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.

Objective To quantitatively assess the exposure-response association between exposure to heatwave and sudden death, estimate the attributable excess deaths, and identify potential vulnerable subgroups. Methods A time-stratified case-crossover study was conducted among residents who died from sudden death in Jiangsu Province, China between 2015 and 2021. Heatwave events in Jiangsu Province, defined using varying relative temperature thresholds and durations, were identified using temperature data from the China Meteorological Administration Land Data Assimilation System (CLDAS V2.0). Individual heatwave exposure was assessed based on each subject's residential address. The exposure-response association between heatwave and sudden death was evaluated using conditional logistic regression model combined with a Distributed Lag Nonlinear Model(DLNM). Heatwave-attributable excess deaths were estimated. Stratified analyses by sex and age were performed to assess potential effect modifications. Results Under all definitions, exposure to heatwave was significantly associated with an increased risk of sudden death, and the risk increased with the intensity of heatwave. Using the P95_3d definition (temperature exceeding the 95th percentile for ≥3 consecutive days), heatwave was significantlyassociated with a 56% increased risk of sudden death (95% CI: 31%, 86%). The population-attributable fraction of sudden death due to heatwave exposure was 1.45% (95% CI: 0.97%, 1.90%). Stratified analyses indicated no statistically significant differences in the association between heatwave exposure and sudden death across age or sex subgroups. Conclusion Heatwave exposure was associated with an increased risk of sudden death. Reducing heatwave exposure during summer may help lower the occurrence of sudden death.

Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.

Objective: To explore the impact of adverse childhood experiences (ACEs) on health risk behaviors (HRBs) among college students and the mediating role of psychological symptoms, so as to provide a basis for developing intervention strategies. Methods: From March to April 2023, a convenience cluster sample of 1 801 students from 12 universities in Nanning, Liuzhou, Guilin, Wuzhou of Guangxi completed an online survey. A self designed questionnaire, Adverse Childhood Experiences-International Questionnaire (ACE-IQ) and Symptom Checklist-90 (SCL-90) were used for evaluation tools. Binary Logistic regression, structural equation modeling (SEM) and Bootstrap methods were used to analyze the associations and mediating effects. Results: Overall, 71.2% of college students experienced at least one type of ACE, with emotional neglect (40.3%) and emotional abuse ( 25.2 %) having the highest detection rates. The top three HRBs were unhealthy diet (77.8%), physical inactivity (54.1%), and smoking/alcohol use (18.5%). Logistic regression showed that poor family functioning, abuse, and extra familial violence were each associated with an increased risk of smoking/alcohol use ( OR =1.14, 1.11, 1.18) and deliberate self harm ( OR =1.26, 1.19,1.30) (all P <0.05). Experience of abuse increased the risk of high risk sexual behavior and family dysfunction increaded the risk of physical inactivity, respectively ( OR = 1.07 , 1.04, both P <0.05). Mediation analysis revealed that anxiety ( β =0.20) and depression ( β = 0.09 ) partially mediated the pathway from poor family functioning to deliberate self harm; paranoia ( β =0.02) partially mediated the pathway from abuse to high risk sexual behavior; and obsessive-compulsive symptoms ( β =0.26) and depression ( β =0.10) partially mediated the pathway from extra familial violence to deliberate self harm (all P <0.05). Conclusion Psychological symptoms play a mediating role in the association between ACEs and HRBs, and mental health interventions may reduce the risk of HRBs among college students.

Chronic obstructive pulmonary disease（COPD）， characterized primarily by persistent airflow limitation and chronic airway inflammation， is a major chronic respiratory disease with persistently high morbidity and mortality. In recent years， macrophage pyroptosis， as an inflammatory form of programmed cell death， has been recognized as playing a key role in amplifying inflammatory responses and promoting tissue damage. According to traditional Chinese medicine（TCM） theory， spleen failing to disperse essence constitutes an important pathological basis for various chronic diseases， clinically manifesting as impaired transportation and transformation， internal generation of phlegm-dampness， and accumulation of turbid toxins. Based on a review of classical TCM pathogenesis and modern molecular biological research， this study proposes that there may be a correlation between spleen failing to disperse essence and macrophage pyroptosis in the pathogenesis of COPD. Specifically， metabolic and immune disturbances such as glucotoxicity， lipotoxicity， and enterotoxicity may trigger macrophage pyroptosis through the advanced glycation end products（AGEs）/AGEs receptor（RAGE）/reactive oxygen species（ROS）， fatty acids/Toll-like receptor 4（TLR4）， and lipopolysaccharide（LPS）/nuclear transcription factor-κB（NF-κB）/NOD-like receptor protein 3（NLRP3） signaling pathways. Excessive pyroptosis， in turn， exacerbates metabolic dysregulation and inflammatory responses， forming a vicious cycle. Furthermore， TCM interventions such as strengthening the spleen and tonifying Qi， as well as resolving dampness and detoxifying， have demonstrated potential in modulating pyroptosis-related signaling pathways， including NF-κB， the NLRP3 inflammasome， and autophagy. In summary， this article explores the role of spleen failing to disperse essence-macrophage pyroptosis mechanism in COPD and highlights possible therapeutic strategies of TCM， providing new insights for integrated Chinese and western medical research and clinical practice.

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.

ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

Objective To investigate the predictive value of dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)radiomics combined with Magee equation 3(ME3)for pathological response following neoadjuvant chemotherapy(NAC)in patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative(HR+/HER2-)breast cancer.Methods A ret-rospective analysis was performed on 325 breast cancer patients diagnosed with HR+/HER2-in two hospitals.Patients from the first hospital were randomly divided into training and internal validation sets at a ratio of 7∶3.Patients from the second hospital served as external validation set.The volume of interest(VOI)of breast cancer was delineated on DCE-MRI images.Then the rele-vant radiomics features were extracted and selected,and the Radiomics score(Radscore)was calculated.The statistically significant clinical and pathological features and Radscore were incorporated into a multivariate analysis.The combined radiomics-clinical model and nomogram were established,and the prediction performance was evaluated by using the receiver operating characteristic(ROC)curve,calibration curve,and decision curve analysis(DCA).Results In the training set,seven radiomics features were selected to construct the radiomics model.ME3 score emerged as the independent factor for pathological complete response(pCR)(P＜0.001).By integrating ME3 score and Radscore,a combined radiomics-clinical model was developed.This model demonstrated robust predictive accuracy,with area under the curve(AUC)of 0.88[95％confidence interval(CI)0.80-0.95],0.90(95％CI 0.82-0.98),and 0.82(95％CI 0.70-0.93)in the training,internal validation,and external validation sets,respectively.The nomogram construc-ted from the combined model exhibited excellent discrimination and calibration,with P-values of 0.455,0.312 and 0.062 in the train-ing,internal validation,and external validation sets.Conclusion DCE-MRI radiomics combined with ME3 can be used to predict the pathological response of NAC in HR+/HER2-breast cancer.

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.