BackgroundThe violent aggressive behaviors of patients with schizophrenia usually have the characteristics of suddenness， unpredictability， high severity， and great difficulty in prevention. Early identification and accurate assessment of their risk of violent aggression have significant clinical significance. ObjectiveTo construct a predictive model for the violence risk in hospitalized patients with schizophrenia， to identify the key factors influencing the occurrence of violent behavior in these patients， so as to provide references for clinical precise quantitative assessment and early intervention. MethodsA total of 200 patients with schizophrenia who were hospitalized at Taiyuan Psychiatric Hospital from March 2022 to September 2024 and met the diagnostic criteria of the International Classification of Diseases， eleventh edition （ICD-11） were collected to form the modeling cohort. They were randomly divided into a training set （n=140） and a test set （n=60） at a ratio of 7∶3. Based on the least absolute shrinkage and selection operator （LASSO） regression algorithm， the feature variables were screened and dimension-reduced. The support vector machine （SVM） from machine learning was selected for model training and prediction. The discrimination efficacy of the model was evaluated by the area under the receiver operating characteristic （ROC） curve （AUC）， accuracy， precision， sensitivity， specificity， F1 value， and Brier value. ResultsLASSO regression screening identified 16 feature variables. Pearson correlation analysis revealed a positive correlation between prior violent behavior frequency and clinical psychiatric symptom scores （r=0.580， P<0.01）， a positive correlation between hospitalization compliance and current disease status （r=0.550， P=0.003）， and a positive correlation between educational level and family per capita monthly income （r=0.367， P<0.01）. The SVM model achieved an AUC of 0.853， accuracy of 0.800， precision of 0.810， sensitivity of 0.895， specificity of 0.636， F1 value of 0.850， and Brier value of 0.168. ConclusionThe SVM model has a relatively high level of applicability and overall predictive performance in the assessment of violent risk in schizophrenia patients， which is helpful for the early identification of violent risks in such patients. ［Funded by Specialized Research Project for Enhancing the Competence of Health Professionals in Taiyuan City （number， Y2023006）］

Background/Aims: Metabolic dysfunction–associated steatotic liver disease (MASLD) is a chronic liver disease characterized by hepatic steatosis. Ubiquitin-specific protease 29 (USP29) plays pivotal roles in hepatic ischemiareperfusion injury and hepatocellular carcinoma, but its role in MASLD remains unexplored. Therefore, the aim of this study was to reveal the effects and underlying mechanisms of USP29 in MASLD progression. Methods: USP29 expression was assessed in liver samples from MASLD patients and mice. The role and molecular mechanism of USP29 in MASLD were assessed in high-fat diet-fed and high-fat/high-cholesterol diet-fed mice and palmitic acid and oleic acid treated hepatocytes. Results: USP29 protein levels were significantly reduced in mice and humans with MASLD. Hepatic steatosis, inflammation and fibrosis were significantly exacerbated by USP29 deletion and relieved by USP29 overexpression. Mechanistically, USP29 significantly activated the expression of genes related to fatty acid β-oxidation (FAO) under metabolic stimulation, directly interacted with long-chain acyl-CoA synthase 5 (ACSL5) and repressed ACSL5 degradation by increasing ACSL5 K48-linked deubiquitination. Moreover, the effect of USP29 on hepatocyte lipid accumulation and MASLD was dependent on ACSL5. Conclusions USP29 functions as a novel negative regulator of MASLD by stabilizing ACSL5 to promote FAO. The activation of the USP29-ACSL5 axis may represent a potential therapeutic strategy for MASLD.

Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

Background/Aims: Metabolic dysfunction–associated steatotic liver disease (MASLD) is a chronic liver disease characterized by hepatic steatosis. Ubiquitin-specific protease 29 (USP29) plays pivotal roles in hepatic ischemiareperfusion injury and hepatocellular carcinoma, but its role in MASLD remains unexplored. Therefore, the aim of this study was to reveal the effects and underlying mechanisms of USP29 in MASLD progression. Methods: USP29 expression was assessed in liver samples from MASLD patients and mice. The role and molecular mechanism of USP29 in MASLD were assessed in high-fat diet-fed and high-fat/high-cholesterol diet-fed mice and palmitic acid and oleic acid treated hepatocytes. Results: USP29 protein levels were significantly reduced in mice and humans with MASLD. Hepatic steatosis, inflammation and fibrosis were significantly exacerbated by USP29 deletion and relieved by USP29 overexpression. Mechanistically, USP29 significantly activated the expression of genes related to fatty acid β-oxidation (FAO) under metabolic stimulation, directly interacted with long-chain acyl-CoA synthase 5 (ACSL5) and repressed ACSL5 degradation by increasing ACSL5 K48-linked deubiquitination. Moreover, the effect of USP29 on hepatocyte lipid accumulation and MASLD was dependent on ACSL5. Conclusions USP29 functions as a novel negative regulator of MASLD by stabilizing ACSL5 to promote FAO. The activation of the USP29-ACSL5 axis may represent a potential therapeutic strategy for MASLD.

ObjectiveTo explore the construction of a machine learning model for the diagnosis of traditional Chinese medicine （TCM） syndromes in chronic cough and the optimization of this model using the Voting ensemble algorithm. MethodsA retrospective analysis was conducted using clinical data from 921 patients with chronic cough treated at the Respiratory Department of Dongfang Hospital， Beijing University of Chinese Medicine. After standardized processing， 84 clinical features were extracted to determine TCM syndrome types. A specialized dataset for TCM syndrome diagnosis in chronic cough was formed by selecting syndrome types with more than 50 cases. The synthetic minority over-sampling technique （SMOTE） was employed to balance the dataset. Four base models， logistic regression （LR）， decision tree （dt）， multilayer perceptron （MLP）， and Bagging， were constructed and integrated using a hard voting strategy to form a Voting ensemble model. Model performance was evaluated using accuracy， recall， precision， F1-score， receiver operating characteristic （ROC） curve， area under the curve （AUC）， and confusion matrix. ResultsAmong the 921 cases， six syndrome types had over 50 cases each， phlegm-heat obstructing the lung （294 cases）， wind pathogen latent in the lung （103 cases）， cold-phlegm obstructing the lung （102 cases）， damp-heat stagnating in the lung （64 cases）， lung yang deficiency （54 cases）， and phlegm-damp obstructing the lung （53 cases）， yielding a total of 670 cases in the specialized dataset. High-frequency symptoms among these patients included cough， expectoration， odor-induced cough， throat itchiness， itch-induced cough， and cough triggered by cold wind. Among the four base models， the MLP model showed the best diagnostic performance （test accuracy： 0.9104； AUC： 0.9828）. Compared with the base models， the Voting ensemble model achieved superior performance with an accuracy of 0.9289 on the training set and 0.9253 on the test set， showing a minimal overfitting gap of 0.0036. It also achieved the highest AUC （0.9836） in the test set， outperforming all base models. The model exhi-bited especially strong diagnostic performance for damp-heat stagnating in the lung （AUC： 0.9984） and wind pathogen latent in the lung （AUC： 0.9970）. ConclusionThe Voting ensemble algorithm effectively integrates the strengths of multiple machine learning models， resulting in an optimized diagnostic model for TCM syndromes in chronic cough with high accuracy and enhanced generalization ability.

Background/Aims: Metabolic dysfunction–associated steatotic liver disease (MASLD) is a chronic liver disease characterized by hepatic steatosis. Ubiquitin-specific protease 29 (USP29) plays pivotal roles in hepatic ischemiareperfusion injury and hepatocellular carcinoma, but its role in MASLD remains unexplored. Therefore, the aim of this study was to reveal the effects and underlying mechanisms of USP29 in MASLD progression. Methods: USP29 expression was assessed in liver samples from MASLD patients and mice. The role and molecular mechanism of USP29 in MASLD were assessed in high-fat diet-fed and high-fat/high-cholesterol diet-fed mice and palmitic acid and oleic acid treated hepatocytes. Results: USP29 protein levels were significantly reduced in mice and humans with MASLD. Hepatic steatosis, inflammation and fibrosis were significantly exacerbated by USP29 deletion and relieved by USP29 overexpression. Mechanistically, USP29 significantly activated the expression of genes related to fatty acid β-oxidation (FAO) under metabolic stimulation, directly interacted with long-chain acyl-CoA synthase 5 (ACSL5) and repressed ACSL5 degradation by increasing ACSL5 K48-linked deubiquitination. Moreover, the effect of USP29 on hepatocyte lipid accumulation and MASLD was dependent on ACSL5. Conclusions USP29 functions as a novel negative regulator of MASLD by stabilizing ACSL5 to promote FAO. The activation of the USP29-ACSL5 axis may represent a potential therapeutic strategy for MASLD.

BackgroundModified electroconvulsive therapy （MECT） is a common front-line strategy widely used in psychiatric practice， and the optimal first stimulus dosage in MECT is usually estimated clinically based on the factors influencing the patient's initial seizure threshold （IST）. However， previous studies on the influencing factors of IST have mostly suffered from limitations such as small sample sizes and single-dimensional research perspectives. ObjectiveTo explore the factors influencing IST in MECT for patients with mental disorders， so as to provide references for stimulus dosing strategies in MECT for the patients. MethodsA retrospective study was used to include 1 446 inpatients fulfilling the diagnostic criteria for any specific mental disorder listed in the ICD-10 and receiving MECT at Shandong Daizhuang Hospital from January 1， 2021 to August 1， 2023. Their general and clinical data were collected， including IST， psychiatric diagnostic categories， gender， ethnicity， age， body weight， body mass index （BMI）， course of disease， family history of psychiatric disorders， first episode status， use of antiepileptic drugs the day before treatment， use of benzodiazepines the day before treatment， and previous MECT treatment history. Pearson correlation analysis was utilized to test the correlation of IST with age， height， body weight， BMI， and course of disease， and stepwise multivariate linear regression analysis was performed to identify the factors affecting IST. ResultsIST yielded statistical difference among patients in terms of gender， first episode status， use of antiepileptic drugs the day before treatment， and use of benzodiazepines the day before treatment （t=2.256， -3.059， -2.136， -3.006， P<0.05 or 0.01）. IST in patients of different ages and psychiatric diagnostic categories also demonstrated statistical difference （F=913.120， 6.212， P<0.01）. Within young population， IST varied significantly based on the psychiatric diagnostic categories （F=2.986， P<0.05）. Correlation analysis indicated that IST was positively correlated with age， body weight， BMI and course of disease （r=0.886， 0.055， 0.184， 0.456， P<0.05 or 0.01）， and negatively correlated with height （r=-0.183， P<0.01）. Stepwise multivariate linear regression analysis revealed that age， gender， and body weight were influencing factors of IST （β=0.888， -0.049， -0.035， P<0.01）. ConclusionsAge， gender and body weight may be factors influencing IST in MECT for patients with mental disorders. ［Funded by Key R&D Plan Projects of Jining City in 2024 (number, 2024YXNS202）］

BACKGROUND: Peripheral helper T (T PH ) cells are uniquely positioned within pathologically inflamed non-lymphoid tissues to stimulate B-cell responses and antibody production. However, the phenotype, function, and clinical relevance of T PH cells in hepatocellular carcinoma (HCC) are currently unknown. METHODS: Blood, tumor, and peritumoral liver tissue samples from 39 HCC patients (Sep 2016-Aug 2017) and 101 HCC patients (Sep 2011-Dec 2012) at the Third Affiliated Hospital of Sun Yat-sen University were used. Flow cytometry was used to quantify the expression, phenotype, and function of T PH cells. Log-rank tests were performed to evaluate disease-free survival and overall survival in samples from 39 patients and 101 patients with HCC. T PH cells, CD19 + B cells, and T follicular helper (T FH ) cells were cultured separately in vitro or isolated from C57/B6L mice in vivo for functional assays. RESULTS: T PH cells highly infiltrated tumor tissues, which was correlated with tumor size, early recurrence, and shorter survival time. The tumor-infiltrated T PH cells showed a unique ICOS hi CXCL13 + IL-21 - MAF + BCL-6 - phenotype and triggered naïve B-cell differentiation into regulatory B cells. Triggering programmed cell death protein 1 (PD-1) induced the production of C-X-C motif chemokine ligand 13 (CXCL13) by T PH cells, which then suppressed tumor-specific immunity and promoted disease progression. CONCLUSION Our study reveals a novel regulatory mechanism of T PH cell-regulatory B-cell-mediated immunosuppression and provides an important perspective for determining the balance between the differentiation of protumorigenic T PH cells and that of antitumorigenic T FH cells in the HCC microenvironment.
Carcinoma, Hepatocellular/metabolism* ; Liver Neoplasms/metabolism* ; Humans ; T-Lymphocytes, Helper-Inducer/metabolism* ; Animals ; Mice ; Male ; Female ; Mice, Inbred C57BL ; Middle Aged ; B-Lymphocytes, Regulatory/metabolism* ; Flow Cytometry ; Interleukin-21 ; Aged ; Chemokine CXCL13/metabolism*

To clarify the occurrence and distribution of broad bean wilt virus 2(BBWV2) on Rehmannia glutinosa, this study collected 87 R. glutinosa samples with typical symptoms of viral disease such as chlorosis and crumple from Wenxian county and Wuzhi county in Jiaozuo city, Henan province and Qiaocheng district in Bozhou city, Anhui province. The BBWV2 CP target band was amplified from 37 R. glutinosa samples by RT-PCR technology. The total detection rate reached 42.5%, among which 43.0% was detected in samples from Henan province. The detection rate in samples from Anhui province was 37.5%. 37 BBWV2 CP sequences were obtained by cloning and sequencing of BBWV2 positive samples(data has been submitted to GenBank, accession numbers: PP407959-PP407995), and the sequence analysis of these CP sequences with 91 other BBWV2 isolates in GenBank showed a high genetic diversity with a consistency rate of 70.8%-100%. Meanwhile, phylogenetic analysis showed that BBWV2 could be divided into three groups according to CP sequences, among which the BBWV2 in R. glutinosa isolates obtained in this study were all located in group 3. This study identified the differences in the occurrence, distribution, and genetic diversity of BBWV2 in R. glutinosa from Henan province and Anhui province and provided a theoretical basis for the prevention and control of BBWV2.
Rehmannia/virology* ; Phylogeny ; Plant Diseases/virology* ; China ; Molecular Sequence Data ; Fabavirus/classification*

Cervical spine health issues not only seriously affect patients' quality of life but also impose a heavy burden on the social healthcare system. Existing guidelines lack sufficient clinical guidance on lifestyle and work habits, such as exercise, posture, daily routine, and diet, making it difficult to meet practical needs. To address this, relying on the China Association of Chinese Medicine, Wangjing Hospital of China Academy of Chinese Medical Sciences took the lead and joined hands with more than ten institutions to form a multidisciplinary guideline development group. For the first time, the group developed the Guidelines for Cervical Spine Health Intervention based on evidence-based medicine methods, strictly following the standardized procedures outlined in the World Health Organization Handbook for Guideline Development and the Guiding Principles for the Formulation/Revision of Clinical Practice Guidelines in China (2022 Edition). This proposal systematically explains the methods and steps for developing the guideline, aiming to make the guideline development process scientific, standardized, and transparent.
Humans ; Practice Guidelines as Topic/standards* ; Cervical Vertebrae ; China