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）］

Objective To explore the roles of transfer RNA-derived small RNAs(tsRNAs)in the oncogenesis and progression of lung adenocarcinoma by analyzing the differential expression of tsRNAs in lung adenocarcinoma and the relationship between the expression levels of tsRNAs in lung adenocarcinoma and the prognosis of patients in order to further screen and validate the tsRNAs associated with lung adenocarcinoma.Methods The differential expression of tsRNAs between lung adenocarcinoma tissues and normal tissues was analyzed based on the database of the Computational Medicine Center.The effects of tsRNAs expression levels on the prognosis of lung adenocarcinoma patients were analyzed based on the Cancer Genome Atlas(TCGA)database(TCGA-LUAD).The target genes were predicted based on TRFtarget2.0 and tRFTar databases.Gene ontology(GO)enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis were performed based on DAVID and KOBA KEGG online websites.The expression levels of target genes in lung adenocarcinoma tissues and normal tissues were analyzed based on the University of ALabama at Birmingham CANcer data analysis Portal(UALCAN)database.In vitro cell proliferation,migration,and invasion assays were performed to investigate the biological functions of tRF-19-69M8LOJX in lung adenocarcinoma cells.Results Compared with the normal tissues,tRF-19-69M8LOJX was up-regulated in lung adenocarcinoma tissues(log2FC=4.28,FDR＜0.05).High expression level of tRF-19-69M8LOJX was associated with shorter progression-free survival(HR=1.565,95％CI=1.142-2.145,P=0.005).And its overexpression promoted cell proliferation and migration(P＜0.001),and invasion(P=0.009)of A549 cells,and up-regulated COL1A1(P=0.002)and VCAN(P=0.022)significantly in the tRF-19-69M8LOJX overexpression cell model.Conclusion tRF-19-69M8LOJX is up-regulated in lung adenocarcinoma tissues.And its high expression is closely associated with poor prognosis.The tsRNA may play an important role in the pathogenesis and development of lung adenocarcinoma.

Objective To explore the association between the relative expression level of SNORD55 in peripheral blood and the outcomes of all-cause mortality and stroke in patients with atrial fibrillation(AF),and to evaluate the predictive value of SNORD55 for prognosis.Methods A total of 133 patients with non-valvular AF admitted in Department of Cardiology of the First Affiliated Hospital of Army Medical University from January 2014 to December 2017 were enrolled in this study.Their baseline information was collected,and the relative expression level of plasma SNORD55 was detected.Cox proportional hazards model was used to explore the association between the relative expression level of SNORD55 in peripheral blood and all-cause mortality as well as stroke in the patients.The predictive performance of CHA2DS2-VASc score for all-cause mortality and stroke was compared with the score combined with the relative expression level of SNORD55 in the AF patients.The area under the receiver operating characteristic curve(AUC)was utilized to evaluate the discrimination,and the net reclassification index(NRI)and comprehensive discriminant improvement index(IDI)were calculated to evaluate the improvement of reclassification ability.Decision curve analysis(DCA)was applied to analyze the change in clinical net benefit.Results The results of multivariate Cox regression showed that high expression of SNORD55 in peripheral blood was an independent risk factor for all-cause mortality and stroke in the AF patients.In predicting the outcomes of all-cause mortality and stroke,the addition of relative expression SNORD55 level with the CHA2DS2-VASc score obtained higher AUC value[0.80(95％CI:0.67～0.93)vs 0.67(95％CI:0.53～0.81),P＜0.05].In predicting the outcome of all-cause death and stroke,combination of the relative expression level of SNORD55 with CHA2DS2-VASc score increased both NRI[54.3(95％CI:10.6～61.9)vs 31.9(95％CI:2.8～47.5),P＜0.05]and IDI[16.1(95％CI:2.4～27.0)vs 7.9(95％CI:0.5～14.8),P＜0.05].The results of DCA showed that our combination of CHA2DS2-VASc score relative expression level of SNORD55 had higher clinical net benefits than the foreign ABC score in the prediction of the outcomes.Conclusion Peripheral blood SNORD55 level is an independent risk factor for all-cause mortality and stroke in AF patients,and has good predictive performance for all-cause mortality and stroke in the patients.

Objectives To explore the association of peripheral blood PIWI-interacting RNA,piR-hsa-2700592,with all-cause mortality and stroke outcomes in patients with atrial fibrillation(AF),and to determine whether piR-hsa-2700592 has the potential to be an AF biomarker.Methods A total of 127 patients with non-valvular AF were enrolled,and the relative expression level of plasma piR-hsa-2700592 was detected.Cox proportional hazard regression was used to analyze the correlation between the expression of piR-hsa-2700592 and all-cause death as well as stroke outcome in the patients.Then the molecule expression level was combined with CHA2DS2-VASc score and ABC stroke(or death)score to establish 2 new prediction models,the improvement of the predictive performance was compared and analyzed.Receiver operating characteristic(ROC)curve analysis(area under the curve,AUC),net reclassification index(NRI),and comprehensive discriminant improvement index(IDI)were used to evaluate the predictive performance,and decision curve analysis(DCA)was employed to assess the clinical benefit.Results Multivariate Cox regression analysis showed that the patients with higher expression level of piR-hsa-2700592 in peripheral blood had a higher risk of stroke(HR:2.203,95%CI:1.120～4.332;P=0.022).In the stroke outcome,combination of plasma piR-hsa-2700592 expression level with CHA2DS2-VASc score and ABC stroke score obtained an AUC of 0.70(95%CI:0.55～0.85,P＜0.001)and 0.84(95%CI:0.73～0.96,P=0.02),respectively.But,no significant association was observed between high plasma piR-hsa-2700592 level and all-cause mortality in the AF patients(HR:1.997;95%CI:0.884～4.509;P=0.096).Combination of plasma piR-hsa-2700592 level improved the discriminative capability than the single CHA2DS2-VASc score and ABC stroke score models,with an NRI and IDI value of 44.20%(95%CI:3.40～59.90,P＜0.001)and 8.20%(95%CI:0.60～15.40,P＜0.001),respectively for the new CHA2DS2-VASc score model,and an NRI and IDI value of 44.20%(95%CI:9.80～58.90,P＜0.001)and 10.40%(95%CI:0.70～21.40,P＜0.001),respectively for the new ABC stroke score model.The DCA curve showed that both new prediction models obtained better net clinical benefits.Conclusion High peripheral blood expression of piR-hsa-2700592 is an independent risk factor for stroke in the AF patients,and the indicator has a good predictive value for prognosis of the patients.piR-hsa-2700592 might be used as a potential biomarker in the diagnosis and prevention of cardiovascular diseases.

Respiratory syncytial virus is the leading pathogen of lower respiratory tract infections in children under 5 years of age. Early-life respiratory syncytial virus infection is closely associated with long-term adverse outcomes，including impaired lung function，recurrent wheezing，and asthma. Metabolomics，an emerging systems biology approach，enables the quantitative analysis of dynamic changes in small-molecule metabolites within biological samples，providing critical insights into disease pathogenesis. This article reviews the metabolomic profiles of children with respiratory syncytial virus infection，with a focus on alterations in carbohydrate，lipid，and amino acid metabolism pathways. Additionally，it examines the distinct metabolomic features of children who develop recurrent wheezing following respiratory syncytial virus infection. These findings offer novel perspectives for elucidating the pathophysiological mechanisms of respiratory syncytial virus infection and improving early diagnosis and prognostic assessment.

Objective:To investigate the role of alkylation repair homolog 5(ALKBH5)-mediated N6-methyladenosine(m6A)modifi-cation in endometrial decidualization.Methods:The mouse models of pregnancy and pseudopregnancy were established,and quantita-tive real-time PCR and Western blot were used to measure the expression pattern of ALKBH5 in the endometrium.The mouse and cell models of artificially induced decidualization were established,and quantitative real-time PCR,Western blot,and immunohistochemis-try were used to measure the expression levels of decidualization-related markers.The EpiQuik m6A RNA methylation quantification kit was used to measure the level of m6A.The mouse and cell models of artificially induced decidualization with interference of ALKBH5 expression were established,and quantitative real-time PCR,Western blot,and immunohistochemistry were used to measure the expression levels of decidualization-related markers,cell proliferation marker molecules,and apoptosis molecules.Flow cytometry was used to measure cell apoptosis rate.Results:In the mouse model of pregnancy,the expression level of ALKBH5 at the uterine em-bryo implantation site was significantly higher than that adjacent to the implantation site,and in the mouse and cell models of artifi-cially induced decidualization,compared with the control group,the induction group had a significant increase in the expression level of ALKBH5 and a significant reduction in the level of m6A.Inhibiting the expression of ALKBH5 led to an increase in the level of m6A,which in turn inhibited the proliferation of stromal cells,induced cell apoptosis,and ultimately impaired the normal process of en-dometrial decidualization.Conclusion:ALKBH5 deficiency leads to an increase in the level of m6A and decidualization injury in the en-dometrium,which lays a foundation for the research on m6A modifi-cation in decidualization.

Adipose tissue is a critical energy reservoir in animals and humans, with multifaceted roles in endocrine regulation, immune response, and providing mechanical protection. Based on anatomical location and functional characteristics, adipose tissue can be categorized into distinct types, including white adipose tissue (WAT), brown adipose tissue (BAT), beige adipose tissue, and pink adipose tissue. Traditionally, adipose tissue research has centered on its morphological and functional properties as a whole. However, with the advent of single-cell transcriptomics, a new level of complexity in adipose tissue has been unveiled, showing that even under identical conditions, cells of the same type may exhibit significant variation in morphology, structure, function, and gene expression——phenomena collectively referred to as cellular heterogeneity. Single-cell transcriptomics, including techniques like single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), enables in-depth analysis of the diversity and heterogeneity of adipocytes at the single-cell level. This high-resolution approach has not only deepened our understanding of adipocyte functionality but also facilitated the discovery of previously unidentified cell types and gene expression patterns that may play key roles in adipose tissue function. This review delves into the latest advances in the application of single-cell transcriptomics in elucidating the heterogeneity and diversity within adipose tissue, highlighting how these findings have redefined the understanding of cell subpopulations within different adipose depots. Moreover, the review explores how single-cell transcriptomic technologies have enabled the study of cellular communication pathways and differentiation trajectories among adipose cell subgroups. By mapping these interactions and differentiation processes, researchers gain insights into how distinct cellular subpopulations coordinate within adipose tissues, which is crucial for maintaining tissue homeostasis and function. Understanding these mechanisms is essential, as dysregulation in adipose cell interactions and differentiation underlies a range of metabolic disorders, including obesity and diabetes mellitus type 2. Furthermore, single-cell transcriptomics holds promising implications for identifying therapeutic targets; by pinpointing specific cell types and gene pathways involved in adipose tissue dysfunction, these technologies pave the way for developing targeted interventions aimed at modulating specific adipose subpopulations. In summary, this review provides a comprehensive analysis of the role of single-cell transcriptomic technologies in uncovering the heterogeneity and functional diversity of adipose tissues.

OBJECTIVE: To explore the relationship between the geriatric nutritional risk index (GNRI) and cognitive function. METHODS: A cross-sectional study method was conducted. People aged ≥ 60 years from the National Health and Nutrition Examination Survey (NHANES) databases from 1999 to 2002 and 2011 to 2014 were included as study subjects. The participants were divided into three groups based on their GNRI scores: a medium-high risk group (82 ≤ GNRI < 92), a low risk group (92 ≤ GNRI < 98), and a no-risk group (GNRI ≥ 98). Demographic characteristics (gender, age, race, education), chronic diseases [chronic bronchitis, emphysema, thyroid problems, coronary heart disease, angina pectoris, stroke, hypertension, diabetes mellitus, and depression score on the patient health questionnaire (PHQ-9)], lifestyle habits (history of smoking, hours of sleep), etc., were collected. Cognitive function was assessed using the consortium to establish a registry for Alzheimer's disease word learning subtest (CERAD-WL), animal fluency test (AFT), and digit symbol substitution test (DSST) for the 2011-2014 data, while only the DSST was used for the 1999-2002 data. Differences in the above information among the GNRI cohorts were compared. Factors affecting cognitive function in the population were analyzed using multifactorial Logistic regression. RESULTS: 2 653 participants from 2011 to 2014 and 2 380 participants from 1999 to 2002 were enrolled, with a total of 5 033 participants in the study. There were statistically significant differences in age, stroke, diabetes mellitus, DSST score, AFT score, CERAD score test 1 recall (Cst1), and CERAD score test 2 recall (Cst2) among the GNRI groups. Multifactorial Logistic regression analysis of data from 2011 to 2014 showed that in model 3 (DSST score, age, gender, race, marriage, education, hours of sleep, history of smoking, emphysema, thyroid problems, chronic bronchitis, coronary heart disease, angina pectoris, hypertension, diabetes mellitus, depression score on the PHQ-9, and stroke) adjusted for all covariates, GNRI was a protective factor for DSST [odds ratio (OR) = 1.03, 95% confidence interval (95%CI) was 1.00 to 1.05, P = 0.03]; Logistic regression analyse for 1999 to 2002 and 2011 to 2014 showed a significant association even after adjustment for covariates (OR = 1.02, 95%CI was 1.00 to 1.03, P = 0.02). Subgroup Logistic regression analyses of the total population from 2011 to 2014 showed a significant association between GNRI and DSST scores (OR = 1.02, 95%CI was 1.01 to 1.03, P < 0.001), with significant associations in the age subgroups of 60 to 64 years old, across gender, non-Hispanic Whites and Blacks, by education, and by marital status associations were significant (all P < 0.05). Subgroup Logistic regression analyse of the total populations from 1999 to 2002 and 2011 to 2014 showed a significant association between the GNRI and DSST score (OR = 1.01, 95%CI was 1.01 to 1.02, P < 0.001), but did not show a significant year difference (interaction P = 0.503), and the newly found in the smoking population the association was also more significant (P < 0.01). CONCLUSION The GNRI correlates with the presence of cognitive functions related to processing speed, sustained attention, and executive function, and may be able to serve as an indicator for the assessment or prediction of related cognitive functions.
Humans ; Cross-Sectional Studies ; Aged ; Middle Aged ; Nutrition Surveys ; Cognition ; Female ; Male ; Nutritional Status ; Risk Factors ; Geriatric Assessment

OBJECTIVE: Glucocorticoid-induced osteoporosis (GIOP) is a common complication of prolonged glucocorticoid therapy. Chlorogenic acid (CGA), a polyphenol with antioxidant properties that is extracted from traditional Chinese medicines such as Eucommiae Cortex, has potential anti-osteoporotic activity. This study aimed to investigate the possible effects of CGA on GIOP in mice and murine long bone osteocyte Y4 (MLO-Y4) cells and explore the underlying molecular mechanisms. METHODS: The protective effects of CGA were initially evaluated in the GIOP mouse model induced by dexamethasone (Dex). The micro-computed tomography, hematoxylin-eosin staining, silver nitrate staining, and serum detection were used to assess the efficacy of CGA for improving bone formation in vivo. Then, network pharmacology analysis was used to predict the potential targets and molecular mechanisms underlying the therapeutic efficacy of CGA against GIOP. After that, 2',7'-dichlorofluorescein diacetate staining, flow cytometry, real-time quantitative reverse transcription polymerase chain reaction, and Western blotting were used to verify the mechanisms of CGA against GIOP in vitro. RESULTS: Animal experiments showed that CGA treatment effectively attenuated Dex-induced decreases in bone mass and strength and improved disrupted osteocyte morphology in mice. The protein-protein interaction analysis highlighted erb-b2 receptor tyrosine kinase (ERBB2), which is also known as human epidermal growth factor receptor 2 (HER2), caspase-3, kinase insert domain receptor, matrix metallopeptidase 9, matrix metallopeptidase 2, proto-oncogene tyrosine-protein kinase Src, and epidermal growth factor receptor as core targets. The Kyoto Encyclopedia of Genes and Genomes analysis revealed several significantly enriched pathways (P < 0.05), including the ERBB, phosphoinositide 3 kinase-AKT serine/threonine kinase 1 (AKT), and mechanistic target of rapamycin kinase (mTOR) pathways. Cellular experiments verified that CGA enhanced bone formation and promoted autophagy while inhibiting apoptosis in MLO-Y4 cells exposed to Dex, which was associated with the upregulated expression of HER2 and activation of the HER2/AKT/mTOR signaling pathway. CONCLUSION CGA exerted anti-osteoporotic effects against GIOP, partially through targeting osteocytes and modulating the HER2/AKT/mTOR signaling pathway. Please cite this article as: Xie AN, Zhang SZY, Zhang Y, Cao JL, Wang CL, Wang LB, Wu HJ, Zhang J, Dai WW. Chlorogenic acid mitigates glucocorticoid-induced osteoporosis via modulation of HER2/AKT/mTOR signaling pathway. J Integr Med. 2025; 23(6):670-682.
Animals ; Chlorogenic Acid/therapeutic use* ; Osteoporosis/metabolism* ; Signal Transduction/drug effects* ; Proto-Oncogene Proteins c-akt/metabolism* ; TOR Serine-Threonine Kinases/metabolism* ; Mice ; Glucocorticoids/adverse effects* ; Receptor, ErbB-2/metabolism* ; Proto-Oncogene Mas ; Dexamethasone/adverse effects* ; Osteocytes/drug effects* ; Osteogenesis/drug effects* ; Male ; Cell Line ; Mice, Inbred C57BL ; Humans