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Feb 2026 DOI 10.14302/issn.2474-9273.jbtm-25-5885
Jia NingCorresponding author
Background Depression, increasingly recognized as a critical factor impacting mental health, notably affects various populations, including teachers. This study aimed to delineate the specific characteristics of depressive symptom networks among Chinese teachers, identify the core symptoms of depression within this demographic, and examine the variations in depressive symptom networks across different genders and teaching stages. Method The study encompassed 1,670 teachers. Depressive symptoms were assessed using the Self-Rating Depression Scale (SDS). Central symptoms were identified through centrality indices. Network stability was examined via a case-dropping procedure. Directed Acyclic Graphs (DAG) was used to identify the activating symptoms. Results “Personal devaluation” exhibited the highest and most stable centrality values in the network. “Depressed Affect” and “Emptiness of Life” were identified as the activating symptoms in the network. No significant differences were observed in the network structure and global strength of depression between teachers of different genders. However, significant differences in the network’s global strength were found between junior and senior high school teachers. Conclusion “Personal devaluation” emerged as the core depressive symptoms among teachers in China. “Depressed Affect” and “Emptiness of Life” serve as the gateways that activate the entire teacher depression network. Paying close attention to these symptoms could potentially alleviate the experiences of depression in this demographic.
May 2024 DOI 10.14302/issn.2470-5020.jnrt-24-5100
T. Adebisi AbdulyekeenCorresponding author
Exploring the dynamic dimension of functional connectivity in dementia, this article departs from traditional static studies to capture the ever-changing brain networks. Investigating temporal connectivity patterns yields valuable insights into disease progression, individualized treatment, and early intervention. Additionally, the concept of cognitive reserve, therapeutic interventions, and machine learning integration are pivotal in revolutionizing dementia research and care.
Oct 2020 DOI 10.14302/issn.2329-9487.jhc-20-3584
Lu YuananCorresponding author
School of Economics and management, Jiangxi University of Traditional Chinese Medicine, Nanchang 330006, PR China
Objective To examine the current linkage between different medical services for hypertension patients for enhanced integration among medical service systems. Methods A total of 18 hospitals and community medical centers from a district of Shanghai were enrolled for social network analysis which covered emergency visits and hospitalization records of 171,177 outpatients with hypertension. Stata software was used for data preprocessing and UCINET software was used for network analysis of medical service providers to quantify and visualize the network tightness and the "main role" of information delivery of the medical institution network in the area. Results The service network of hypertension consultation institutions in the region is closely connected as a whole, but the level of diagnosis and treatment of medical services in various communities varies widely, and the degree of association with higher-level medical institutions is not uniform. Conclusion Based on the limited tightness of various medical service providers, it is necessary to implement the responsibilities of individual medical institutions at different levels and pay more attention to improving the service capabilities of primary medical institutions for enhanced integrating medical services in future.
May 2024 DOI 10.14302/issn.2470-0436.jos-23-4493
Sun KexinCorresponding author
Background Beta-Sitosterol (SIT) is an active TCM compound employed to treat diabetic retinopathy (DR). A network pharmacology approach to understanding the active ingredients and the therapeutic mechanisms underlying DR has not been pursued. Methods The potential targets for DM were identified according to the MedGene, Gendome, HGNC, OMIM, GeneCards, PheGenI, GEO, and STRING database. The herb and components were predicted and screened by network pharmacology through oral bioavailability and drug-likeness filtration using the Traditional Chinese Medicine Systems Pharmacology Analysis Platform database. A network pharmacology prediction and network analysis were used to predict the active potential targets and pathways of SIT application to DR. Results We found the Top 15 DR-related genes by screening in 9 databases. 26 kinds of TCM and nearly 300 kinds of active ingredients. SIT exists in 10 kinds of DR-treat TCM. The comprehensive network pharmacology approach was successful in identifying 23 kinds of core genes for SIT treating DR. ERBB3 and IGF2-related PI3K-Akt signaling pathway or EDN3, IGF2 and SPP1-related receptor ligand activity pathway might be the main pharmacological targets, and pathways in DR. We speculated that SIT was effective for the treatment of DR. Conclusion Based on the network pharmacology, we predicted the potential targets of SIT in treating DR and helped to illustrate the mechanism of action. Our study identifies key genes and pathways associated with the prognosis and pathogenesis of DR from new insights.