risk prediction models was developed using six machine learning algorithms,including logistic regression(LR),classification and regression tree(CART),random forest(RF),extreme gradient boosting(XGB),support vector machine(SVM) and artificial neural network(ANN). The internal and external validations of the prediction models were conducted. Results:Among 2 979 patients with T2DM,2 158(72.44%) had concurrent hypertension,with 1 572 in the development set,280 in the internal validation set,306 in the external validation set. The LASSO regression identified 14 risk factors: age,educational level,occupation,medical insurance type,alcohol consumption,exercise frequency,BMI,SBP,TG/HDL-C,METS-IR,FBG,eGFR,duration of T2DM,and dyslipidemia. The nomogram model based on 14 predictive factors was constructed with XGB algorithm showed the best performance in predicting risk of hypertention for T2DM patients,showing the highest area under the curve(AUC) of 0.694(95% CI: 0.524-0.810) and effective calibration(Brier Score=0.121). Decision curve analysis confirmed the clinical utility of the predictive model. Conclusion:The risk prediction models based on machine learning algorithms have been developed in the study,which show good prediction perfomance for hiypertention comorbidity in community-dwelling T2DM patients.

Mental health records have been well utilized in various industries or groups both within and outside the mili-tary.However,due to insufficient attention,lack of technology,and poor talent stability,the effectiveness of mental health re-cords is low.This article investigates psychological cadres during a major task to understand the current situation of the establish-ment and use of mental health records in the military.It finds that there is a phenomenon of"building but not flowing,storing but not using",and identifies issues such as inconsistent standards,poor circulation,insufficient content,and disordered manage-ment.Based on this,the article discusses the safeguards and basic content for the construction of mental health records.The dis-cussion concludes that mental health record content should include general information about officers and soldiers,the develop-ment of psychological services,records of psychological rehabilitation(including psychological measurement results,etc.),and other supplementary materials(such as physical health status,personal life history,etc.).It is necessary to standardize mental health measurement,mental health education,mental health training,psychological counseling interviews,psychiatric assess-ment,and psychiatric rehabilitation.Support must be provided in terms of systems,personnel,and technology,and a dynamic management and use mechanism and information security control responsibilities must be implemented.This will promote the or-derly development of military mental health work and,in turn,ensure the mental health of officers and soldiers.

Objective To establish a risk prediction model of continuous renal replacement therapy(CRRT)withdrawal failure in patients with infectious shock complicating acute kidney injury(AKI)based on the decision tree algorithm,and to explore the influencing factors of CRRT withdrawal failure in patients with infectious shock complicating AKI.Methods 220 patients with infectious shock complicating AKI admitted to our hospital from May 2020 to May 2023 were retrospectively analyzed,and divided into success group and failure group according to the success or failure of the withdrawal,univariate and multivariate Logistic regression analysis were used to screen risk factors of CRRT withdrawal failure in patients with septic shock complicated with AKI,C-reactive protein/albumin(CRP/ALB)at admission and sepsis-related organ failure assessment(SOFA)score at withdrawal,acute physiology and chronic health evaluation(APACHE Ⅱ)score,N-terminal B-type natriuretic peptide(NT-proBNP)level at the beginning of CRRT,mean arterial pressure(MAP)grading,urine volume after withdrawal,and serum creatinine(Scr)level after withdrawal were taken into constructing a decision tree model and validating the model efficacy.Results In this study,there were 41.82％of patients failed to withdrawal.Combination of univariate and multivariate Logistic regression analysis showed that SOFA score at withdrawal,APACHE Ⅱ scores,urine volume after withdrawal,Scr level after withdrawal,NT-proBNP at the beginning of CRRT,and MAP grading,CRP/ALB at the time of admission were an independent risk factor for CRRT withdrawal failure in patients with septic shock complicated with AKI(P＜0.05).The results showed that the higher CRP/ALB was the most important influencing factor on the failure of CRRT evacuation in patients with infectious shock complicating AKI,and the area under the receiver operating characteristic curve was 0.965.Conclusion The decision tree model constructed by CRP/ALB at admission,SOFA score at withdrawal,urine volume after withdrawal,Scr level after withdrawal,APACHE Ⅱ score,and MAP grading has a better predictive efficacy of CRRT withdrawal failure in patients with infectious shock complicating AKI,which is a guideline for patients'prognostic assessment.

Mental health records have been well utilized in various industries or groups both within and outside the mili-tary.However,due to insufficient attention,lack of technology,and poor talent stability,the effectiveness of mental health re-cords is low.This article investigates psychological cadres during a major task to understand the current situation of the establish-ment and use of mental health records in the military.It finds that there is a phenomenon of"building but not flowing,storing but not using",and identifies issues such as inconsistent standards,poor circulation,insufficient content,and disordered manage-ment.Based on this,the article discusses the safeguards and basic content for the construction of mental health records.The dis-cussion concludes that mental health record content should include general information about officers and soldiers,the develop-ment of psychological services,records of psychological rehabilitation(including psychological measurement results,etc.),and other supplementary materials(such as physical health status,personal life history,etc.).It is necessary to standardize mental health measurement,mental health education,mental health training,psychological counseling interviews,psychiatric assess-ment,and psychiatric rehabilitation.Support must be provided in terms of systems,personnel,and technology,and a dynamic management and use mechanism and information security control responsibilities must be implemented.This will promote the or-derly development of military mental health work and,in turn,ensure the mental health of officers and soldiers.

Objective To mine and analyze signals of acute kidney injury(AKI)related to drugs,comprehensively summarize the potential risk drugs,and provide a reference for clinically safe medication.Methods The AKI reports from January 2004 to September 2023 in the US FDA Adverse Event Reporting System(FAERS)were retrieved.Disproportionality methods were used to explore the relationship between drugs and AKI,and demographic information,time to onset,and patient outcomes were analyzed.Results Out of 1 253 drugs,159 were identified as AKI signal drugs.Among these,there were 49 antimicrobial agents(30.82%),including 35 antibiotics and 14 antiviral agents;33 antineoplastic agents(20.75%);and 25 hypotensive agents(15.72%).Drug-related AKI occurred mostly in the elderly,and the male-to-female ratio was 124∶100.The median time to onset for AKI related to antibiotics was≤8 d,with the third quartile≤21 d.Rivaroxaban and aspirin had higher proportions of death reports,with 33.03%and 31.44%respectively.Conclusions A multitude of drugs pose a risk for acute kidney injury,necessitating caution in their clinical application and the implementation of monitoring of renal function.The elderly are a high-risk group for drug-related AKI,and there are more males than females.For antibiotics,the first 21 days are the key monitoring period.For drugs that require long-term use,regular monitoring is necessary.

Objective To establish a risk prediction model of continuous renal replacement therapy(CRRT)withdrawal failure in patients with infectious shock complicating acute kidney injury(AKI)based on the decision tree algorithm,and to explore the influencing factors of CRRT withdrawal failure in patients with infectious shock complicating AKI.Methods 220 patients with infectious shock complicating AKI admitted to our hospital from May 2020 to May 2023 were retrospectively analyzed,and divided into success group and failure group according to the success or failure of the withdrawal,univariate and multivariate Logistic regression analysis were used to screen risk factors of CRRT withdrawal failure in patients with septic shock complicated with AKI,C-reactive protein/albumin(CRP/ALB)at admission and sepsis-related organ failure assessment(SOFA)score at withdrawal,acute physiology and chronic health evaluation(APACHE Ⅱ)score,N-terminal B-type natriuretic peptide(NT-proBNP)level at the beginning of CRRT,mean arterial pressure(MAP)grading,urine volume after withdrawal,and serum creatinine(Scr)level after withdrawal were taken into constructing a decision tree model and validating the model efficacy.Results In this study,there were 41.82％of patients failed to withdrawal.Combination of univariate and multivariate Logistic regression analysis showed that SOFA score at withdrawal,APACHE Ⅱ scores,urine volume after withdrawal,Scr level after withdrawal,NT-proBNP at the beginning of CRRT,and MAP grading,CRP/ALB at the time of admission were an independent risk factor for CRRT withdrawal failure in patients with septic shock complicated with AKI(P＜0.05).The results showed that the higher CRP/ALB was the most important influencing factor on the failure of CRRT evacuation in patients with infectious shock complicating AKI,and the area under the receiver operating characteristic curve was 0.965.Conclusion The decision tree model constructed by CRP/ALB at admission,SOFA score at withdrawal,urine volume after withdrawal,Scr level after withdrawal,APACHE Ⅱ score,and MAP grading has a better predictive efficacy of CRRT withdrawal failure in patients with infectious shock complicating AKI,which is a guideline for patients'prognostic assessment.