BACKGROUND:In China,the patient population with osteonecrosis is large,and there is an urgent need to find new preventive targets to develop more effective treatment strategies.Metabolomics studies have shown that there is an association between human metabolites and osteonecrosis,but the causal relationship between blood metabolites and osteonecrosis has not yet been clarified.OBJECTIVE:To investigate the causal relationship between blood metabolites and osteonecrosis through two-sample Mendelian randomization analysis.METHODS:The public data of 486 blood metabolites(exposure factors)and osteonecrosis(outcome factors)were collected.Data of 486 blood metabolites were derived from a genome-wide association estimate for blood metabolites published in Nature Genetics in 2014,which covered 7 824 European adults.The single nucleotide polymorphism data for osteonecrosis were obtained from the FinnGen public database R11 dataset,containing information on a total of 431 614 samples and 21 306 430 single nucleotide polymorphism loci,with 1 788 cases of osteonecrosis and 429 826 controls,with all participants being of European descent.Mendelian randomization analysis(inverse variance weighting method,MR-Egger method,and weighted median method)was performed by Rstudio software,and then the heterogeneity test,horizontal pleiotropy test and Steiger directionality test were performed to ensure the robustness and reliability of the results.RESULTS AND CONCLUSION:(1)Sixteen blood metabolites were identified as having a significant causal relationship with osteonecrosis(Pinverse variance weighting＜Pfalse discovery rate＜0.05).(2)Eight blood metabolites increased the risk of osteonecrosis(including four known metabolites and four unknown metabolites),specifically pantothenate,beta-hydroxyisovalerate,hippurate,salicyluric glucuronide,X-08766,X-11452,X-12776 and X-14662.(3)Eight blood metabolites could reduce the risk of osteonecrosis(six known metabolites and two unknown metabolites),including cortisol,1-palmitoylglycerol(1-monopalmitin),pyroglutamyl glycine,2-stearoylglycerophosphocholine,p-cresol sulfate,ergothioneine,X-06307,X-12092.(4)The above results suggest that there is a causal relationship between 16 blood metabolites and osteonecrosis,which is expected to be a potential target for intervention in the occurrence and treatment of osteonecrosis in the future.(5)Despite the lack of relevant data from large-scale Asian populations at present,this study provides important reference value for the field of osteonecrosis in China based on European population data.In the future,domestic medical workers may be able to achieve precise intervention for osteonecrosis by regulating metabolite levels.In addition,based on the results of this study,relevant researchers can further explore the mechanism of action of metabolites in the treatment of osteonecrosis with traditional Chinese medicine,which not only helps to deepen the understanding of traditional Chinese medical therapies but also promotes the progress of integrated traditional Chinese and Western medicine research,driving the development of personalized treatment plans that are more suitable for the characteristics of the Chinese population.

BACKGROUND:In China,the patient population with osteonecrosis is large,and there is an urgent need to find new preventive targets to develop more effective treatment strategies.Metabolomics studies have shown that there is an association between human metabolites and osteonecrosis,but the causal relationship between blood metabolites and osteonecrosis has not yet been clarified.OBJECTIVE:To investigate the causal relationship between blood metabolites and osteonecrosis through two-sample Mendelian randomization analysis.METHODS:The public data of 486 blood metabolites(exposure factors)and osteonecrosis(outcome factors)were collected.Data of 486 blood metabolites were derived from a genome-wide association estimate for blood metabolites published in Nature Genetics in 2014,which covered 7 824 European adults.The single nucleotide polymorphism data for osteonecrosis were obtained from the FinnGen public database R11 dataset,containing information on a total of 431 614 samples and 21 306 430 single nucleotide polymorphism loci,with 1 788 cases of osteonecrosis and 429 826 controls,with all participants being of European descent.Mendelian randomization analysis(inverse variance weighting method,MR-Egger method,and weighted median method)was performed by Rstudio software,and then the heterogeneity test,horizontal pleiotropy test and Steiger directionality test were performed to ensure the robustness and reliability of the results.RESULTS AND CONCLUSION:(1)Sixteen blood metabolites were identified as having a significant causal relationship with osteonecrosis(Pinverse variance weighting＜Pfalse discovery rate＜0.05).(2)Eight blood metabolites increased the risk of osteonecrosis(including four known metabolites and four unknown metabolites),specifically pantothenate,beta-hydroxyisovalerate,hippurate,salicyluric glucuronide,X-08766,X-11452,X-12776 and X-14662.(3)Eight blood metabolites could reduce the risk of osteonecrosis(six known metabolites and two unknown metabolites),including cortisol,1-palmitoylglycerol(1-monopalmitin),pyroglutamyl glycine,2-stearoylglycerophosphocholine,p-cresol sulfate,ergothioneine,X-06307,X-12092.(4)The above results suggest that there is a causal relationship between 16 blood metabolites and osteonecrosis,which is expected to be a potential target for intervention in the occurrence and treatment of osteonecrosis in the future.(5)Despite the lack of relevant data from large-scale Asian populations at present,this study provides important reference value for the field of osteonecrosis in China based on European population data.In the future,domestic medical workers may be able to achieve precise intervention for osteonecrosis by regulating metabolite levels.In addition,based on the results of this study,relevant researchers can further explore the mechanism of action of metabolites in the treatment of osteonecrosis with traditional Chinese medicine,which not only helps to deepen the understanding of traditional Chinese medical therapies but also promotes the progress of integrated traditional Chinese and Western medicine research,driving the development of personalized treatment plans that are more suitable for the characteristics of the Chinese population.

Sigma-1 receptor (σ ₁R) has become a focus point of drug discovery for central nervous system (CNS) diseases. A series of novel 1-phenylethan-1-one O-(2-aminoethyl) oxime derivatives were synthesized. In vitro biological evaluation led to the identification of 1a, 14a, 15d and 16d as the most high-affinity (K _i < 4 nmol/L) and selective σ ₁R agonists. Among these, 15d, the most metabolically stable derivative exhibited high selectivity for σ ₁R in relation to σ ₂R and 52 other human targets. In addition to low CYP450 inhibition and induction, 15d also exhibited high brain permeability and excellent oral bioavailability. Importantly, 15d demonstrated effective antipsychotic potency, particularly for alleviating negative symptoms and improving cognitive impairment in experimental animal models, both of which are major challenges for schizophrenia treatment. Moreover, 15d produced no significant extrapyramidal symptoms, exhibiting superior pharmacological profiles in relation to current antipsychotic drugs. Mechanistically, 15d inhibited GSK3β and enhanced prefrontal BDNF expression and excitatory synaptic transmission in pyramidal neurons. Collectively, these in vivo proof-of-concept findings provide substantial experimental evidence to demonstrate that modulating σ ₁R represents a potential new therapeutic approach for schizophrenia. The novel chemical entity along with its favorable drug-like and pharmacological profile of 15d renders it a promising candidate for treating schizophrenia.

Objective To develop a toolkit suitable for assisting community health institutions in the early identification and inter-vention of mild cognitive impairment(MCI)among older adults.Methods A literature review was conducted to construct a draft of the identification and intervention toolkit.Tools with an expert approval rate above 70%were included after expert consultation.The final version of the toolkit was developed by integrating these tools with officially recommended tools in China.Results The expert consultation yielded an authority coefficient of 0.84.The finalized toolkit included the assessment tools of Mini-Mental State Examination,Montreal Cognitive Assessment,General Practitioner Assessment of Cognition,Cognitive Abilities Screening Instrument and Clock Drawing Test,and 18 intervention measures in-cluding pharmacological treatment,cognitive training and psychological interventions,etc.Conclusion The MCI Identification-Intervention Toolkit may serve as a reference for guiding the identification and inter-vention of MCI among older adults for community health institutions.

Objective:To explore the value of a scoring system based on preoperative abdominal computed tomography (CT) for predicting the difficulty of laparoscopic cholecystectomy (LC).Methods:A retrospective analysis was conducted on 105 patients diagnosed with gallstones or cholecystitis who underwent LC at Beijing Jishuitan Hospital, Capital Medical University from January 2021 and February 2022. Based on surgical video reviews, patients were divided into the easy group ( n=58) and the difficult group ( n=47) according to the intraoperative Parkland Grading Scale (PGS), with PGS grades 1-2 assigned to the easy group, and PGS grades 3-5 assigned to the difficult group. The normally distributed measurement data were expressed as mean±standard deviation ( ± s), and compared using independent samples t-test; the non-normally distributed measurement data were expressed as median (interquartile range) [ M ( Q1, Q3)], and compared using the rank-sum test. The count data were expressed as the number of cases and percentage, and compared using the Chi-square test or Fisher exact probability method. Univariate analysis and cut-off value determination: for continuous CT variables, univariate Logistic regression and stepwise regression analyses (with surgical difficulty grouping as the dependent variable) were performed to identify the optimal combination of predictive variables and establish a scoring system. For each significantly associated continuous variable or important CT image feature from a clinical perspective, receiver operating characteristic (ROC) curve analysis was used to evaluate its predictive performance for difficult surgery. The area under the curve (AUC) was calculated, and the optimal cut-off value was determined using the Youden index to maximize the sum of sensitivity and specificity. The categorical CT image features were scored according to their original groups. The Kappa consistency test was used to assess the strength of agreement between the preoperative abdominal CT score (grouped by the optimal cut-off) and PGS grades (easy/difficult). Decision curve analysis (DCA) was employed to validate the predictive performance of the model. Results:Stepwise Logistic regression identified seven key imaging features as the optimal predictive variables for constructing the preoperative abdominal CT scoring system: maximum gallbladder cross-sectional diameter, maximum gallbladder cross-sectional width, gallbladder wall thickness, common bile duct diameter, pericholecystic fat stranding, periductal fat stranding, and impacted cystic duct stones. Each case was scored after assigning scores based on the optimal cut-off values. The total score of the preoperative abdominal CT scoring system was ≥3 points predicted difficult LC with an AUC of 0.745 (95% CI: 0.650-0.839), sensitivity of 66.0%, and specificity of 75.9%. DCA confirmed the model′s reliable predictive performance, and the preoperative abdominal CT scoring system showed good agreement with PGS grades ( Kappa value was 0.420, P<0.001). Conclusions:The preoperative abdominal CT scoring system based on pericholecystic imaging features can effectively predict the difficulty of LC with good discriminative ability. It provides a quantitative tool for preoperative assessment, surgical scheduling, and ambulatory surgery management.

Background Under the background of global warming, research on association between ambient temperature and risk of injury is needed. Objective To examine the effect of temperature on injury in Bao'an district, Shenzhen and identify the sensitive population, thereby providing a scientific basis for formulating prevention and control strategies and measures of injury. Methods The injury reports from the Injury Surveillance System and the meteorological data of Bao'an District between 2018 to 2022 were collected. The meteorological data were sourced from the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) land reanalysis data. Based on time-stratified case-crossover design, conditional logistic regression combined with distributed lag nonlinear model was used to evaluate the exposure-response association between ambient temperature and injury. The stratified analyses were further conducted by gender, age, and causes of injury. Results A total of 156205 injury cases were collected from the injury surveillance sentinel hospitals in Bao'an District of Shenzhen from 2018 to 2022, and the median of daily average temperature during the same period was 20.0 ℃. The exposure-response curve showed that the risk of injury was positively correlated with temperature. The linearized analysis revealed that each 1°C increase in temperature was associated with a 1.05% (95%CI: 0.68%, 1.42%) rise in injury risk (ER). Notably, the effect was greater in females (ER=1.31%, 95%CI: 0.67%, 1.94%) than males (ER=0.92%, 95%CI: 0.47%, 1.37%). Among age groups, adults ＞60 years faced the highest risk (ER=1.91%, 95%CI: −0.36%, 4.24%). The top three temperature-associated injury risks were sharp instrument injuries (ER=2.19%, 95%CI: 1.16%, 3.22%), animal injuries (ER=1.71%, 95%CI: 0.86%, 2.56%), and blunt injuries (ER=071%, 95%CI: −0.08%, 1.51%). The impact of temperature on unintentional injuries (ER=1.11%, 95%CI: 0.72%, 1.49%) was higher than that on intentional injuries (ER=0.43%, 95%CI: −0.85%, 1.72%). Severe injuries (ER=2.20%, 95%CI: −3.09%, 7.77%) were more affected by temperature than mild injuries (ER=1.00%, 95%CI: 0.58%, 1.43%) and moderate injuries (ER=1.15%, 95%CI: 0.42%, 1.89%). Conclusion The increase in ambient temperature associates with injury occurrence, and the impact of temperature exhibits obvious heterogeneity among different populations, indicating that targeted intervention measures should be taken for different populations and types of injuries.

BACKGROUND:Hormonal osteonecrosis of the femoral head is strongly associated with aging,but the regulatory targets and mechanisms are still unclear.Through bioinformatics combined with machine learning analysis and experimental verification,the key genes of hormonal osteonecrosis of the femoral head mediated by cell senescence will be identified,which will provide new ideas for the prevention and treatment of hormonal osteonecrosis of the femoral head.OBJECTIVE:To screen and validate the senescence core genes of hormonal osteonecrosis of the femoral head using bioinformatics analysis to explore its mechanism of action.METHODS:The GSE123568 dataset was obtained from the GPL15207 platform of the GEO database,which contained the gene expression profiles of peripheral serum samples of 30 hormonal osteonecrosis of the femoral head patients and 10 healthy controls.Data on 279 cellular senescence-related genes were obtained from the CellAge database.Differential analysis and weighted correlation network analysis(WGCNA)were performed on hormonal osteonecrosis of the femoral head gene profiles,and both were intersected with senescence-related genes and then concatenated to obtain hormonal osteonecrosis of the femoral head senescence potential genes,and GO and KEGG analyses were performed.The machine learning method screened out the pivotal genes,constructed nomogram model,and performed consensus clustering and immune infiltration analysis.Finally,clinical femoral samples were collected for validation by qPCR and western blot assay.RESULTS AND CONCLUSION:(1)41 potential genes were obtained,which were mainly enriched in biological processes such as aging and oxidative stress response,as well as FoxO and tumor necrosis factor signaling pathways.(2)The pivotal genes catalase,connective tissue growth factor,forkhead box protein O3,insulin receptor substrate 2,and mitogen-activated protein kinase kinase 11 were obtained after machine learning identification,and the predictive ability of nomogram model was good.(3)The patients were classified into three groups,namely a,b and c,by the consensus clustering analysis.Catalase,forkhead box protein O3,insulin receptor substrate 2,and mitogen-activated protein kinase kinase 11 were differentially expressed among the three molecular subtypes(P＜0.05).Results of immune infiltration showed that the abundance of immune cells,such as activated CD4+T cells,activated CD8+T cells,and eosinophils,differed among the three molecular subclasses(P＜0.05).(4)The results of qPCR and western blot assay showed that the expression of catalase,connective tissue growth factor,forkhead box protein O3,and mitogen-activated protein kinase kinase 11 was lower in hormonal osteonecrosis of the femoral head group compared to the control group(P＜0.05),and the expression of insulin receptor substrate 2 was elevated(P＜0.05).(5)It is concluded that through in-depth analysis combined with bioinformatics and machine learning,and further experimental verification,five hormonal osteonecrosis of the femoral head age-related hub genes were finally identified.These genes are catalase,connective tissue growth factor,forkhead box o3,insulin receptor substrate 2,and serine/threonine kinase 11.These genes may provide potential molecular targets for the prevention and treatment of hormonal osteonecrosis of the femoral head in the future by regulating the cellular aging process.

Objective To establish a rat model of venous thrombosis in a plateau hypobaric hypoxic environment and to investigate the effect of this environment on venous thrombosis.Methods A total of 144 healthy male SD rats were assigned randomly to four groups(n=36 rats per group):a plains sham operation(A)group,plains operation(B)group,plateau altitude 6000 m+sham operation(C)group,and plateau altitude 6000 m+surgery(D)group.Rats in A and B groups were maintained in a plains normoxic environment,while rats in C and D groups C and D were subjected to a plateau environment.Rats in the surgical groups underwent quantitative constriction to incompletely obstruct the inferior vena cava blood flow.Each group was further divided into subgroups based on time:1,3,5,7,14,and 21 d(n=6 rats per group).Regular vascular ultrasound monitoring was conducted,and blood samples were taken for whole blood viscosity testing and the assessment of inflammatory indicators,including endothelin-1(ET-1),interleukin-6(IL-6)and tissue factor(TF).Coagulation function was evaluated through the activated partial thromboplastin time(APTT),prothrombin time(PT),thrombin time(TT),fibrinogen(FIB)and D-dimer.After the observation period,the experimental animals were sacrificed and the limbs were removed.Thrombus samples were stained with hematoxylin/eosin(HE),and the thrombus wet mass was measured.Results The thrombosis incidence was significantly higher in the plateau D group than in B group,accompanied by a marked increase in blood viscosity and hematocrit(P＜0.01).Additionally,levels of ET-1,IL-6,and TF were significantly elevated(P＜0.05),indicating a coagulation disorder.Conclusions A plateau hypoxic environment model can be successfully simulated by quantitative coarctation of the inferior vena cava,combined with a specialized environmental chamber.The findings of this study suggest that a plateau hypoxic environment promotes venous thrombosis.

Objective To develop a toolkit suitable for assisting community health institutions in the early identification and inter-vention of mild cognitive impairment(MCI)among older adults.Methods A literature review was conducted to construct a draft of the identification and intervention toolkit.Tools with an expert approval rate above 70%were included after expert consultation.The final version of the toolkit was developed by integrating these tools with officially recommended tools in China.Results The expert consultation yielded an authority coefficient of 0.84.The finalized toolkit included the assessment tools of Mini-Mental State Examination,Montreal Cognitive Assessment,General Practitioner Assessment of Cognition,Cognitive Abilities Screening Instrument and Clock Drawing Test,and 18 intervention measures in-cluding pharmacological treatment,cognitive training and psychological interventions,etc.Conclusion The MCI Identification-Intervention Toolkit may serve as a reference for guiding the identification and inter-vention of MCI among older adults for community health institutions.

BACKGROUND:Hormonal osteonecrosis of the femoral head is strongly associated with aging,but the regulatory targets and mechanisms are still unclear.Through bioinformatics combined with machine learning analysis and experimental verification,the key genes of hormonal osteonecrosis of the femoral head mediated by cell senescence will be identified,which will provide new ideas for the prevention and treatment of hormonal osteonecrosis of the femoral head.OBJECTIVE:To screen and validate the senescence core genes of hormonal osteonecrosis of the femoral head using bioinformatics analysis to explore its mechanism of action.METHODS:The GSE123568 dataset was obtained from the GPL15207 platform of the GEO database,which contained the gene expression profiles of peripheral serum samples of 30 hormonal osteonecrosis of the femoral head patients and 10 healthy controls.Data on 279 cellular senescence-related genes were obtained from the CellAge database.Differential analysis and weighted correlation network analysis(WGCNA)were performed on hormonal osteonecrosis of the femoral head gene profiles,and both were intersected with senescence-related genes and then concatenated to obtain hormonal osteonecrosis of the femoral head senescence potential genes,and GO and KEGG analyses were performed.The machine learning method screened out the pivotal genes,constructed nomogram model,and performed consensus clustering and immune infiltration analysis.Finally,clinical femoral samples were collected for validation by qPCR and western blot assay.RESULTS AND CONCLUSION:(1)41 potential genes were obtained,which were mainly enriched in biological processes such as aging and oxidative stress response,as well as FoxO and tumor necrosis factor signaling pathways.(2)The pivotal genes catalase,connective tissue growth factor,forkhead box protein O3,insulin receptor substrate 2,and mitogen-activated protein kinase kinase 11 were obtained after machine learning identification,and the predictive ability of nomogram model was good.(3)The patients were classified into three groups,namely a,b and c,by the consensus clustering analysis.Catalase,forkhead box protein O3,insulin receptor substrate 2,and mitogen-activated protein kinase kinase 11 were differentially expressed among the three molecular subtypes(P＜0.05).Results of immune infiltration showed that the abundance of immune cells,such as activated CD4+T cells,activated CD8+T cells,and eosinophils,differed among the three molecular subclasses(P＜0.05).(4)The results of qPCR and western blot assay showed that the expression of catalase,connective tissue growth factor,forkhead box protein O3,and mitogen-activated protein kinase kinase 11 was lower in hormonal osteonecrosis of the femoral head group compared to the control group(P＜0.05),and the expression of insulin receptor substrate 2 was elevated(P＜0.05).(5)It is concluded that through in-depth analysis combined with bioinformatics and machine learning,and further experimental verification,five hormonal osteonecrosis of the femoral head age-related hub genes were finally identified.These genes are catalase,connective tissue growth factor,forkhead box o3,insulin receptor substrate 2,and serine/threonine kinase 11.These genes may provide potential molecular targets for the prevention and treatment of hormonal osteonecrosis of the femoral head in the future by regulating the cellular aging process.