ObjectiveTo systematically evaluate the effect of intermittent theta burst stimulation (iTBS) on lower extremity motor function and balance function in patients with stroke. MethodsA systematic literature search was conducted in the Cochrane Library, Embase, PubMed, Web of Science, CNKI, SinoMed, Wanfang data and VIP from inception to February 19, 2025. Randomized controlled trials comparing iTBS with conventional rehabilitation or sham iTBS in patients with post-stroke lower extremity motor and balance dysfunction were included. The methodological quality of the included studies was assessed using the Cochrane Risk of Bias Tool. Meta-analysis was performed using RevMan 5.4 and Stata 14.0. ResultsA total of 16 articles involving 647 patients were included. Meta-analysis showed that iTBS improved the Fugl-Meyer Assessment-Lower Extremities score (MD = 2.58, 95%CI 1.61 to 3.55, P < 0.001), Berg Balance Scale score (MD = 4.11, 95%CI 2.43 to 5.79, P < 0.001), Barthel Index score (MD = 4.95, 95%CI 0.97 to 8.92, P = 0.010) and motor-evoked potential (MEP) latency (MD = -1.42, 95%CI -2.54 to -0.30, P = 0.010). Subgroup analyses suggested that at subacute stage, cerebellar iTBS, more than ten treatment sessions, and 1 200 pulses per day may be more effective. ConclusioniTBS may improve lower extremity motor function and activities of daily living in patients with stroke, and shorten MEP latency, and it may also confer potential benefits in improving balance function in these patients.

Drug development remains a critical issue in the field of biomedicine.With the rapid advancement of information technologies such as artificial intelligence(AI)and the advent of the big data era,AI-assisted drug development has become a new trend,particularly in predicting drug-target associations.To address the challenge of drug-target prediction,AI-driven models have emerged as powerful tools,of-fering innovative solutions by effectively extracting features from complex biological data,accurately modeling molecular interactions,and precisely predicting potential drug-target outcomes.Traditional machine learning(ML),network-based,and advanced deep learning architectures such as convolutional neural networks(CNNs),graph convolutional networks(GCNs),and transformers play a pivotal role.This review systematically compiles and evaluates AI algorithms for drug-and drug combination-target predictions,highlighting their theoretical frameworks,strengths,and limitations.CNNs effectively identify spatial patterns and molecular features critical for drug-target interactions.GCNs provide deep insights into molecular interactions via relational data,whereas transformers increase prediction accu-racy by capturing complex dependencies within biological sequences.Network-based models offer a systematic perspective by integrating diverse data sources,and traditional ML efficiently handles large datasets to improve overall predictive accuracy.Collectively,these AI-driven methods are transforming drug-target predictions and advancing the development of personalized therapy.This review summa-rizes the application of AI in drug development,particularly in drug-target prediction,and offers rec-ommendations on models and algorithms for researchers engaged in biomedical research.It also provides typical cases to better illustrate how AI can further accelerate development in the fields of biomedicine and drug discovery.

Traditional Chinese medicine (TCM) is characterized by complex, multicomponent herbal formulations that challenge the conventional“one drug, one target” paradigm. Network pharmacology, through the construction of multilayered drug-target-disease networks, provides a systematic framework for unraveling TCM’s multitarget and multipathway mechanisms. Recent advancements in artificial intelligence, particularly large language models (LLMs), further enhance data integration, target identification, and clinical decision-making. This review synthesizes current progress in the application of network pharmacology and LLMs in TCM, highlighting their potential to deepen mechanistic insights and optimize drug discovery. By bridging traditional medical wisdom with modern computational tools, this integrative approach aims to advance the scientific validation of TCM and foster innovative healthcare solutions.

Objective:To investigate the co-occurrence patterns of psychosocial and behavioral problems among children and to identify associated influencing factors.Methods:A multicenter cross-sectional survey was conducted in 2023. A cluster random sample of 19 176 children aged 6-16 years was recruited from middle-income areas across 10 provincial capitals and municipalities in China. Psychological and behavioral problems, including anxiety, compulsive behavior, social withdrawal, depression, somatic complaints, social problems, schizoid, delinquent behaviors, hyperactivity, sexual issues, and aggression, were assessed using the Achenbach Child Behavior Checklist parent version. Co-occurrence was defined as ≥2 concurrent problems. Children were divided into 4 groups by gender and age: boys aged 6-11 years, girls aged 6-11 years, boys aged 12-16 years, and girls aged 12-16 years. Those children who had psychosocial and behavioral problems were further categorized into the single-problem group, and the co-occurrence group based on assessment results. High-frequency co-occurrence phenotypes of children′s psychosocial and behavioral problems were identified. Demographic factors, such as parental employment, education, as well as psychosocial factors like parent-child relationship, screen time and outdoor activity, were investigated. χ 2 test was used to analyze differences between groups. Multivariate Logistic regression modeling was conducted to identify potential factors. Results:Among 14 711 children (7 501 boys, 7 210 girls) who provided effective questionnaires, the detection rates of single problem in the boys aged 6-11 years, girls aged 6-11 years, boys aged 12-16 years, and girls aged 12-16 years groups were 4.9% (171/3 461), 6.2% (193/3 120), 3.9% (158/4 040), and 5.1% (208/4 090), respectively; the detection rates of co-occurrence were 7.6% (262/3 461), 7.7% (241/3 120), 4.9% (199/4 040), and 5.7% (234/4 090), respectively. The overall detection rates of co-occurrence was higher than that of single problem ( χ2=25.47, P<0.001). Among children with co-occurrence, there were varied manifestations: in the boys aged 6-11 years group, the detection rates of social withdrawal (69.8% (183/262)), schizoid-like behavior (68.3% (179/262)), and compulsive behavior (67.6% (177/262)) were relatively high; in the girls aged 6-11 years group, the detection rates of schizoid-compulsive behavior (69.3% (167/241)), delinquent behavior (65.6% (158/241)), and hyperactivity (58.9% (142/241)) were relatively high; in the boys aged 12-16 years group, the detection rates of hyperactivity (78.9% (157/199)), compulsive behavior (67.3% (134/199)), and immature behavior (57.3% (114/199)) were relatively high; in the girls aged 12-16 years group, the detection rates of schizoid-like behavior (89.7% (210/234)), immature behavior (59.0% (138/234)), and cruelty (57.7% (135/234)) were relatively high. Maternal bachelor′s degree or higher ( OR=0.78, 95% CI 0.61-0.99, P=0.038) served as co-occurrence protective factors, whereas having 1 or more siblings, increased parent-child conflict and decreased parent-child interaction time ( OR=1.24, 1.41, 1.36; 95% CI 1.02-1.52, 1.15-1.73, 1.02-1.82, all P<0.05) were co-occurrence risk factors. Conclusions:Children exhibit strong co-occurrence tendencies in psychosocial and behavioral problems. Compulsive and schizoid traits are the predominant co-occurring phenotypes for childhood and girls respectively. ?Familial environment plays a critical role, necessitating ?multidimensional clinical assessments and ?family-centered interventions.

Chronic atrophic gastritis(CAG)is a chronic gastric disorder characterized by recurrent damage to the gastric mucosal epithelium,resulting in the reduction of intrinsic glands,with or without concurrent intestinal metaplasia.The"hyperactive stomach qi"theory,derived from Huang Di Nei Jing Su Wen Ji Zhu,proposes that the core pathogenesis of CAG lies in excessive stomach qi activity,grounded in the physiological principle of"strong yang qi in earth and weak yin qi in earth".This theory synthesizes the clinical manifestations and pathological progression of CAG,asserting that its development often involves intertwined pathological factors such as stagnation,dryness-heat,phlegm-dampness and stasis-toxicity.A triphasic therapeutic framework is proposed:the spleen qi deficiency phase,marked by impaired spleen transport function and dysregulated qi-fluid distribution,requiring spleen fortification and qi-fluid regulation;the hyperactive stomach qi phase,characterized by intensified stomach qi activity coupled with dryness-damp stagnation,necessitating stagnation resolution,dampness elimination and yin nourishment;the decline and disorder of middle qi phase,characterized by the deficiency of the middle qi,with phlegm,blood stasis and toxins forming the terminal stage.Treatment should focus on reinforcing the middle and restoring balance,detoxifying and dissipating accumulation.By exploring CAG pathogenesis and treatment through the lens of"hyperactive stomach qi",this study aimed to provide novel theoretical insights and therapeutic strategies for TCM in the prevention and treatment of CAG.

Eye-tracking technology monitors eye movement trajectories to reveal the cognitive mechanisms underlying visual behavior.With advantages like objectivity and real-time capability,it is increasingly applied in nursing.However,research and application in China are still in the early stages.This article reviews the development,measurement metrics,methods,and impact of eye-tracking in nursing,analyzes current challenges,and suggests solutions to aid its development in the field of nursing in China.

Objective To explore the mechanism by which the early growth response protein 1(EGR1)/AMP-activated protein kinase(AMPK)/nuclear factor erythroid 2-related factor 2(Nrf2)pathway improves Neuro-2a cell injury via Mendelian randomization(MR),bioinformatics and in vitro models of ischemic stroke(IS).Methods The blood proteins associated with genetic susceptibility to IS were identified based on MR analysis.Then,the GSE22255 dataset was comprehensively analyzed,including GSEA,immunoinfiltration and differential expression analysis.The transcription factors closely related to the occurrence and development of IS were identified after joint analysis with MR results,and the biological functions of key genes were further verified by in vitro experiments.Results A total of 712 proteins related to IS susceptibility were identified by MR analysis.A total of 2357 differentially expressed genes were identified from the GSE22255 dataset,and 75 intersection genes and 34 transcription factors were identified after combined analysis with MR results.In vitro experiments showed that knockdown of EGR1 expression could significantly inhibit oxygen-glucose deprivation/reperfusion(OGD/R)-induced Neuro-2a cell damage,and the mechanism might be related to the up-regulation of p-AMPK and Nrf2 protein expression.Conclusion This study integrates MR analysis,transcriptomics and in vitro experiments to reveal the potential role of 75 IS susceptibility genes and transcription factor EGR1 in the pathogenesis of IS,which provides theoretical basis for the development of therapeutic drugs for IS.

Objective To comprehensively evaluate the prevalence of and influencing factors for low-level viraemia(LLV)in Chinese patients receiving antiviral therapy for human immunodeficiency virus(HIV)infection through systematic review and Meta-analysis.Methods Cochrane Library,Web of Science,Embase,PubMed,China Bio-medicine(CBM),VIP,China National Knowledge Infrastructure(CNKI),and Wanfang Data were systematically retrieved.Retrieval time was from the establishment of the database to February 2024.Literatures related to the prevalence of LLV in patients receiving antiviral therapy for HIV infection were retrieved using combination of key-words and free words.Stata 16.0 software was used for Meta-analysis.Random effects model was adopted to calcu-late the combined prevalence and its 95％confidence interval.Results A total of 15 papers were included in analy-sis,involving 191 212 specimens.Meta-analysis random effects model showed that the prevalence of LLV in Chinese patients receiving antiviral therapy for HIV infection was 13.00％(95％CI:7.82％-19.24％).Subgroup analysis showed that cross-sectional studies,northern regions,males,age ≥50 years,heterosexual transmission routes,baseline CD4+T lymphocyte count＜200 cells/μL,and patients who had ever changed therapy regimens had higher LLV prevalence.Conclusion The prevalence of LLV in patients receiving antiviral therapy for HIV infection is re-latively higher.Attention should be paid to such high-risk population,and appropriate antiviral therapy schemes should be selected as early as possible.Timely intervention is necessary when LLV occurs.

Meat food is an important part of people's dietary supplements,but in recent years,meat adulteration cases are hidden and frequent,which seriously affects people's health and destroys the fairness of the market.Based on this,this paper analyses the development trend of meat adulteration and the current meat adulteration detection technology is summarized,combed in detail the use of the most widely used real-time fluorescence quantitative PCR technology application of the status quo and challenges to help real-time fluorescence quantitative PCR technology testing in meat adulteration evidence testing to the direction of more high detection efficiency and higher accuracy development.

Objective: To screen and identify the key active molecules, signaling pathways, and therapeutic targets of Shuxuening (SXN) injection for treating liver cirrhosis (LC) and to evaluate its therapeutic potential using a mouse model. Methods: Target genes of SXN and LC were retrieved from public databases, and enrichment analysis was performed. A protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and hub genes were identified using Molecular Complex Detection (MCODE). LC was induced in rats and mice via intraperitoneal injections of diethylnitrosamine and carbon tetrachloride (CCl4) for 12 weeks. Starting at week 7, SXN was administered intraperitoneally to the mice in the treatment group. Serum and liver tissues of the mice were collected for the detection of indicators, pathological staining, and expression analysis of hub targets using quantitative real-time polymerase chain reaction (qRT-PCR). Results: We identified 368 overlapping genes (OLGs) between SXN and LC targets. These OLGs were subsequently used to build a PPI network and to screen for hub genes. Enrichment analysis showed that these genes were associated with cancer-related pathways, including phosphoinositide-3-kinase/Akt and mitogen-activated protein kinase signaling and various cellular processes, such as responses to chemicals and metabolic regulation. In vivo experiments demonstrated that SXN treatment significantly improved liver function and pathology in CCl4-induced LC mice by reducing inflammation and collagen deposition. Furthermore, qRT-PCR demonstrated that SXN regulated the expression of MAPK8, AR and CASP3 in the livers of LC mice. Conclusion This study highlighted the therapeutic effects of SXN in alleviating LC using both bioinformatics and experimental methods. The observed effect was associated with modulation of hub gene expression, particularly MAPK8, and CASP3.