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ObjectiveCollege students are currently grappling with severe mental health challenges, and research on artificial intelligence (AI) related to college students mental health, as a crucial catalyst for promoting psychological well-being, is rapidly advancing. Employing bibliometric methods, this study aim to analyze and discuss the research on AI in college student mental health.MethodsPublications pertaining to AI and college student mental health were retrieved from the Web of Science core database. The distribution of publications were analyzed to gage the predominant productivity. Data on countries, authors, journal, and keywords were analyzed using VOSViewer, exploring collaboration patterns, disciplinary composition, research hotspots and trends.ResultsSpanning 2003 to 2023, the study encompassed 1722 publications, revealing notable insights: (1) a gradual rise in annual publications, reaching its zenith in 2022; (2) Journal of Affective Disorders and Psychiatry Research emerged were the most productive and influential sources in this field, with significant contributions from China, the United States, and their affiliated higher education institutions; (3) the primary mental health issues were depression and anxiety, with machine learning and AI having the widest range of applications; (4) an imperative for enhanced international and interdisciplinary collaboration; (5) research hotspots exploring factors influencing college student mental health and AI applications.ConclusionThis study provides a succinct yet comprehensive overview of this field, facilitating a nuanced understanding of prospective applications of AI in college student mental health. Professionals can leverage this research to discern the advantages, risks, and potential impacts of AI in this critical field.

ObjectiveWith its high prevalence, depression's pathogenesis remains unclear. Recent attention has turned to the interplay between depression and epigenetic modifications. However, quantitative bibliometric analyses are lacking. This study aims to visually analyze depression epigenetics trends, utilizing bibliometric tools, while comprehensively reviewing its epigenetic mechanisms.MethodsUtilizing the Web of Science core dataset, we collected depression and epigenetics-related studies. Employing VOSViewer software, we visualized data on authors, countries, journals, and keywords. A ranking table highlighted field leaders.ResultsAnalysis encompassed 3,469 depression epigenetics studies published from January 2002 to June 2023. Key findings include: (1) Gradual publication growth, peaking in 2021; (2) The United States and its research institutions leading contributions; (3) Need for enhanced collaborations, spanning international and interdisciplinary efforts; (4) Keyword clustering revealed five main themes—early-life stress, microRNA, genetics, DNA methylation, and histone acetylation—highlighting research hotspots; (5) Limited focus on adolescent depression epigenetics, warranting increased attention.ConclusionTaken together, this study revealed trends and hotspots in depression epigenetics research, underscoring global collaboration, interdisciplinary fusion, and multi-omics data's importance. It discussed in detail the potential of epigenetic mechanisms in depression diagnosis and treatment, advocating increased focus on adolescent research in this field. Insights aid researchers in shaping their investigative paths toward understanding depression's epigenetic mechanisms and antidepressant interventions.

Abstract Background The purpose of this study was to demonstrate the in vitro anti-nephritis activity of Rostellularia procumbens (L.) Nees (R. procumbens) extract and to make a preliminary investigation of its anti-nephritis mechanism. Methods A prediction network was built that describes the relationship between R. procumbens and CGN. Then, the potential targets for R. procumbens against CGN were imported into the DAVID database for Gene Ontology (GO) biological annotation analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. A lipopolysaccharide (LPS)-stimulated rat mesangial cell HBZY-1 model in vitro was used to examine the anti-inflammatory activity of R. procumbens extract. RNA-seq was utilized to investigate differentially expressed genes (DEGs) and enriched signaling pathways between groups. Finally, qPCR was used for the validation analysis of the experimental results. Results The results of network pharmacology showed that R. procumbens exerts its therapeutic effect on CGN through the AGE-RAGE signaling pathway in diabetic complications, PI3K-Akt, IL-17 signaling pathway, and so on. R. procumbens n-butanol extract (J-NE) can effectively relieve inflammation in HBZY-1. The results of KEGG pathway enrichment suggest that J-NE attenuated CGN was associated with the IL-17 signaling pathway, and the results of RNA-seq were consistent with network pharmacology. Targets enriched in the IL-17 signaling pathway, including Chemokine (C-C motif) ligand 7 (CCL7), Lipocalin 2 (LCN2), Chemokine (C-C motif) ligand 2 (CCL2), and Chemokine (C-X-C motif) ligand 1 (CXCL1), have been identified as crucial targets attenuating CGN by J-NE. Conclusion R. procumbens is a promising pharmacological candidate for the treatment of CGN in the present era.

BackgroundDepression is a serious psychological disorder that college students are experiencing. College students’ depression problems, which can be caused by various factors, have been easily ignored and untreated. In recent years, exercise, as a low-cost and easily accessible method for treating depression, has attracted widespread attention. The purpose of this study is to use bibliometrics to explore the hotspots and trends in the field of exercise therapy of college students in depression from 2002 to 2022.MethodsWe retrieved relevant literature from the Web of Science (WoS), PubMed, and Scopus databases, and generated a ranking table to describe the core productivity in the field. We used VOSViewer software to generate network maps of authors, countries, co-cited journals, and co-occurring keywords to help us better understand the scientific collaboration patterns, potential disciplinary foundations, as well as research hotspots and trends in this field.ResultsFrom 2002 to 2022, a total of 1,397 articles related to exercise therapy of college students in depression were selected. The key findings of this study are as follows: (1) the number of publications has gradually increased, especially after 2019; (2) United States and its affiliated higher education institutions have made significant contributions to the development of this field; (3) there are multiple research groups in this field, but their connections are relatively limited; (4) the field is relatively interdisciplinary, primarily a convergence of behavioral science, public health, and psychology; (5) based on co-occurring keyword analysis, six main themes were summarized: health-promoting factors, body image, negative behaviors, increased stress, depression coping strategies, and diet.ConclusionOur study illustrates the research hotspots and trends for the research of exercise therapy of college students in depression, presents some challenges and new insights, and provides valuable information for further research.

This study explored the possible bioactive ingredients and target protein of Rostellularia procumbens (L.) Nees. The results of optical turbidimetry revealed that the ethyl acetate extraction obtained from R. procumbens (L.) Nees could inhibit platelet aggregation. Gene chip was used to investigate differentially expressed genes. According to the results of the gene chip, the targets of compounds isolated from the ethyl acetate extraction were predicted by network pharmacology. Computational studies revealed that chinensinaphthol methyl ether and neojusticin B may target the integrin αIIbβ3 protein. The results of Prometheus NT.48 and microscale thermophoresis suggested that the molecular interactions between the two compounds with purified integrin αIIbβ3 protein in the optimal test conditions were coherent with the docking results. To our best knowledge, this is the first report to state that chinensinaphthol methyl ether and neojusticin B target the integrin αIIbβ3 protein.

There has been a large global outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), representing a major public health issue. In China, combination therapy, including traditional Chinese medicine (TCM) as a treatment for COVID-19 has been used widely. “Fei Yan No. 1” (QFDYG) is a formula recommended by the Hubei Government to treat COVID-19. A retrospective study of 84 COVID-19 patients from Hubei Provincial Hospital of TCM and Renmin Hospital of Hanchuan was conducted to explore the clinical efficacy of QFDYG combination therapy. TCMSP and YaTCM databases were used to determine the components of all Chinese herbs in QFDYG. Oral bioavailability (OB) ≥ 30% and drug-like (DL) quality ≥ 0.18 were selected as criteria for screening the active compounds identified within the TCMSP database. The targets of active components in QFDYG were determined using the Swiss TargetPrediction (SIB) and Targetnet databases. The STRING database and the Network Analyzer plugin in Cytoscape were used to obtain protein-protein interaction (PPI) network topology parameters and to identify hub targets. Gene Ontology (GO) enrichment was conducted using FunRich version 3.1.3, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment using ClueGO version 2.5.6 software. PPI and compound-pathway (C-T) networks were constructed using Cytoscape 3.6.0. Compared with the control group, combined treatment with QFDYG resulted in a significantly higher rate of patients recovering from symptoms and shorter the time. After 14 days of treatment, QFDYG combined treatment increased the proportion of patients testing negative for SARS-CoV-2 nucleic acid by RT-PCR. Compared with the control group, promoting focal absorption and inflammation as viewed on CT images. GO and KEGG pathway enrichment indicated that QFDYG principally regulated biological processes, such as inflammation, an immune response, and apoptosis. The present study revealed that QFDYG combination therapy offered particular therapeutic advantages, indicating that the theoretical basis for the treatment of COVID-19 by QFDYG may play an antiviral and immune response regulation through multiple components, targets, and pathways, providing reference for the clinical treatment of COVID-19.

Taohe-Chengqi decoction (THCQ), a classical traditional Chinese medicinal (TCM) formula, has been extensively used for treating chronic kidney disease (CKD). However, the biological activity and mechanisms of action of its constituents against renal fibrosis have not yet been investigated thoroughly. This study was aimed at devising an integrated strategy for investigating the bioactivity constituents and possible pharmacological mechanisms of the n-butanol extract of THCQ (NE-THCQ) against renal fibrosis. The n-butanol extract of THCQ was prepared by the solvent extraction method. The components of NE-THCQ were analyzed using UPLC-Q/TOF-MS/MS techniques and applied for screening the active components of NE-THCQ according to their oral bioavailability and drug-likeness index. Then, we speculated the potential molecular mechanisms of NE-THCQ against renal fibrosis through pharmacological network analysis. Based on data mining techniques and topological parameters, gene ontology, and pathway enrichment, we established compound-target (C-T), protein-protein interaction (PPI) and compound-target-pathway (C-T-P) networks by Cytoscape to identify the hub targets and pathways. Finally, the potential molecular mechanisms of NE-THCQ against renal fibrosis, as predicted by the network pharmacology analyses, were validated experimentally in renal tubular epithelial cells (HK-2) in vitro and against unilateral ureteral obstruction models in the rat in vivo. We identified 26 components in NE-THCQ and screened seven bioactive ingredients. A total of 118 consensus potential targets associated with renal fibrosis were identified by the network pharmacology approach. The experimental validation results demonstrated that NE-THCQ might inhibit the inflammatory processes, reduce ECM deposition and reverse EMT via PI3K/AKT/mTOR and HIF-1α/VEGF signaling pathways to exert its effect against renal fibrosis. This study identified the potential ingredients of the NE-THCQ by UPLC-Q/TOF-MS/MS and explained the possible mechanisms of NE-THCQ against renal fibrosis by integrating network pharmacology and experimental validation.