1.Meta analysis of the efficacy of digital psychological therapies on depressive symptoms among adolescents
YANG Xuan, YANG Dong, CAI Rui, TANG Yuping, YE Sheng, LUO Yaoyue
Chinese Journal of School Health 2026;47(4):531-537
Objective:
To systematically evaluate the therapeutic efficacy and maintenance effects of digital psychological therapies on depressive symptoms among adolescents, so as to provide a reference for clinical practice.
Methods:
Randomized controlled trial(RCT) investigating digital psychological therapies to improve depressive symptoms among adolescents were searched across databases, including PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang database, VIP database, and SinoMed, from database inception to November 20, 2025. Following literature screening, quality assessment, and data extraction, a Meta analysis was performed using Stata 18.0 software.
Results:
A total of 20 studies involving 2 042 adolescents aged 11-19 were included. The Meta analysis revealed that digital psychological therapies significantly alleviated depressive symptoms in adolescents ( SMD =-0.59, 95% CI =-0.85 to -0.32, P <0.01). The therapeutic effect was sustained at long term follow up ( SMD =-0.21, 95% CI =-0.34 to -0.09, P <0.01). Furthermore, depression scores in the intervention group showed a continued decrease from post intervention to long term follow up ( SMD =-0.28, 95% CI =-0.41 to -0.14, P <0.01). Egger s linear regression test indicated possible publication bias (Kendall s tall=0.28, P <0.01).
Conclusions
Digital psychological therapies can effectively improve depressive symptoms among adolescents, with stable long term efficacy. However, current evidence remains limited and exhibits substantial heterogeneity. Therefore, further large sample, high quality RCTs are warranted to validate the effectiveness of this intervention.
2.column:Serum short-chain fatty acid levels and their association with atopic dermatitis in pediatric patients
Zhenxiang WANG ; Lele CHEN ; Liping DONG ; Sheng WANG ; Jinlei XU ; Xinying CAI ; Fengli XIAO
Acta Universitatis Medicinalis Anhui 2026;61(4):763-769
ObjectiveTo investigate the metabolic alterations of serum short chain fatty acids (SCFAs) in pediatric patients with atopic dermatitis (AD) and their correlation with different clinical phenotypes using targeted metabolomics. MethodsThis study enrolled 87 AD patients and 67 healthy controls (HC). Serum levels of eight SCFAs were quantified by ultra-high-performance liquid chromatography-mass spectrometry. The associations between SCFAs and AD were assessed using various statistical methods. ResultsCompared with the HC group, levels of acetic acid (AA), propionic acid (PA), and caproic acid (CA) (P=0.002,P=0.002,P=0.043) decreased in the AD group. Logistic regression analysis identified AA (OR=0.449, 95% CI: 0.289–0.698) and PA (OR = 0.487, 95% CI: 0.324–0.732) as protective factors against AD. The combination of AA and PA yielded an area under the curve (AUC) greater than 0.7, indicating good diagnostic efficacy. Age-stratified analysis revealed that AA reduction was predominant in childhood, whereas PA reduction was predominant in adolescence. Pathway enrichment analysis showed significant enrichment of fatty acid biosynthesis (FDR=0.341, P=0.003) and vitamin K metabolism (FDR=1, P=0.039) pathways. Furthermore, subgroup analyses based on disease severity, personal/family history of atopy, and sex revealed no significant differences in SCFAs levels among the groups. ConclusionDifferential serum SCFAs and their enriched metabolic pathways may be implicated in the pathogenesis of AD.
3.Developing Effective Strategies to Overcome Immunotherapy Resistance in Non-Small Cell Lung Cancer by Directly Targeting Cancer Cells
Qing HUANG ; Jiaqi XIAO ; Sheng HU ; Qian CAI
Cancer Research on Prevention and Treatment 2025;52(11):913-925
The development of novel point-to-point drugs targeting resistance mechanisms is a critical and popular research field; nevertheless, success remains challenging. Therefore, given the short survival time and heightened expectations of patients with advanced NSCLC, the design of various combination therapy strategies––integrating preclinical, clinical, and real-world evidence (such as radiotherapy, chemotherapy, targeted therapy, antibody–drug conjugates, oncolytic viruses, and cell therapy)––may be a wise and practical choice to address the disease. Resistance to immunotherapy involves almost all cell types in the body, primarily cancer cells and T cells involved in immune surveillance. As a result of space limitations, this article focuses on the progress and challenges of various combined strategies for directly eliminating cancer cells. We also emphasize the realignment of treatment goals, shifting from primarily focusing on eliminating cancer cells (via chemotherapy and radiotherapy) to fully utilizing immune regulation to overcome resistance to immune checkpoint inhibitors.
4.Identification of telomere-related diagnostic markers in osteoarthritis based on bioinformatics analysis and machine learning
Sheng XU ; Jia YE ; Xiaochong CAI
The Korean Journal of Physiology and Pharmacology 2025;29(3):359-372
Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.
5.Identification of telomere-related diagnostic markers in osteoarthritis based on bioinformatics analysis and machine learning
Sheng XU ; Jia YE ; Xiaochong CAI
The Korean Journal of Physiology and Pharmacology 2025;29(3):359-372
Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.
6.Research progress on the mechanism of action of rosmarinic acid in the prevention of cardiovascular diseases
Ke CAI ; Sheng-ru HUANG ; Fang-fang GAO ; Xiu-juan PENG ; Sheng GUO ; Feng LIU ; Jin-ao DUAN ; Shu-lan SU
Acta Pharmaceutica Sinica 2025;60(1):12-21
With the rapid development of social economy and the continuous improvement of human living standard, the incidence, fatality and recurrence rates of cardiovascular disease (CVD) are increasing year by year, which seriously affects people's life and health. Conventional therapeutic drugs have limited improvement on the disability rate, so the search for new therapeutic drugs and action targets has become one of the hotspots of current research. In recent years, the therapeutic role of the natural compound rosmarinic acid (RA) in CVD has attracted much attention, which is capable of preventing CVD by modulating multiple signalling pathways and exerting physiological activities such as antioxidant, anti-apoptotic, anti-inflammatory, anti-platelet aggregation, as well as anti-coagulation and endothelial function protection. In this paper, the role of RA in the prevention of CVD is systematically sorted out, and its mechanism of action is summarised and analysed, with a view to providing a scientific basis and important support for the in-depth exploration of the prevention value of RA in CVD and its further development as a prevention drug.
7.Advances in prenatal imaging assessment of fetal malformation of cortical development
Simin ZHANG ; Changqing SHENG ; Yu ZHANG ; Chunyan ZHANG ; Xiaoxue YANG ; Yuanyuan MAN ; Yingying CAI ; Rui YAN ; Xinru GAO
Chinese Journal of Medical Imaging Technology 2025;41(3):377-381
Fetal malformation of cortical development(MCD)is a group of structural neurological disorders caused by abnormalities in development of cortical layer during embryogenesis,characterized by significant heterogeneity and diversity,which may lead to adverse clinical outcomes such as epilepsy and intellectual disabilities.The progresses in prenatal evaluation on fetal MCD were reviewed in this article.
8.Identification of telomere-related diagnostic markers in osteoarthritis based on bioinformatics analysis and machine learning
Sheng XU ; Jia YE ; Xiaochong CAI
The Korean Journal of Physiology and Pharmacology 2025;29(3):359-372
Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.
9.Identification of telomere-related diagnostic markers in osteoarthritis based on bioinformatics analysis and machine learning
Sheng XU ; Jia YE ; Xiaochong CAI
The Korean Journal of Physiology and Pharmacology 2025;29(3):359-372
Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.
10.Development of DUS testing guidelines for new Atractylodes lancea varieties.
Cheng-Cai ZHANG ; Ming QIN ; Xiu-Zhi GUO ; Zi-Hua ZHANG ; Hao-Kuan ZHANG ; Xiao-Yu DAI ; Sheng WANG ; Lan-Ping GUO
China Journal of Chinese Materia Medica 2025;50(6):1515-1523
Atractylodes lancea is a perennial herbaceous plant of Asteraceae, with rhizomes for medical use. However, A. lancea plants from different habitats have great variability, and the germplasm resources of A. lancea are unclear and mixed during production. Therefore, it is urgent to protect new varieties of A. lancea. The distinctness, uniformity, and stability(DUS) testing of new plant varieties is the foundation of plant variety protection, and the DUS testing guidelines are the technical basis for variety approval agencies to conduct DUS testing. In this study, the phenotypic traits of 94 germplasm accessions of A. lancea were investigated considering the breeding and variety characteristics of A. lancea in China. The traits were classified and described, and 24 traits were preliminarily determined, including 20 basic traits that must be tested and four traits selected to be tested. The 20 basic traits included 3 quality traits, 5 false quality traits, and 12 quantitative traits, corresponding to 1 plant traits, 2 stem traits, 8 leaf traits, 6 flower traits, and 3 seed traits. The measurement ranges and coefficients of variation of eight quantitative traits were determined, on the basis of which the grading criteria and codes of the traits were determined and assigned. The guidelines has guiding significance for the trait evaluation, utilization, and breeding of new varieties of A. lancea.
Atractylodes/growth & development*
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China
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Phenotype
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Guidelines as Topic
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Plant Breeding


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