Objective: To explore the relationship between non suicidal self injury (NSSI) behavior and serum lipid levels as well as thyroid function among college students with depression. Methods: A total of 169 college students with depression in the psychiatry departments of tertiary hospitals (grade 3A and 3B) in Ningbo from December 2023 to April 2025 were selected. The Adolescent Self injury Scale (ASIS) was used to assess the presence of NSSI, and participants were accordingly divided into a NSSI group ( n =51) and a non NSSI group ( n =118). General demographic data (including gender, age, and family situation) were collected from both groups. Blood tests were performed to measure lipid profiles [triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C)] and thyroid hormones [triiodothyronine (T3), thyroxine (T4), free triiodothyronine (FT3), free thyroxine (FT4), thyroid stimulating hormone (TSH)]. Multivariate Logistic regression was employed to analyze risk factors for NSSI, and receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive value of serum lipid and thyroid hormone levels for NSSI occurrence in college students with depression. Results: The levels of TC, LDL-C, and TSH in the NSSI group were (4.02±0.73) mmol/L, (2.32±0.36) mmol/L, and (6.57±1.95) mU/L , which were significantly higher than those in the non NSSI group [(3.41±0.56) mmol/L, (2.00±0.27) mmol/L, and ( 4.48± 1.09) mU/L, respectively] ( t =5.32, 5.60, 7.20, all P <0.05). Logistic regression analysis revealed that college students from single parent/reconstituted families, those who had experienced school bullying, and those with higher levels of TC, LDL-C, and TSH had a significantly increased risk of engaging in NSSI ( OR =5.22, 6.12, 5.90, 83.64, 3.64, all P <0.05). ROC curve analysis demonstrated that the combined detection of TC, LDL-C, and TSH had high diagnostic efficacy for predicting NSSI in college students with depression, with a sensitivity of 86.3% and a specificity of 94.9%. Conclusions NSSI behavior in college students with depression is associated with serum lipid levels and thyroid function. These biomarkers may serve as useful reference indicators for assessing the conditions of these patients.

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 The relationship between blood pressure variability(BPV)and short-term neurological prognosis in patients with aneurysmal subarachnoid hemorrhage(aSAH)was investigated.Methods The study conducted a retrospective analysis of clinical data from aSAH patients who underwent surgical treatment and were admitted to the ICU at Beijing Tiantan Hospital,Capital Medical University,from January 2023 to April 2024.BPV was quantitively assessed by calculating the standard deviation(SD),successive variation(SV),coefficient of variation(CV),and range of mean blood pressure(MBP).Patients were divided into two group based on discharge GOS scores:good prognosis[Glasgow Outcome Scale(GOS)4-5]and poor prognosis(GOS 1-3)groups.Comparative analyses were performed to evaluate differences in BPV metrics between the two groups,followed by multivariable logistic regression modeling to adjust for potential confounding factors and elucidate the association between BPV and clinical prognosis.Results A total of 150 patients were included,with 59 in the poor prognosis group and 91 in the good prognosis group.The poor prognosis group exhibited significantly elevated levels of MBP-SD[(9.85±3.20)mmHg vs.(8.04±2.31)mmHg,P<0.001],MBP-SV[(10.37±3.85)mmHg vs.(8.07±2.33)mmHg,P<0.001],MBP-CV(10.00±3.30%vs.8.19±2.33%,P<0.001),and MBP-range[(39.60±13.56)mmHg vs.(32.44±9.78)mmHg,P<0.05]compared to the good prognosis group.Cohen’s d values indicated moderate effect sizes for BPV differences(0.65,0.72,0.63,and 0.61,respectively).Multivariable logistic regression showed that MBP-SD(OR=1.22,95%CI:1.08-1.39,P=0.002)and MBP-SV(OR=1.19,95%CI:1.05-1.35,P=0.007)were independently associated with poor prognosis.Conclusion Elevated MBP-SD and MBP-SV within the first 24 hours postoperative period are independent predictors of unfavorable short-term neurological outcomes in aSAH patients.

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

Objective To investigate the relationship between serum platelet-activating factor (PAF) level, T cell immune function and disease activity in vitiligo patients. Methods A total of 102 patients with vitiligo treated in our hospital from July 18th, 2022 to July 26th, 2023 were enrolled as study subjects. According to VIDA score, the patients were divided into an advanced-stage group (n=54) and a stable stage group (n=49). PAF and T lymphocyte levels were compared between the two groups. Logistic regression analysis was performed to examine the relationship between PAF levels and disease activity, as well as their correlation with T cell subsets. Unconditional logistic regression modeling was employed to analyze the interaction between PAF levels and T cell subsets in disease activity. Results No significant difference was observed in CD3⁺ levels between advanced and stable stage vitiligo patients. PAF and CD8⁺ levels in advanced group were significantly higher than those in stable group, while CD4⁺ levles and CD4⁺/CD8⁺ ratios were significantly lower than those in stable group. When PAF level was 18.24 ng/L, the maximum Youden index reached 0.670, with corresponding sensitivity of 84.22% and specificity of 82.77%. The area under ROC curve AUC was 0.858. The intensity of association between PAF level and disease activity was nonlinear dose-response relationship. Among patients with VIDA score ≥1, significant differences were observed in both CD4⁺ and CD8⁺ levels across different PAF levels, and the CD4⁺/CD8⁺ ratios in vitiligo patients with different VIDA scores was significantly different. Interaction analysis revealed that after adjusting for confounding factors, the effect of PAF levels and T cell subsets on disease activity in vitiligo patients showed significant interaction in both additive model (RERI=4.674, 95%CI: 1.032~11.942; AP=0.763, 95%CI: 0.336~1.201; S=6.854, 95%CI: 1.904~16.520) and multiplicative model (OR=3.461, 95%CI: 1.365~8.713). Conclusion Serum PAF, CD4⁺, CD8⁺ and CD4⁺/CD8⁺ of vitiligo patients are closely related to disease activity, and PAF level interacts with T cell subsets (CD4⁺, CD8⁺, CD4⁺/CD8⁺) in the disease activity of vitiligo patients. PAF and T cell immune function may contribute to the occurrence and development of vitiligo, which could serve as clinical indicators of disease activity to guide timely management.
Humans ; Vitiligo/blood* ; Platelet Activating Factor/immunology* ; Male ; Female ; Adult ; Middle Aged ; Young Adult ; T-Lymphocytes/immunology* ; Adolescent ; T-Lymphocyte Subsets/immunology*

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.

Objective:To compare the diagnostic efficacy of 68Ga-prostate-specific membrane antigen (PSMA)-617 PET/CT and multiparametric magnetic resonance imaging (mpMRI) in detecting extraprostatic extension (EPE) and seminal vesicle invasion (SVI) in prostate cancer. Methods:A retrospective analysis was conducted on the clinical data of 113 patients with localized prostate cancer who underwent both 68Ga-PSMA-617 PET/CT and mpMRI at Xiangya Hospital, Central South University, from May 2018 to May 2024 prior to radical prostatectomy (RP). The median age of the patients was 66.0 (61.3, 71.0) years old, with a median body mass index of 28.86 (19.01, 24.77) kg/m 2, and a median prostate-specific antigen (PSA) level of 13.50(9.26, 21.99) ng/ml. The pathological results after RP were used as the gold standard to compare the sensitivity, specificity, positive predictive value, and negative predictive value of the two imaging modalities in diagnosing EPE and SVI. Additionally, the diagnostic value of combining both imaging modalities was explored, employing a parallel strategy where a positive result from either modality was deemed positive, and only when both tests were negative was the result considered negative. Results:Pathological results after RP indicated EPE in 46 cases (40.71%) and SVI in 11 cases (9.70%). In diagnosing EPE, the sensitivity, specificity, positive predictive value, and negative predictive value of 68Ga-PSMA-617 PET/CT were 17.39% (8/46), 97.01% (65/67), 80.00% (8/10), and 63.11% (65/103), respectively, while for mpMRI they were 34.78% (16/46), 83.58% (56/67), 59.26% (16/27), and 65.12% (56/86), respectively. The sensitivity of mpMRI was significantly higher than that of 68Ga-PSMA-617 PET/CT ( P=0.048), while the specificity was the opposite ( P=0.008). When combining both imaging modalities, the sensitivity, specificity, positive predictive value, and negative predictive value were 45.65% (21/46), 80.60% (54/67), 61.76% (21/34), and 68.35% (54/79), respectively. In diagnosing SVI, the sensitivity, specificity, positive predictive value, and negative predictive value of 68Ga-PSMA-617 PET/CT were 27.27% (3/11), 96.08% (98/102), 42.86% (3/7), and 92.45% (98/106), respectively, while for mpMRI they were 36.36% (4/11), 88.24% (90/102), 25.00% (4/16), and 92.78% (90/97), respectively. The specificity of 68Ga-PSMA-617 PET/CT was significantly higher than that of mpMRI ( P=0.033). When combining both imaging modalities, the sensitivity, specificity, positive predictive value, and negative predictive value were 45.45% (5/11), 85.29% (87/102), 25.00% (5/20), and 93.55% (87/93), respectively. Conclusions:mpMRI has higher sensitivity in diagnosing EPE and SVI in prostate cancer, while 68Ga-PSMA-617 PET/CT shows higher specificity. The combined use of both imaging modalities can increase diagnostic sensitivity but may reduce specificity. PSMA PET/MRI may be a more accurate diagnostic tool for discerning EPE and SVI.

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.

Objective To investigate the influencing factors and Traditional Chinese Medical(TCM)syndrome classification of skin pruritus in patients with maintenance hemodialysis(MHD).Methods A total of 174 hemodialysis patients who underwent regular dialysis in Zhejiang Chinese Medical University Affiliated Jiaxing TCM Hospital from July to September 2024 were selected as study subjects.According to the presence or absence of uremic pruritus(UP),they were divided into pruritus group(n=66)and non-pruritus group(n=108).Both groups of patients were classified into TCM syndromes,and the factors affecting skin pruritus in MHD patients were analyzed by Logistic regression analysis and an evaluation model was established.The evaluation efficiency of the model was evaluated by receiver operating characteristic curve.The relationship between TCM syndromes and pruritus degree was analyzed.Results Both groups of patients were mainly characterized by spleen and kidney Qi deficiency,and the difference was statistically significant(P＜0.05).Logistic regression analysis showed that β2 microglobulin(β2-MG),blood phosphorus,hyper-sensitive C-reactive protein and parathyroid hormone(PTH)were all risk factors for skin pruritus in MHD patients.The area under the curve of skin pruritus in MHD patients was 0.962(95％CI:0.930-0.995).The underlying syndrome of UP patients was mainly spleen and kidney Qi deficiency,and marked syndrome was mainly blood deficiency and wind-dryness.Conclusion β2-MG,blood phosphorus,hyper-sensitive C-reactive protein and PTH are closely related to the occurrence of skin pruritus in MHD patients.The TCM syndrome of UP patients is mainly characterized by spleen and kidney Qi deficiency,and syndrome of blood deficiency and wind-dryness is mainly characterized by UP patients,and there is a certain correlation between TCM syndrome classification and the degree of skin pruritus.

Objective The relationship between blood pressure variability(BPV)and short-term neurological prognosis in patients with aneurysmal subarachnoid hemorrhage(aSAH)was investigated.Methods The study conducted a retrospective analysis of clinical data from aSAH patients who underwent surgical treatment and were admitted to the ICU at Beijing Tiantan Hospital,Capital Medical University,from January 2023 to April 2024.BPV was quantitively assessed by calculating the standard deviation(SD),successive variation(SV),coefficient of variation(CV),and range of mean blood pressure(MBP).Patients were divided into two group based on discharge GOS scores:good prognosis[Glasgow Outcome Scale(GOS)4-5]and poor prognosis(GOS 1-3)groups.Comparative analyses were performed to evaluate differences in BPV metrics between the two groups,followed by multivariable logistic regression modeling to adjust for potential confounding factors and elucidate the association between BPV and clinical prognosis.Results A total of 150 patients were included,with 59 in the poor prognosis group and 91 in the good prognosis group.The poor prognosis group exhibited significantly elevated levels of MBP-SD[(9.85±3.20)mmHg vs.(8.04±2.31)mmHg,P<0.001],MBP-SV[(10.37±3.85)mmHg vs.(8.07±2.33)mmHg,P<0.001],MBP-CV(10.00±3.30%vs.8.19±2.33%,P<0.001),and MBP-range[(39.60±13.56)mmHg vs.(32.44±9.78)mmHg,P<0.05]compared to the good prognosis group.Cohen’s d values indicated moderate effect sizes for BPV differences(0.65,0.72,0.63,and 0.61,respectively).Multivariable logistic regression showed that MBP-SD(OR=1.22,95%CI:1.08-1.39,P=0.002)and MBP-SV(OR=1.19,95%CI:1.05-1.35,P=0.007)were independently associated with poor prognosis.Conclusion Elevated MBP-SD and MBP-SV within the first 24 hours postoperative period are independent predictors of unfavorable short-term neurological outcomes in aSAH patients.