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.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

Objective To explore the longitudinal associations of body roundness index (BRI), visceral adiposity index (VAI), and metabolic score for visceral fat (METS-VF) with the risk of new-onset atrial fibrillation (AF). Methods This study included participants from the UK Biobank who were free of AF or pregnancy at baseline and completed the first and second assessments of BRI, VAI, and METS-VF. The changes in BRI, VAI, and METS-VF were classified using K-means clustering analyses, and the cumulative adiposity indices were also calculated. The primary outcome was new-onset AF. Three Cox regression models were employed to investigate the longitudinal associations of the BRI, VAI, and METS-VF changes with the risk of incident new-onset AF. The results were presented as hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs). Restricted cubic spline analyses were performed to explore potential non-linear associations between baseline or cumulative adiposity indices and the risk of new-onset AF. C-index analyses were conducted to evaluate the predictive value of BRI, VAI, and METS-VF for new-onset AF. Subgroup analyses were performed according to age, gender, race, smoking status, alcohol consumption, and physical activity. Polygenic risk scores were applied to account for genetic susceptibility and investigate potential interactions between adiposity indices and genetic risk. Univariate linear regression analyses were performed to evaluate the relationships of cumulative adiposity indices and magnetic resonance imaging and dual X-ray absorptiometry parameters, including visceral adipose tissue (VAT) volume, VAT mass, trunk fat volume, and trunk fat mass. We further applied the eXtreme Gradient Boosting (XGBoost) algorithm, with the feature importance being measured to evaluate the predictive value of each adiposity index for imaging parameters. Mendelian randomization analysis was further conducted to investigate the potential causal relationship between trunk fat mass and AF. Results A total of 12 776 participants were included. Over a median follow-up of 9.60 years, 761 (5.96%) new-onset AF events were recorded. Participants were divided into four classes based on the changes in adiposity indices. In the fully adjusted model, compared to participants in Class 1 of BRI, those in Class 3 (HR＝1.30, 95%CI 1.04-1.63, P＝0.023) and Class 4 (HR＝2.17, 95%CI 1.61-2.93, P＜0.001) were associated with significantly higher risks of new-onset AF. Regarding METS-VF, participants in Class 4 of METS-VF also demonstrated a significantly higher risk of new-onset AF compared to those in Class 1 (HR＝1.66, 95%CI 1.15-2.39, P＝0.007). However, no significant association was observed between different classes of VAI and the risk of new-onset AF. For every 1 standard deviation increase in cumulative BRI, VAI, and METS-VF, the fully adjusted HRs of new-onset AF were 1.23 (95%CI 1.13-1.35), 1.02 (95%CI 0.94-1.10), and 1.23 (95%CI 1.12-1.35), respectively. Cumulative adiposity indices (BRI, VAI, and METS-VF) were divided into quartiles. Using the first quartile as reference, participants in the highest quartiles of BRI (HR＝1.40, 95%CI 1.10-1.79, P＝0.007) and METS-VF (HR＝1.44, 95%CI 1.13-1.83, P＝0.003) both exerted a significantly higher risk of new-onset AF. Regarding VAI, no significant association was observed (HR＝1.00, 95%CI 0.81-1.23, P＝0.988). Restricted cubic spline analyses revealed non-linear relationships between cumulative BRI, baseline/cumulative VAI, and baseline/cumulative METS-VF with new-onset AF risk (all P_overall＜0.05, P_non-linear＜0.05). In the C-index analysis, BRI demonstrated the highest predictive performance for new-onset AF, followed by METS-VF and VAI. Subgroup analysis indicated a stronger association between METS-VF and the risk of new-onset AF amongst participants younger than 60 years (P_interaction＝0.008). Polygenic risk score analysis stratified by genetic risk demonstrated a synergistic effect between BRI and genetic risk with new-onset AF, with the overall risk of new-onset AF increasing as both BRI and genetic risk increased. Linear regression analysis revealed a positive correlation between cumulative BRI with VAT volume, VAT mass, trunk fat volume, and trunk fat mass. The feature importance plot derived from the XGBoost algorithm indicated that cumulative BRI had the greatest predictive value on VAT volume, VAT mass, trunk fat volume, and trunk fat mass. Mendelian randomization analysis confirmed a significant causal relationship between trunk fat mass and AF. Conclusions There are significant non-linear associations between BRI, METS-VF, and VAI with new-onset AF. Higher BRI and METS-VF are significantly associated with a higher risk of new-onset AF, whereas no significant association is observed for the VAI. BRI exhibits a positive correlation with VAT and trunk fat, and demonstrates superior performance in predicting new-onset AF compared to VAI and METS-VF. Monitoring and managing BRI may be important in the early detection and intervention of AF.

Objective To investigate the mediating role of anxiety and depression in social sup-port and burnout among primary caregivers of stroke patients.Methods A convenience sampling method was employed to select 506 primary caregivers of stroke patients as research subjects.The Gen-eral Information Questionnaire,Caregiver Burnout Inventory for Stroke Patients,Multidimensional Scale of Perceived Social Support,and Hospital Anxiety and Depression Scale were used for data col-lection.Results The total scores for caregiver burnout,social support,anxiety,and depression a-mong primarycaregivers of stroke patients were(72.83±14.32),(47.79±7.74),(10.49±3.00),and(10.45±3.06),respectively.Correlation analysis revealed a negative correlation between caregiver burnout and social support(r=-0.245,P＜0.001),and positive correlations with anxiety and depression(r=0.178,0.216,P＜0.001).Anxiety and depression partially media-ted the relationship between social support and caregiver burnout,accounting for 7.9％and 10.7％of the total effect,respectively.Conclusion Social support,anxiety,depression,and burnout are closely interrelated.Social support can directly or indirectly influence the occurrence of burnoutthrough anxiety and depression.Medical staff should pay attention to the anxiety and depression status of primary caregivers of stroke patients and enhance social support levels to reduce the incidence of burnout by alleviating anxiety and depression.

Objective:This study aimed to retrospectively analyze the incidence and influencing factors of tricuspid regurgitation (TR) in the short term after pacemaker lead implantation at the Second Affiliated Hospital of Zhejiang University School of Medicine, so as to provide evidence for understanding pacemaker lead-related TR.Methods:Consecutive patients who underwent single- or dual-chamber permanent pacemaker implantation between June 2019 and December 2023 in the Department of Cardiology were enrolled. General clinical data and relevant parameters were collected. Changes in TR severity before and shortly after the procedure were assessed using echocardiography. TR progression was defined as an increase by one grade or more, and TR improvement as a decrease by one grade or more. Logistic regression analysis was employed to identify factors associated with TR progression.Results:A total of 219 patients were included (128 males, 91 females), with a mean age of 69.7 ± 11.2 years. The median follow-up time was 99 (26, 199) days. TR remained unchanged in 114 patients (52.1%), improved in 46 (21.0%)—including 36 (16.4%) with one-grade reduction, 9 (4.1%) with two-grade reduction, and 1 (0.5%) with three-grade reduction—and progressed in 59 patients (26.9%). Among those with progression, 51 (23.3%) had mild-to-moderate TR worsening by one grade, and 8 (3.7%) had moderate or worse TR worsening by at least two grades. Notably, one case involved lead perforation of the leaflet and two cases had lead impingement. Compared with the non-progression group ( n = 114), pacemaker indication (AV block vs. sick sinus syndrome), baseline left atrial diameter, pulmonary artery systolic pressure (PASP), and the severity of mitral regurgitation (MR) and TR were significantly associated with TR progression or improvement (all P < 0.05). Ordinal logistic regression analysis identified preoperative TR severity [ OR=10.57 (3.77–29.68), P < 0.001] and pacemaker indication [ OR=0.452 (0.222–0.918), P = 0.028] as independent predictors of postoperative TR progression. Patients with AV block were more likely to receive left bundle branch pacing ( P < 0.001), which may contribute to their lower risk of TR. Conclusions:Short-term progression of TR after pacemaker implantation is relatively common, although severe TR remains rare. Preoperative TR severity and pacemaker indication are independent predictors of short-term TR progression. The use of physiological pacing modalities may help reduce the incidence of TR following pacemaker lead implantation.

Objective To explore the longitudinal associations of body roundness index(BRI),visceral adiposity index(VAI),and metabolic score for visceral fat(METS-VF)with the risk of new-onset atrial fibrillation(AF).Methods This study included participants from the UK Biobank who were free of AF or pregnancy at baseline and completed the first and second assessments of BRI,VAI,and METS-VF.The changes in BRI,VAI,and METS-VF were classified using K-means clustering analyses,and the cumulative adiposity indices were also calculated.The primary outcome was new-onset AF.Three Cox regression models were employed to investigate the longitudinal associations of the BRI,VAI,and METS-VF changes with the risk of incident new-onset AF.The results were presented as hazard ratios(HRs)and the corresponding 95%confidence intervals(CIs).Restricted cubic spline analyses were performed to explore potential non-linear associations between baseline or cumulative adiposity indices and the risk of new-onset AF.C-index analyses were conducted to evaluate the predictive value of BRI,VAI,and METS-VF for new-onset AF.Subgroup analyses were performed according to age,gender,race,smoking status,alcohol consumption,and physical activity.Polygenic risk scores were applied to account for genetic susceptibility and investigate potential interactions between adiposity indices and genetic risk.Univariate linear regression analyses were performed to evaluate the relationships of cumulative adiposity indices and magnetic resonance imaging and dual X-ray absorptiometry parameters,including visceral adipose tissue(VAT)volume,VAT mass,trunk fat volume,and trunk fat mass.We further applied the eXtreme Gradient Boosting(XGBoost)algorithm,with the feature importance being measured to evaluate the predictive value of each adiposity index for imaging parameters.Mendelian randomization analysis was further conducted to investigate the potential causal relationship between trunk fat mass and AF.Results A total of 12 776 participants were included.Over a median follow-up of 9.60 years,761(5.96%)new-onset AF events were recorded.Participants were divided into four classes based on the changes in adiposity indices.In the fully adjusted model,compared to participants in Class 1 of BRI,those in Class 3(HR=1.30,95%CI 1.04-1.63,P=0.023)and Class 4(HR=2.17,95%CI 1.61-2.93,P＜0.001)were associated with significantly higher risks of new-onset AF.Regarding METS-VF,participants in Class 4 of METS-VF also demonstrated a significantly higher risk of new-onset AF compared to those in Class 1(HR=1.66,95%CI 1.15-2.39,P=0.007).However,no significant association was observed between different classes of VAI and the risk of new-onset AF.For every 1 standard deviation increase in cumulative BRI,VAI,and METS-VF,the fully adjusted HRs of new-onset AF were 1.23(95%CI 1.13-1.35),1.02(95%CI 0.94-1.10),and 1.23(95%CI 1.12-1.35),respectively.Cumulative adiposity indices(BRI,VAI,and METS-VF)were divided into quartiles.Using the first quartile as reference,participants in the highest quartiles of BRI(HR=1.40,95%CI 1.10-1.79,P=0.007)and METS-VF(HR=1.44,95%CI 1.13-1.83,P=0.003)both exerted a significantly higher risk of new-onset AF.Regarding VAI,no significant association was observed(HR=1.00,95%CI 0.81-1.23,P=0.988).Restricted cubic spline analyses revealed non-linear relationships between cumulative BRI,baseline/cumulative VAI,and baseline/cumulative METS-VF with new-onset AF risk(all Poverall＜0.05,Pnon-linear＜0.05).In the C-index analysis,BRI demonstrated the highest predictive performance for new-onset AF,followed by METS-VF and VAI.Subgroup analysis indicated a stronger association between METS-VF and the risk of new-onset AF amongst participants younger than 60 years(Pinteraction=0.008).Polygenic risk score analysis stratified by genetic risk demonstrated a synergistic effect between BRI and genetic risk with new-onset AF,with the overall risk of new-onset AF increasing as both BRI and genetic risk increased.Linear regression analysis revealed a positive correlation between cumulative BRI with VAT volume,VAT mass,trunk fat volume,and trunk fat mass.The feature importance plot derived from the XGBoost algorithm indicated that cumulative BRI had the greatest predictive value on VAT volume,VAT mass,trunk fat volume,and trunk fat mass.Mendelian randomization analysis confirmed a significant causal relationship between trunk fat mass and AF.Conclusions There are significant non-linear associations between BRI,METS-VF,and VAI with new-onset AF.Higher BRI and METS-VF are significantly associated with a higher risk of new-onset AF,whereas no significant association is observed for the VAI.BRI exhibits a positive correlation with VAT and trunk fat,and demonstrates superior performance in predicting new-onset AF compared to VAI and METS-VF.Monitoring and managing BRI may be important in the early detection and intervention of AF.

Probiotics are natural systems bridging synthetic biology, physical biotechnology, and immunology, initiating innate and adaptive anti-tumor immune activity. We previously constructed an all-in-one engineered food-grade probiotic Lactococcus lactis (FOLactis) which could boost the crosstalk among different immune cells such as dendritic cells (DCs), natural killer cells, and T cells. Herein, considering the limited clinical efficacy of naked personalized neoantigen peptide vaccines, we decorate FOLactis with tumor antigens by employing a Plug-and-Display system comprising membrane-inserted peptides. Intranodal injection of FOLactis coated with neoantigen peptides (Ag-FOLactis) induces robust DCs presentation and neoantigen-specific cellular immunity. Notably, Ag-FOLactis not only triggers a 45-fold rise in the quantity of locally reactive neoantigen-specific T cells but also induces epitope spreading in both subcutaneous and metastatic tumor-bearing models, leading to potent inhibition of tumor growth. These findings imply that Ag-FOLactis represents a powerful platform to rapidly and easily display antigens, facilitating the development of a bio-activated platform for personalized therapy.

Metformin has been demonstrated to attenuate hyperglycaemia by modulating the gut microbiota. However, the mechanisms through which the microbiome mediates metformin monotherapy failure (MMF) are unclear. Herein, in a prospective clinical cohort study of newly diagnosed type 2 diabetes mellitus (T2DM) patients treated with metformin monotherapy, metagenomic sequencing of faecal samples revealed that Phocaeicola vulgatus abundance was approximately 12 times higher in nonresponders than in responders. P. vulgatus rapidly hydrolysed taurine-conjugated bile acids, leading to ceramide accumulation and reversing the improvements in glucose intolerance conferred by metformin in high-fat diet-fed mice. Interestingly, C22:0 ceramide bound to mitochondrial fission factor to induce mitochondrial fragmentation and impair hepatic oxidative phosphorylation in P. vulgatus-colonized hyperglycaemic mice, which could be exacerbated by metformin. This work suggests that metformin may be unsuitable for P. vulgatus-rich T2DM patients and that clinicians should be aware of metformin toxicity to mitochondria. Suppressing P. vulgatus growth with cefaclor or improving mitochondrial function using adenosylcobalamin may represent simple, safe, effective therapeutic strategies for addressing MMF.

Myocardial fibrosis is a serious cause of heart failure and even sudden cardiac death. However, the mechanisms underlying myocardial ischemia-induced cardiac fibrosis remain unclear. Here, we identified that the expression of sterile alpha and TIR motif containing 1 (SARM1), was increased significantly in the ischemic cardiomyopathy patients, dilated cardiomyopathy patients (GSE116250) and fibrotic heart tissues of mice. Additionally, inhibition or knockdown of SARM1 can improve myocardial fibrosis and cardiac function of myocardial infarction (MI) mice. Moreover, SARM1 fibroblasts-specific knock-in mice had increased deposition of extracellular matrix and impaired cardiac function. Mechanically, elevated expression of SARM1 promotes the deposition of extracellular matrix by directly modulating P4HA1. Notably, by using the Click-iT reaction, we identified that the increased expression of ZDHHC17 promotes the palmitoylation levels of SARM1, thereby accelerating the fibrosis process. Based on the fibrosis-promoting effect of SARM1, we screened several drugs with anti-myocardial fibrosis activity. In conclusion, we have unveiled that palmitoylated SARM1 targeting P4HA1 promotes collagen deposition and myocardial fibrosis. Inhibition of SARM1 is a potential strategy for the treatment of myocardial fibrosis. The sites where SARM1 interacts with P4HA1 and the palmitoylation modification sites of SARM1 may be the active targets for anti-fibrosis drugs.

With the rapid advancement of synthetic biology, CRISPR-Cas systems have emerged as a powerful tool for gene editing, demonstrating significant potential in various fields, including medicine, agriculture, and industrial biotechnology. This review comprehensively summarizes the significant progress in applying artificial intelligence (AI) technologies to the design, mining, and modification of CRISPR-Cas systems. AI technologies, especially machine learning, have revolutionized sgRNA design by analyzing high-throughput sequencing data, thereby improving the editing efficiency and predicting off-target effects with high accuracy. Furthermore, this paper explores the role of AI in sgRNA design and evaluation, highlighting its contributions to the annotation and mining of CRISPR arrays and Cas proteins, as well as its potential for modifying key proteins involved in gene editing. These advancements have not only improved the efficiency and precision of gene editing but also expanded the horizons of genome engineering, paving the way for intelligent and precise genome editing.
CRISPR-Cas Systems/genetics* ; Artificial Intelligence ; Gene Editing/methods* ; RNA, Guide, CRISPR-Cas Systems/genetics* ; Machine Learning ; Humans ; Genetic Engineering/methods* ; Synthetic Biology