ObjectiveTo establish a tumor prognostic risk assessment model related to target genes of the miR-34 family. MethodsTarget genes of the miR-34 family were screened， and the scores of miR-34 target genes were assessed in 16 tumor types. Univariate Cox regression analysis was used to identify the tumor type with the strongest correlation between miR-34 target gene scores and overall survival （OS）. Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses were performed to elucidate the functional roles and signaling pathways of miR-34 target genes. A prognostic risk model based on the miR-34 target genes was constructed using univariate Cox and LASSO regression analyses. Quantitative real-time PCR （qPCR） and dual-luciferase reporter assays were conducted to validate whether the target genes bind to miR-34 and measure their RNA expression levels in the relevant tumors. Additionally， the risk score was integrated with other clinical indicators to develop a nomogram prediction model for patient survival. ResultsA total of 65 target genes of the miR-34 family were screened. The cancer type exhibiting stronger correlation between the target gene scores and OS was lung adenocarcinoma （P = 0.003， HR= 5.150）. Furthermore， miR-34 target genes were predominantly enriched in oxidative stress pathways and various tumor-related processes. Three genes， LDHA， GALNT7， and SATB2， were identified as core components of the prognostic analysis model for lung adenocarcinoma. Additionally， the constructed nomogram model demonstrated robust predictive performance. ConclusionThe risk model and prognosis model of lung adenocarcinoma constructed based on the key target genes of miR-34 have good predictive performance.

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.

ObjectiveAs a common lifestyle habit, alcohol consumption has a controversial association with the onset of Parkinson’s disease (PD). To demonstrate the correlation between alcohol consumption and PD and to identify associated genes, we integrated findings from clinical surveys, genomics, transcriptomics, and animal experiments. MethodsWe investigated the alcohol consumption rates (including both before and after disease onset) among 244 PD patients in China and 177 PD patients from the U.S. NHANES database. Mendelian randomization (MR) analysis was performed using genome-wide association study (GWAS) data for three alcohol-related traits and seven PD-related datasets from the MRC IEU OpenGWAS database. Transcriptomic data from the substantia nigra of PD patients were obtained from three GEO datasets (GSE7621, GSE20141, and GSE49036) to analyze RIT2 gene transcription. Finally, three groups of animal experiments (water/20% ethanol/20% liquor, with 4 C57BL/6J mice per group) were conducted to examine changes in brain RIT2 gene expression and transcriptomic profiles following alcohol consumption. ResultsThe alcohol consumption rates among PD patients in China and the U.S. (9%-18.87%) were significantly lower than the general population rates of 15%-45% in their respective regions (P<0.001), suggesting a possible negative association between alcohol consumption and PD. Subsequently, in 21 bidirectional MR analyses using 3 alcohol-related GWAS datasets and 7 PD-related GWAS datasets, the forward MR analyses (alcohol intake as exposure, PD as outcome) yielded 12 negative associations (OR_IVW<1) and 9 positive associations (OR_IVW>1). Among these, only two negative associations reached statistical significance: alcohol intake frequency (OR_IVW=0.75, 95% CI: 0.60-0.93, P=0.010) and alcohol consumption (OR_IVW=0.20, 95% CI: 0.05-0.83, P=0.026). The forward MR analysis (alcohol intake→PD) identified 235 SNPs, annotated to 316 genes, while the reverse MR analyses (PD→alcohol intake) identified 37 SNPs, annotated to 53 genes. Notably, only the RIT2 gene appeared in both the forward and reverse MR analyses (alcohol intake→PD: rs28597806, rs8083110; PD→alcohol intake: rs4588066). RIT2 is selectively expressed in the human brain (FPKM: 5.259±2.103), with low or no expression in peripheral tissues (FPKM: <1). Analysis of three human substantia nigra transcriptomic datasets revealed a decreasing trend in RIT2 gene expression in PD patients (GSE20141 array signal: 3.49±1.23 vs. 2.33±0.87, P=0.044). Animal experiments demonstrated that administration of 20% ethanol or 20% liquor (approximately 8% ethanol) stimulated a >2-fold upregulation of RIT2 gene expression in the mouse brain. Furthermore, transcriptomic sequencing revealed that the two alcohol-treated groups exhibited 96 (20% ethanol vs. water control) and 4 (20% liquor vs. water control) differentially expressed genes, respectively, indicating that low-dose alcohol consumption can achieve RIT2 upregulation while minimizing impact on other brain genes. In addition to its anti-infective effects, low-dose alcohol consumption primarily influences signaling pathways related to neurodegenerative diseases such as PD and Prion diseases. ConclusionAlcohol consumption is generally considered as a harmful lifestyle habit. However, some studies have also shown a lower risk of mortality among individuals who consume low doses of alcohol (100 g/week of ethanol) or drink occasionally. Currently, one of the research focuses on alcohol consumption is whether the human body can benefit from low-dose alcohol intake. This study provides new evidence supporting a negative association between alcohol consumption and PD, and for the first time, through MR analysis, identifies the RIT2 gene as a potential mediator of the effect of alcohol consumption on PD. RIT2 is selectively expressed in the human brain. Building upon existing evidence indicating downregulated RIT2 gene expression in PD pathogenesis, our experiments confirm that low-dose alcohol consumption can upregulate RIT2 expression in the brain. In brief, alcohol consumption may suppress the pathogenesis of PD by upregulating RIT2 expression in the substantia nigra. China is facing a serious problem of population aging. This study offers important insights for long-term PD prevention and treatment strategies, with the aim of benefiting more potential PD patients through lifestyle modifications, thereby improving the quality of life of the aging population and reducing the economic burden on healthcare.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

AIM:To observe the changes of atrial fibrillation susceptibility,and the remodeling of atrial myo-cyte action potential,ultrarapid activation delayed rectifier potassium current(IKur)and transient outward potassium cur-rent(Ito)in elderly mice,and to explore the mechanism of atrial fibrillation from the single cell electrophysiological level.METHODS:The C57BL/6J mice were divided into old group(20 months old)and young group(4 months old).Atrial fi-brillation was induced by esophageal atrial pacing.The atrial myocytes were isolated,and action potential and ion currents were recorded with patch-clamp technique.The associated proteins were detected by Western blot technique.RE-SULTS:(1)Compared with young mice,the total incidence of atrial fibrillation was significantly increased in old mice(20.0%at 4 months old vs 60.0%at 20 months old,P<0.01).(2)The action potential duration of atrial myocytes in aged mice was shortened,and more significantly after stimulation.(3)The density of Ito and IKur in atrial myocytes of aged mice increased significantly,from(12.6±1.4)pA/pF to(21.7±1.1)pA/pF,and from(7.5±1.5)pA/pF to(13.3±2.1)pA/pF,respectively(P<0.01).After stimulation,the current increased more significantly,especially in older atrial cells.Compared with the young mice,the steady-state activation curve of Ito in the atrial myocytes of the aged mice shifted towards the depolarization,suggesting that activation of Ito channels in the aged mice increased at the same voltage stimula-tion.(4)Compared with young group,the expression of KV4.2(generating Ito)and KV1.5(generating IKur)proteins in the atrial tissue of the mice in old group was significantly increased,and the expression of caveolin-3 and end-binding protein 1(EB1)was up-regulated,suggesting that the increases in KV4.2 and KV1.5 total channel proteins and effective proteins in the cell membrane might contribute to the increase in the remodeling of potassium currents in the elderly atrial myo-cytes.CONCLUSION:The incidence of atrial fibrillation in elderly mice is significantly augmented,which may be related to the increases in Ito and IKur in atrial myocytes.The remodeling of potassium currents in elderly atrial myocytes is one of the electrophysiological bases leading to the shortening of action potential duration and the occurrence of atrial fibrillation.

Objective:To investigate the hemodynamic characteristics of intracranial collateral circulation assessed non-invasively by TCD and their correlation with clinical prognosis in patients with severe carotid stenosis or occlusion.Methods:A retrospective cohort study design was used to include 96 patients with severe stenosis(≥70％)or occlusion of the unilateral internal carotid artery admitted from March 2021 to March 2024,who were divided into a well-compensated group(58 patients)versus a poorly-compensated group(38 patients)based on the ASITN/SIR collateral branch score.Hemodynamic parameters(PSV,EDV,MFV,PI,RI)were measured using TCD,and collateral circulation status was validated by digital subtraction angiography(DSA).Prognosis was evaluated over a 12-month follow-up.Logistic regression was used to analyze risk factors for poor prognosis.Results:The good collateral group exhibited significantly higher PSV(82.32±18.51 vs.56.45±15.32 cm/s)and MFV(56.93±12.33 vs.35.89±9.83 cm/s),and significantly lower PI(0.64±0.15 vs.0.82±0.21)and RI(0.43±0.08 vs.0.51±0.11)compared to the poor collateral group(all P＜0.001).TCD parameters showed strong correlations with ASITN/SIR grades(PSV:r=0.62;PI:r=-0.61,all P＜0.001).Multivariate analysis identified age ≥65 years(OR=1.06),hypertension(OR=3.07),PI ≥ 1.00(OR=17.25),and PSV ≤ 60 cm/s(OR=1.96)as independent risk factors for poor prognosis(all P＜0.05).Conclusion:The TCD multi-parameter model enables quantitative assessment of collateral circulation function,with PI ≥ 1.00 and PSV ≤ 60 cm/s serving as key predictors of adverse outcomes.The non-invasive and dynamic monitoring advantages of TCD provide critical insights for hemodynamic stratification and personalized intervention in patients with carotid stenosis or occlusion.

AIM:To observe the changes of atrial fibrillation susceptibility,and the remodeling of atrial myo-cyte action potential,ultrarapid activation delayed rectifier potassium current(IKur)and transient outward potassium cur-rent(Ito)in elderly mice,and to explore the mechanism of atrial fibrillation from the single cell electrophysiological level.METHODS:The C57BL/6J mice were divided into old group(20 months old)and young group(4 months old).Atrial fi-brillation was induced by esophageal atrial pacing.The atrial myocytes were isolated,and action potential and ion currents were recorded with patch-clamp technique.The associated proteins were detected by Western blot technique.RE-SULTS:(1)Compared with young mice,the total incidence of atrial fibrillation was significantly increased in old mice(20.0%at 4 months old vs 60.0%at 20 months old,P<0.01).(2)The action potential duration of atrial myocytes in aged mice was shortened,and more significantly after stimulation.(3)The density of Ito and IKur in atrial myocytes of aged mice increased significantly,from(12.6±1.4)pA/pF to(21.7±1.1)pA/pF,and from(7.5±1.5)pA/pF to(13.3±2.1)pA/pF,respectively(P<0.01).After stimulation,the current increased more significantly,especially in older atrial cells.Compared with the young mice,the steady-state activation curve of Ito in the atrial myocytes of the aged mice shifted towards the depolarization,suggesting that activation of Ito channels in the aged mice increased at the same voltage stimula-tion.(4)Compared with young group,the expression of KV4.2(generating Ito)and KV1.5(generating IKur)proteins in the atrial tissue of the mice in old group was significantly increased,and the expression of caveolin-3 and end-binding protein 1(EB1)was up-regulated,suggesting that the increases in KV4.2 and KV1.5 total channel proteins and effective proteins in the cell membrane might contribute to the increase in the remodeling of potassium currents in the elderly atrial myo-cytes.CONCLUSION:The incidence of atrial fibrillation in elderly mice is significantly augmented,which may be related to the increases in Ito and IKur in atrial myocytes.The remodeling of potassium currents in elderly atrial myocytes is one of the electrophysiological bases leading to the shortening of action potential duration and the occurrence of atrial fibrillation.

Objective:To investigate the hemodynamic characteristics of intracranial collateral circulation assessed non-invasively by TCD and their correlation with clinical prognosis in patients with severe carotid stenosis or occlusion.Methods:A retrospective cohort study design was used to include 96 patients with severe stenosis(≥70％)or occlusion of the unilateral internal carotid artery admitted from March 2021 to March 2024,who were divided into a well-compensated group(58 patients)versus a poorly-compensated group(38 patients)based on the ASITN/SIR collateral branch score.Hemodynamic parameters(PSV,EDV,MFV,PI,RI)were measured using TCD,and collateral circulation status was validated by digital subtraction angiography(DSA).Prognosis was evaluated over a 12-month follow-up.Logistic regression was used to analyze risk factors for poor prognosis.Results:The good collateral group exhibited significantly higher PSV(82.32±18.51 vs.56.45±15.32 cm/s)and MFV(56.93±12.33 vs.35.89±9.83 cm/s),and significantly lower PI(0.64±0.15 vs.0.82±0.21)and RI(0.43±0.08 vs.0.51±0.11)compared to the poor collateral group(all P＜0.001).TCD parameters showed strong correlations with ASITN/SIR grades(PSV:r=0.62;PI:r=-0.61,all P＜0.001).Multivariate analysis identified age ≥65 years(OR=1.06),hypertension(OR=3.07),PI ≥ 1.00(OR=17.25),and PSV ≤ 60 cm/s(OR=1.96)as independent risk factors for poor prognosis(all P＜0.05).Conclusion:The TCD multi-parameter model enables quantitative assessment of collateral circulation function,with PI ≥ 1.00 and PSV ≤ 60 cm/s serving as key predictors of adverse outcomes.The non-invasive and dynamic monitoring advantages of TCD provide critical insights for hemodynamic stratification and personalized intervention in patients with carotid stenosis or occlusion.

BACKGROUND:We have successfully established an animal model of small ear pig in southern Yunnan province with internal tension relieving technique combined with autologous Achilles tendon for anterior cruciate ligament reconstruction,and verified the stability and reliability of the model.However,whether internal tension relieving technique can promote the ligamentalization process of autologous Achilles tendon graft has not been studied. OBJECTIVE:To investigate the differences in the process of ligamentalization between conventional reconstruction and internal reduction reconstruction of the anterior cruciate ligament by gross view,histology and electron microscopy. METHODS:Thirty adult female small ear pigs in southern Yunnan province were selected.Anterior cruciate ligament reconstruction was performed on the left knee joint with the ipsilateral knee Achilles tendon(n=30 in the normal group),and anterior cruciate ligament reconstruction was performed on the right knee joint with the ipsilateral knee Achilles tendon combined with the internal relaxation and enhancement system(n=30 in the relaxation group).The autogenous right forelimb was used as the control group;the anterior cruciate ligament was exposed but not severed or surgically treated.At 12,24,and 48 weeks after surgery,10 animals were sacrificed,respectively.The left and right knee joint specimens were taken for gross morphological observation to evaluate the graft morphology.MAS score was used to evaluate the excellent and good rate of the ligament at each time point.Hematoxylin-eosin staining was used to evaluate the degree of ligament graft vascularization.Collagen fibers and nuclear morphology were observed,and nuclear morphology was scored.Ultrastructural remodeling was evaluated by scanning electron microscopy and transmission electron microscopy. RESULTS AND CONCLUSION:(1)The ligament healing shape of the relaxation group was better at various time points after surgery,and the excellent and good rate of MAS score was higher(P<0.05).Moreover,the relaxation group could obtain higher ligament vascularization score(P<0.05).(2)The arrangement of collagen bundles and fiber bundles in the two groups gradually tended to be orderly,and the transverse fiber connections between collagen gradually increased and thickened,suggesting that the strength and shape degree of the grafts were gradually improved,but the ligament remodeling in the relaxation group was always faster than that in the normal group at various time points after surgery.(3)The diameter,distribution density,and arrangement degree of collagen fibers in the relaxation group were better than those in the normal group at all time points,especially in the comparison of collagen fiber diameter between and within the relaxation group(P<0.05).

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.