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 The study aimed to elucidate the population composition and seasonal distribution characteristics of mosquitoes in Laoshan District, Qingdao City, providing a scientific basis for the prevention and control of mosquito-borne infectious diseases. Methods Mosquito surveillance was conducted in Laoshan District in Qingdao City using light traps from April to November 2020-2022. Dominant mosquito species were identified using the Berger-Parker dominance index(I)and mosquito density was compared using the Kruskal-Wallis H test. The seasonal distribution characteristics of adult mosquitoes were analyzed using concentration and circular distribution method. Spearman rank correlation analysis was used to study the relationship between mosquito populations and meteorological factors with mean monthly temperature, mean monthly relative humidity, and mean monthly rainfall. Results The mean mosquito density for the trapping period was 9.771 females/(trap·night)in 2020,9.771 in 2021, and 9.427 in 2022. There was no statistically significant difference in mosquito density between different years(H = 0.095, P = 0.954). In total, 2 781 adult female mosquitoes comprising five species from four genera were captured over three years. Culex pipiens(I = 0.654), Aedes albopictus(I = 0.202), and Aedes aegypti(I = 0.118)were identified as dominant species. Seasonal fluctuations in the adult mosquitoes were unimodal, and primarily concentrated from June to September. The peak period of adult mosquito varied between years with statistical significance. (F = 3.838, P ＜ 0.05). Mosquito density was highly correlated with mean monthly temperature, mean monthly relative humidity and mean monthly precipitation(P＜ 0.05). Conclusions Cx. pipiens pallens, Ae. albopictus, and Ar. inamoratus are the dominant mosquito species in the Laoshan District of Qingdao City. The activity of adult mosquitoes is seasonal, and primarily concentrated in summer and autumn, during which the risk of mosquito-borne diseases such as dengue fever is increased.

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: To explore the mechanism by which the extract of Semen Ziziphi Spinosae extract promotes bone growth in mice by modulation of the expression of miR-34a-5p in brain tissue. METHODS: Mice were assigned to four experimental groups:a normal control group, a drug administration group (receiving 0.320 mg·g^-1 body weight of Semen Ziziphi Spinosae extract via intragastric administration), a positive control group (receiving 0.013 mg·g^-1 body weight of jujube seed saponin via intragastric administration), and a combination group administration with Semen Ziziphi Spinosae extract plus a 5-hydroxytryptamine 2A receptor (5-HT2AR) agonist (intragastric administration of Semen Ziziphi Spinosae extract combined with intracerebroventricular injection of 8 μg P-MPPF per mice for the final three days of the experiment). Following a 20-day administration period, the effects of the interventions on bone growth, serum growth hormone (GH) levels, and 5-HT2AR expression in brain tissue were evaluated. MicroRNAs (miRNAs) that were differentially expressed in the brain tissues of mice exhibiting bone growth induced by Semen Ziziphi Spinosae extract, as compared to those in normal mice, were identified using a gene chip approach. The interaction between miR-34a-5p and 5-HT2AR was subsequently validated through quantitative reverse transcription polymerase chainreaction (RT-qPCR) and dual-luciferase reporter gene assays. Subsequently, by utilizing the miR-34a-5p inhibitor group and mimics group, along with the normal control group, the drug administration group, the positive control group, and the drug administration combined with miR-34a-5p inhibitor group, the variations in 5-HT2AR expression in mouse brain tissue across all groups were examined, and the binding activity of 5-hydroxytryptamine (5-HT) to the 5-hydroxytryptamine 1A receptor (5-HT1AR) in mice was assessed. RESULTS: The body lengths of the normal control group and the drug administration group were(8.9±0.3) and(10.4±0.4) cm;femur lengths were (8.5±0.3) and (9.1±0.5) mm;tibia lengths were (10.7±0.3) and (11.2±0.4) mm, respectively. The contents of GH levels were (58.6±8.2) and (72.9±6.1) ng·ml-1;and the contents of 5-HT2AR were (32.0±5.0) and (21.9± 5.5) ng·ml-1, respectively. Compared with the normal control group, the drug administration group promoted the growth of body length, femur, and tibia in mice, and increased GH secretion, showing statistically significant differences (P<0.05). Additionally, it significantly reduced the content of 5-HT2AR in brain tissue, with statistical significance (P<0.01). The gene chip analysis identified a total of 16 differentially expressed miRNAs, of which 13 were up-regulated and 3 were down-regulated. Bioinformatics analysis predicted that the up-regulated miR-34a-5p could regulate the expression of 5-HT2AR, a prediction that was confirmed through a dual-luciferase reporter gene assay, demonstrating a direct regulatory interaction between the two. Furthermore, in vivo experiments in mice revealed that overexpression and silencing of miR-34a-5p resulted in corresponding changes in the expression levels of 5-HT2AR in brain tissues/cells, as well as in the binding activity between 5-HT and 5-HT1AR. CONCLUSION The Semen Ziziphi Spinosae extract promotes animal bone growth by enhancing miR-34a-5p expression in brain tissue, downregulating the expression level of 5-HT2AR, improving the binding activity between 5-HT and 5-HT1AR, and extending slow-wave sleep duration, thereby stimulating GH secretion.
Animals ; MicroRNAs/metabolism* ; Mice ; Male ; Brain/metabolism* ; Ziziphus/chemistry* ; Bone Development/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Plant Extracts/pharmacology*

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

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 analyze the status of social support and the influencing factors of support utilization among general practitioners.Methods:An investigation on the status of social support and the influencing factors of support utilization was conducted among general practitioners (GPs) from 6 communities in Shanghai Minhang District selected by simple sampling method in February 2023. The investigation included a questionnaire survey containing basic information and intervention measures (emotional support, information support, tool support); and assessments of the Social Support Rate Scale (SSRS), Perceived Social Support Scale, General Self-Efficacy Scale, Quality of Work Life Scale, Trait Coping Style Scale, and Psychological Resilience Scale. The association of social support status with various characteristics of GPs and their perceived social support and trait coping style was analyzed, and the influencing factors of social support utilization were determined.Results:A total of 184 questionnaires were distributed and 184 valid questionnaires were collected, with an effective recovery rate of 100.00%. Among the 184 participants, 55 (29.89%) had a general level of social support, and 129 (70.11%) were satisfied with their social support. The total score of SSRS was (37.49±8.41), with the objective support dimension scoring (9.67±3.42), subjective support scoring (20.04±4.52), and support utilization scoring (7.77±2.09). Univariate analysis showed significant differences in social support levels among respondents with different marital status, number of children, emotional support, informational support, instrumental support, positive coping, negative coping, psychological resilience, compassion fatigue, general self-efficacy, and perceived social support status ( P<0.05). Multiple linear regression analysis indicated that marital status, family support, professional skills, positive coping, and negative coping were independent influencing factors of social support. Among these factors, being married, having family care support, professional titles and skills and positive coping had a positive impact on social support levels, while negative coping had a negative impact ( P<0.05). Further stepwise multiple linear regression analysis showed that friend support, positive coping and family care were positive influencing factors for support utilization, while negative coping was a negative influencing factor ( P<0.05). Conclusion:The levels of social support among GPs in Minghang district of Shanghai are relatively high. Marital status, family support, professional title and skills and positive coping are positive factors for social support; and friend support, positive coping and family support are positive factors for support utilization.

To explore the role of the "Clinical Practice Guidelines" column and others in the Medical Joumnal of Peking Union Medical College Hospital (Med J PUMCH) in promoting diseiplinary development.

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.