BACKGROUND:Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated,but the causal relationship and related mechanisms have not yet been confirmed.With the cross-fertilization of computer science and life sciences,Mendelian randomization and bioinformatics analyses based on genome-wide association study(GWAS)and transcriptome sequencing data can assess the causal relationship between two diseases,explore the related mechanisms,and mine the therapeutic targets,which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.OBJECTIVE:To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses,aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.METHODS:(1)Firstly,GWAS data of rheumatoid arthritis,osteoporosis,and cis-expression quantitative trait locus(cis-eQTL)in Asian and European populations were downloaded from the GWAS Catalog,IEU Open GWAS,FinnGen,and eQTLGen databases,and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis.(2)Transcriptome sequencing data of rheumatoid arthritis(GSE93272 and GSE15573)were downloaded from the GEO database for bioinformatics analysis.(3)Subsequently,forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed,and inverse variance weighted was used as the main metric for the analyses,and the results were corroborated with MR Egger,simple mode,weighted median and weighted mode.(4)Then,the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis,and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis.Meanwhile,the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments.(5)In addition,a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2,and its prediction performance was verified by receiver operating characteristic curve,correction curve and decision curve.Finally,the target potential drugs were mined based on Enrichr database and molecular docking was performed.RESULTS AND CONCLUSION:(1)Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118,and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis.(2)Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis.(3)Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis,and 421 and 347 genes negatively associated.Based on the cross-analysis,26 co-morbid genes were subsequently obtained.Among them,DYRK2 was a potential therapeutic target,and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis.(4)Furthermore,the constructed nomogram has excellent predictive performance.Finally,four potential DYRK2-targeting drugs(undecanoic acid,metyrapone,JNJ-38877605,and ACA)were discovered and molecular docking also demonstrated reliable targeting ability.(5)In conclusion,based on GWAS data from Asian and European populations,we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level,DYRK2 is a potential therapeutic target,and four small molecules are potential target drugs.

BACKGROUND:Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated,but the causal relationship and related mechanisms have not yet been confirmed.With the cross-fertilization of computer science and life sciences,Mendelian randomization and bioinformatics analyses based on genome-wide association study(GWAS)and transcriptome sequencing data can assess the causal relationship between two diseases,explore the related mechanisms,and mine the therapeutic targets,which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.OBJECTIVE:To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses,aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.METHODS:(1)Firstly,GWAS data of rheumatoid arthritis,osteoporosis,and cis-expression quantitative trait locus(cis-eQTL)in Asian and European populations were downloaded from the GWAS Catalog,IEU Open GWAS,FinnGen,and eQTLGen databases,and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis.(2)Transcriptome sequencing data of rheumatoid arthritis(GSE93272 and GSE15573)were downloaded from the GEO database for bioinformatics analysis.(3)Subsequently,forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed,and inverse variance weighted was used as the main metric for the analyses,and the results were corroborated with MR Egger,simple mode,weighted median and weighted mode.(4)Then,the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis,and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis.Meanwhile,the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments.(5)In addition,a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2,and its prediction performance was verified by receiver operating characteristic curve,correction curve and decision curve.Finally,the target potential drugs were mined based on Enrichr database and molecular docking was performed.RESULTS AND CONCLUSION:(1)Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118,and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis.(2)Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis.(3)Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis,and 421 and 347 genes negatively associated.Based on the cross-analysis,26 co-morbid genes were subsequently obtained.Among them,DYRK2 was a potential therapeutic target,and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis.(4)Furthermore,the constructed nomogram has excellent predictive performance.Finally,four potential DYRK2-targeting drugs(undecanoic acid,metyrapone,JNJ-38877605,and ACA)were discovered and molecular docking also demonstrated reliable targeting ability.(5)In conclusion,based on GWAS data from Asian and European populations,we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level,DYRK2 is a potential therapeutic target,and four small molecules are potential target drugs.

Sepsis-acquired weakness (SAW) is a common complication in critically ill patients, yet significant gaps remain in both mechanistic understanding and therapeutic interventions for this condition. SAW not only prolongs the duration of mechanical ventilation and hospitalization but is also closely associated with increased mortality. Even if these SAW patients survive, they often experience long-term physical dysfunction after hospital discharge, leading to diminished quality of life. Emerging evidence suggests that sustained mitochondrial dysfunction may constitute a pivotal pathophysiological basis for the development and progression of SAW, primarily encompassing five key aspects: dysregulated mitochondrial quality control (MtQC), impaired oxidative phosphorylation (OXPHOS), exacerbated oxidative stress, disrupted Ca²⁺; homeostasis, and their mediation of diverse myofiber injuries. This article systematically elucidates the central role of mitochondrial dysfunction in the pathogenesis of SAW. Furthermore, we explore potential therapeutic strategies targeting mitochondrial function, including mitigating mitochondrial oxidative stress, optimizing nutritional support, and supplementing with muscle-derived mesenchymal stem cells. These insights provide a critical theoretical framework for understanding SAW mechanisms and developing clinical interventions, with particular emphasis on the translational value of mitochondrial-targeted therapies in improving outcomes for septic patients.
Humans ; Sepsis/metabolism* ; Mitochondria/metabolism* ; Muscle Weakness/etiology* ; Oxidative Stress ; Oxidative Phosphorylation

OBJECTIVE: CRISPR-Cas protects bacteria from exogenous DNA invasion and is associated with bacterial biofilm formation and pathogenicity. METHODS: We analyzed the type I-F CRISPR-Cas system of Legionella pneumophila WX48, including Cas1, Cas2-Cas3, Csy1, Csy2, Csy3, and Cas6f, along with downstream CRISPR arrays. We explored the effects of the CRISPR-Cas system on the in vitro growth, biofilm-forming ability, and pathogenicity of L. pneumophila through constructing gene deletion mutants. RESULTS: The type I-F CRISPR-Cas system did not affect the in vitro growth of wild-type or mutant strains. The biofilm formation and intracellular proliferation of the mutant strains were weaker than those of the wild type owing to the regulation of type IV pili and Dot/Icm type IV secretion systems. In particular, Cas6f deletion strongly inhibited these processes. CONCLUSION The type I-F CRISPR-Cas system may reduce biofilm formation and intracellular proliferation in L. pneumophila.
Legionella pneumophila/pathogenicity* ; CRISPR-Cas Systems ; Biofilms/growth & development* ; Phenotype ; Bacterial Proteins/metabolism* ; Gene Deletion

AIM To explore the clinical effects of Huayu Ditan Linao Decoction combined with Suhexiang Pills on elderly patients with cerebral hemorrhage in convalescent stage.METHODS One hundred and ten patients were randomly assigned into control group(55 cases)for 1-month intervention of both conventional treatment and rehabilitation training,and observation group(55 cases)for 1-month intervention of Huayu Ditan Linao Decoction,Suhexiang Pills,conventional treatment and rehabilitation training.The changes in clinical effects,TCM syndrome score,NIHSS score,FMA score,BI index,cerebrovascular function indices(dynamic resistance,average flow velocity,peripheral resistance,average flow rate),serum inflammatory indices(IL-6,hs-CPR,TNF-α)and serum oxidative stress indices(SOD,MDA)were detected.RESULTS The observation group demonstrated higher total effective rate than the control group(P＜0.05).After the treatment,the two groups displayed decreased TCM syndrome score,NIHSS score,dynamic resistance,peripheral resistance,serum inflammatory indices,MDA(P＜0.05),and increased FMA score,BI index,average flow velocity,average flow rate,SOD(P＜0.05),especially for the observation group(P＜0.05).CONCLUSION For the elderly patients with cerebral hemorrhage in convalescent stage,Huayu Ditan Linao Decoction combined with Suhexiang Pills can enhance clinical effects,improve limb functions and nerve functions,regulate serum inflammatory and oxidative stress indice,and promote prognosis.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

A method for simultaneous determination of 21 kinds of Aconitum alkaloids(ATS)in biological specimens and infused liquor using ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)was developed.The biological samples were pretreated with methanol-acetonitrile(1∶2,V/V)for protein precipitation,while infused liquors were diluted 100-fold with acetonitrile,followed by centrifugation,and filtration by a 0.22-μm membrane.Chromatographic separation was carried out on an EC-C18 column using gradient elution with the mixture of 10 mmol/L ammonium acetate and 0.2%formic acid as mobile phase A and acetonitrile as mobile phase B.With this method,all the analytes were separated within 9.5 min.The samples were detected in positive ESI mode with dynamic multiple reaction monitoring(MRM)and quantified via external standard calibration.The results showed that the concentrations of the analytes in the range of 2-1000 ng/mL had excellent linearity(R2>0.9992)with the peak area.The developed method was successfully used for detection of 21 kinds of aconitum alkaloids,with limits of detection of 0.5-2 ng/mL,quantification limits of 2-6 ng/mL,intra/inter-day precision≤6.0%,spiked recoveries of 89.4%-100.9%,extraction recoveries of 74.2%-104.4%,and matrix effects ranging from-11.1%to 9.2%in blood/urine.The method was applied to detection of 12 samples from 4 fatal aconite poisoning cases,and all 21 kinds of ATS with total alkaloid concentrations of 0.04-4.18 μg/mL in blood and 154.96-422.83 μg/mL in medicinal liquors were detected.Tissue distribution revealed that the order of concentrations from highest to lowest is as follows:urine(157.22 μg/mL)>gastric contents(51.37 μg/mL)>kidney(21.6 μg/g)>whole blood(4.18 μg/mL)>liver(0.03 μg/g).This method showed many advantages such as simple pretreatment,low detection limits,accurate quantification,broad analyte coverage,and superior anti-interference capability in complex matrices,proving ideal for forensic and toxicological analysis of aconitum alkaloids.

Coronavirus,a major pathogen infecting humans,mammals,and birds,causes primarily respiratory diseases af-ter infecting humans.Seven coronaviruses have been found to infect humans and subsequently cause varying degrees of respira-tory symptoms.From 2019 to 2023,millions of people died from severe acute respiratory syndrome coronavirus 2 infections,and the virus continues to mutate.Therefore,drug screening research must urgently be expanded to develop more effective,broad-spectrum anti-coronavirus drugs.In-depth research has indicated that the coronavirus 3C-like protease and RNA polymer-ase are necessary for viral reproduction and are highly conserved among strains,and consequently are anti-virus targets of great interest.This article summarizes the enzymes encoded by coronaviruses and drug screening methods,to provide a reference for coronavirus prevention and control.

Aim To explore the mechanism of Cong Rong San on AD model rats based on protein kinase R-like endoplasmic reticulum kinase(PERK)-eukaryotic initiation factor 2α(eIF2α)-nuclear factor kappa B(NF-κB)signaling pathway.Methods Sixty mice were randomly divided into normal group,model group,Cong Rong San groups(4.62,9.24,18.48 g·kg-1)and donepezil group,with 10 mice in each group.All groups of rats received bilateral hippocampal injections of Aβ1-42 to establish the AD model,except the normal group.After the intragastric administration,the Morris water maze behavior test was performed for rats to test-ed the learning and memory abilities.Nissl staining was detected the quantity and Nissl bodies of nerve cells.To detect the nuclear translocation of NF-κB by immu-nofluorescence.To observe the ultrastructure of endo-plasmic reticulum by Transmission electron microsco-py.ELISA for Aβ1-42 and inflammatory cytokines quantification.Western blot was used to detect the ex-pression level of protein in the hippocampus in PERK-eIF2α-NF-κB signaling pathway.Results The morris water maze results showed that Cong Rong San im-proved the escape latency time,increased the number of platform crossings,and prolonged the time spent in the target quadrant in AD rats.(P＜0.05 or P＜0.01).Nissl staining shows the neuronal cells are ar-ranged neatly,nucleus are present and the number of Nissl bodies was numerous and the number of neurons was increased in various doses of Cong Rong San.Im-munofluorescence showed that the expression of NF-κB in the nucleus of rats was decreased(P＜0.05 or P＜0.01).The shape of endoplasmic reticulum was neat,no significantly expanded,and the structure was normal in various doses of Cong Rong San.The levels of Aβ1-42,IL-1,TNF-α and the ratio of p-PERK/PERK,p-eIF2α/eIF2α,p-NF-κB p65/NF-κB p65 in hippo-campus of Cong Rong San group was significantly de-creased in ELISA and Western blot test(P＜0.05 or P＜0.01).Conclusion Cong Rong San can alleviates the immune inflammatory response of neuronal cells in the ERS state for improve the learning and memory a-bility of AD rats,the mechanism of action may through restraint the activation of PERK-eIF2α-NF-κB signa-ling pathway.

Objective To propose a precise suctioning scheme for intravenous drug dispensing based on the vial dispensing robot to enhance the quality of finished infusion.Methods Six kinds of typical representative vial drugs were selected as the research objects,including pantoprazole sodium for injection,papaverine hydrochloride for injection,cefuroxime sodium for injection,Bozhi Glycopeptide Injection,Esomeprazole Sodium for Injection and Methylprednisolone Sodium Succinate for injection.The optimal suction speed was determined by studying the relationship between the size parameters of vials and the suction speed of robot dispensing,which was used to carry out drug dispensing with the vial dispensing robot to verify whether the minimum drug residue could be obtained with the speed.The drug residue was compared with that by manual dispensing.SPSS 24.0 and Excel 2021 were applied to statistical analysis.Results The optimal suction efficiency and minimized drug residue could be got with the depth of the syringe needle hole into the rubber plug(X)less than the height of the rubber plug(H)and the optimal suction speed(Vs)of 7.48 mm/s;the suction efficiency could be ensured without air drawn in when X not less than H and Vs ranging from 10.64 to 39.31 mm/s.The mean values of the drug residue by the robot were all lower than those by manual dispensing,with the differences being statistically significant(P<0.05).Conclusion The proposed scheme can be used for optimizing the parameters of the vial vial dispensing robot to obtain infusion solution with high stability and reliability,which promotes standardization and normalization of intravenous infusion dispensing process.[Chinese Medical Equipment Journal,2025,46(9):45-51]