BACKGROUND:Inter-limb asymmetry is a common phenomenon observed during human growth and development.Prolonged specialized training can lead to specific adaptations in inter-limb asymmetry among athletes.OBJECTIVE:To review the formation causes,manifestations,and impacts of inter-limb asymmetry on sports performance,and provide an overview of the relevant assessment methods and intervention strategies.METHODS:A literature search was conducted in the CNKI,WanFang,PubMed,and Web of Science databases from their inception to September 2024.The search terms included"asymmetry,asymmetries,asymmetric,asymmetrical,imbalance,strength,power,force,jump,sprint,athletic performance,anthropometry,injury"in English and Chinese.After excluding duplicate publications,irrelevant content,and conference papers,a total of 131 articles were finally included for analysis.RESULTS AND CONCLUSION:(1)Inter-limb asymmetry can be influenced by various factors including genetics,task demands,training regimens,injuries,fatigue,and limb preference.These factors lead to being primarily manifested in anatomical structure,strength performance,and task-specific asymmetry.(2)An increase in inter-limb asymmetry can result in impaired performance in bilateral in-phase symmetric movements.However,the relationship between increased inter-limb asymmetry and bilateral out-of-phase symmetric movements remains unclear and requires further investigation.(3)Training interventions have been shown to effectively mitigate inter-limb asymmetry,with unilateral training demonstrating superior outcomes compared with bilateral training.The choice of training methods and content should be tailored to meet the specific demands of the sport.(4)To further clarify the relationship between inter-limb asymmetry and athletic performance,it is recommended that future research adopt the concept of"task specificity"in inter-limb asymmetry.This includes standardizing study designs,selecting sensitive testing methods and indicators,unifying calculation methods to provide more high-quality evidence,and establishing categorized warning threshold standards for inter-limb asymmetry in different sports.

BackgroundIndividuals with schizophrenia are prone to higher rates of hospital readmission， presenting significant clinical challenges and imposing considerable social burdens within the mental health domain. In recent years， various risk prediction models have been developed to forecast readmission in patients with schizophrenia and support clinical decision-making， but their predictive performance and clinical applicability require comprehensive evaluation. ObjectiveTo systematically evaluate the risk prediction models for readmission in patients with schizophrenia， so as to provide insights for the development of high-performance and highly applicable readmission risk prediction models for patients with schizophrenia. MethodsOn July 5， 2025， a systematic literature search was conducted across multiple electronic databases， including PubMed， Embase， Cochrane Library， Web of Science， CINAHL， CNKI， China Biomedical Literature Database， Wanfang Database， and VIP Database， to identify risk prediction models for readmission in patients with schizophrenia. The search period was from the establishment of the databases to July 1， 2025. Two researchers independently performed literature screening， data extraction， risk of bias assessment， and applicability assessment. ResultsA total of 9 studies were included in this review， encompassing 18 risk prediction models for readmission in patients with schizophrenia. Among them， 4 models reported the area under the receiver operating characteristic （ROC） curve （AUC）， ranging from 0.734 to 0.820， 16 models provided AUC values of 0.642–0.879 for internal validation， and 1 model demonstrated an AUC of 0.841 for external validation. Key predictors included disease duration and the concomitant therapy of antipsychotic medications. The risk of bias was assessed as "high" in all included studies. ConclusionThe development of risk prediction models for readmission in patients with schizophrenia remains in an exploratory stage. Although the model exhibits favorable predictive performance， it is associated with a high risk of bias and insufficient performance evaluation.

The application of immunosuppressants has significantly reduced the incidence rate of rejection reaction after liver transplantation， but the clinical efficacy of immunosuppressants is greatly affected by individual differences between patients. This article systematically reviews the recent research advances in the interaction between immunosuppressants and gut microbiota， with a focus on the regulatory role and mechanism of intestinal microflora communities on the efficacy of immunosuppressants. Studies have shown that intestinal microbiome is one of the key factors influencing the efficacy of immunosuppressive therapy after liver transplantation. This review aims to provide a theoretical basis for in-depth research in this field and provide new insights for developing individualized immunosuppressive treatment regimens based on the regulation of intestinal microflora.

BACKGROUND:Inter-limb asymmetry is a common phenomenon observed during human growth and development.Prolonged specialized training can lead to specific adaptations in inter-limb asymmetry among athletes.OBJECTIVE:To review the formation causes,manifestations,and impacts of inter-limb asymmetry on sports performance,and provide an overview of the relevant assessment methods and intervention strategies.METHODS:A literature search was conducted in the CNKI,WanFang,PubMed,and Web of Science databases from their inception to September 2024.The search terms included"asymmetry,asymmetries,asymmetric,asymmetrical,imbalance,strength,power,force,jump,sprint,athletic performance,anthropometry,injury"in English and Chinese.After excluding duplicate publications,irrelevant content,and conference papers,a total of 131 articles were finally included for analysis.RESULTS AND CONCLUSION:(1)Inter-limb asymmetry can be influenced by various factors including genetics,task demands,training regimens,injuries,fatigue,and limb preference.These factors lead to being primarily manifested in anatomical structure,strength performance,and task-specific asymmetry.(2)An increase in inter-limb asymmetry can result in impaired performance in bilateral in-phase symmetric movements.However,the relationship between increased inter-limb asymmetry and bilateral out-of-phase symmetric movements remains unclear and requires further investigation.(3)Training interventions have been shown to effectively mitigate inter-limb asymmetry,with unilateral training demonstrating superior outcomes compared with bilateral training.The choice of training methods and content should be tailored to meet the specific demands of the sport.(4)To further clarify the relationship between inter-limb asymmetry and athletic performance,it is recommended that future research adopt the concept of"task specificity"in inter-limb asymmetry.This includes standardizing study designs,selecting sensitive testing methods and indicators,unifying calculation methods to provide more high-quality evidence,and establishing categorized warning threshold standards for inter-limb asymmetry in different sports.

Objective To identify potential drug target genes associated with idiopathic pulmonary fibrosis(IPF)and predict therapeutic candidates using a two-sample Mendelian randomization(MR)approach across the druggable genome.Methods Druggable genome data from the DGIdb database and Finan were integrated to identify overlapping genes.A two-sample MR analysis was performed to infer causal relationships between genes and IPF.Functional enrichment analyses,including Gene Ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG),were conducted to explore biological pathways.Drug-target interactions were predicted via DSigDB database screening,followed by molecular docking simulations to evaluate binding affinities.Results Among the 2588 overlapping druggable genes,thirty exhibited significant causal associations with IPF(P＜0.05).Four hub genes(NOD2,LATS2,LTA,and TCF7L2)were enriched in IPF-related pathways,notably Hippo and TNF signaling.Six potential therapeutics were identified:oxyphenbutazone,moexipril,α-galactosylceramide,GSK429286A,CGP74514A,and JW-7-24-1.Molecular docking confirmed strong binding affinities between these drugs and their targets.Conclusion This study has identified thirty druggable gene targets and six candidate drugs for IPF.The enrichment of hub genes in key pathways and validated drug-target interactions provide insights into IPF therapies.

Glycoprotein non-metastatic melanoma protein B (GPNMB) is a transmembrane glycoprotein that plays an important role in various physiological and pathological processes. In recent years, its role in lung diseases has gradually attracted attention. Studies have found that GPNMB is abnormally expressed in lung diseases and is involved in regulating pathological processes such as inflammatory responses, fibrosis, and tumorigenesis. This article systematically reviews the research progress of GPNMB in common lung diseases such as chronic obstructive pulmonary disease (COPD), pulmonary fibrosis, and lung cancer, and explores its potential as a therapeutic target, providing new insights for the diagnosis and treatment of lung diseases in the future.

Objective To investigate the effects of whole breast combined with regional nodal hypofractionated radiotherapy compared with conventional fractionated radiotherapy on peripheral lymphocyte count (PLC) and neutrophil-to-lymphocyte ratio (NLR) in patients with breast cancer after breast-conserving surgery. Methods This retrospective study enrolled 94 patients with breast cancer who underwent breast-conserving surgery in Tangshan People’s Hospital between April 2022 and April 2024. All patients received whole breast combined with regional nodal radiotherapy. These patients were divided into hypofractionated radiotherapy group (n = 42) and conventional fractionated radiotherapy group (n = 52) according to radiotherapy regimen. Differences in PLC and NLR before and after radiotherapy between the two groups were compared using the t-test. Results Before radiotherapy, the baseline PLC and NLR were comparable between the two groups (P > 0.05). After radiotherapy, PLC decreased and NLR increased in both groups (P < 0.05). The PLC in the hypofractionated radiotherapy group was significantly higher than that in the conventional fractionated radiotherapy group (0.95 ± 0.30 vs. 0.77 ± 0.26, P = 0.002), and the NLR was significantly lower in the hypofractionated radiotherapy group than in the conventional fractionated radiotherapy group (2.86 ± 1.27 vs. 3.67 ± 1.59, P = 0.010). Conclusion Compared with conventional fractionated radiotherapy, whole breast combined with regional nodal hypofractionated radiotherapy has less impact on PLC and NLR in patients with breast cancer after breast-conserving surgery.

With the rapid advancement of synthetic biology, CRISPR-Cas systems have emerged as a powerful tool for gene editing, demonstrating significant potential in various fields, including medicine, agriculture, and industrial biotechnology. This review comprehensively summarizes the significant progress in applying artificial intelligence (AI) technologies to the design, mining, and modification of CRISPR-Cas systems. AI technologies, especially machine learning, have revolutionized sgRNA design by analyzing high-throughput sequencing data, thereby improving the editing efficiency and predicting off-target effects with high accuracy. Furthermore, this paper explores the role of AI in sgRNA design and evaluation, highlighting its contributions to the annotation and mining of CRISPR arrays and Cas proteins, as well as its potential for modifying key proteins involved in gene editing. These advancements have not only improved the efficiency and precision of gene editing but also expanded the horizons of genome engineering, paving the way for intelligent and precise genome editing.
CRISPR-Cas Systems/genetics* ; Artificial Intelligence ; Gene Editing/methods* ; RNA, Guide, CRISPR-Cas Systems/genetics* ; Machine Learning ; Humans ; Genetic Engineering/methods* ; Synthetic Biology

Objective:Comprehensive characterization of B-cell phenotypes and spatial distribution in oral lichen planus (OLP) and related oral lichenoid lesions (OLL)(OLP/OLL), with an emphasis on transcriptomic profiling and functional analysis, to uncover the epigenetic mechanisms underlying B cell-mediated immune regulation within the oral mucosal microenvironment.Methods:Single-cell RNA sequencing raw data were sourced from the GSE211630 database, encompassing samples from 2 cases of erosive OLP (EOLP), 3 cases of non-erosive OLP (NEOLP) and 1 healthy control (NORMAL). Following stringent quality control, the data underwent normalization, selection of highly variable genes and batch effect correction. Subsequent analyses included dimensionality reduction and unsupervised clustering to identify distinct cell populations. This study collected pathological specimens from 3 OLP/OLL patients and 3 healthy controls who were treated at the Department of Oral Medicine, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine from January 2021 to December 2023. Using 10X Genomics Visium HD spatial transcriptomics technology, tissue sections were processed through dewaxing, staining and histological imaging, enabling the reconstruction of nucleic acid structures and the capture of gene expression profiles. Data analysis included quality assessment, gene quantification, normalization, dimensionality reduction and clustering. Furthermore, cell type deconvolution was performed using the robust cell type decomposition algorithm, integrating single-cell transcriptomic data to accurately predict and spatially resolve cell type distributions within the tissue microenvironment.Results:After integrating single-cell data from EOLP, NEOLP and NORMAL, cells were classified into seven major categories: B/plasma cells, endothelial cells, epithelial cells, fibroblasts, myeloid cells, smooth muscle cells and T/natural killer cells. The proportion of B/plasma cells varied significantly among the three groups, accounting for 10.7% (1 693/15 815), 3.8% (833/21 653) and 0.4% (47/11 556) of the total cells respectively. Further clustering analysis of B/plasma cells identified four distinct subpopulations: naive B cells, activated B cells, memory B cells and plasma cells. In the EOLP group, these subpopulations constituted 25.9% (348/1 344), 45.9% (617/1 344), 3.3% (45/1 344) and 24.9% (334/1 344) of the B/plasma cells respectively. In the NEOLP group, they represented 31.6% (195/617), 59.6% (368/617), 0.2% (1/617) and 8.6% (53/617). Howerer, only plasma cells were detected in the NORMAL group. Spatial analysis revealed that B cells were actively involved in the formation of tertiary lymphoid structures (TLS) at various stages in OLP/OLL samples, with a prominent structural organization observed in secondary follicle-like TLS. Within these structures, the expressions of T cells marker gene CD3E and B cells marker gene MS4A1 were significantly elevated. Additionally, in secondary follicle-like TLS, the gene encoding follicular dendritic cell secreted protein, germinal center marker gene B cell lymphoma 6 and the gene for activation induced cytidine deaminase also showed strong expression. In OLP/OLL samples, plasma cell marker gene CD38, immunoglobulin (IGH) G3, IGHG1, IGHM, IGHD, IGHE, imunoglobulin Kappa constant, immunoglobulin alpha 1, immunoglobulin Lambda constant 1 and complement gene C3 all exhibited high levels of expression.Conclusions:Compared to normal mucosa, extensive B-cell infiltration is observed in both OLP and OLL, accompanied by significant differences in B-cell phenotypes and proportions. B cells appear to play a central role in local immune responses, primarily through the formation of TLS. However, the precise functional mechanisms underlying their involvement require further investigation.

Breast cancer is the most prevalent malignant tumor that poses a threat to women's health in China,with incidence and mortality rates persistently increasing.Given this critical situation,there is an urgent need to optimize therapeutic options through basic translational research to address current treatment challenges.This article provided a comprehensive overview of the significant advancements in fundamental translational breast cancer research in China over the past five years,aiming to provide a scientific basis and new directions for precision treatment of breast cancer.This research encompasses a range of subjects,including molecular typing,biomarker identification,exploration of drug resistance mechanisms,optimization of precision treatment strategies,and identification of new targets in breast cancer.In the domain of molecular typing,researchers have revealed substantial disparities in treatment responses among distinct subtypes of breast cancer through in-depth analysis.This has led to the proposal of specific therapeutic strategies for each subtype,thereby establishing a robust theoretical foundation for individualized treatment approaches.The identification of biomarkers plays a pivotal role in selecting appropriate treatment options for patients.Recent research advancements have demonstrated the potential of liquid biopsy and proteomics technologies in uncovering promising biomarkers,offering novel prospects for the early diagnosis and prognostic assessment of breast cancer.In the investigation of resistance mechanisms,researchers have elucidated the molecular underpinnings of resistance to endocrine therapy and human epidermal growth factor receptor 2(HER2)-targeted therapy and proposed potential strategies to overcome resistance.This has paved the way for novel approaches to enhance therapeutic efficacy.In the context of immunotherapy and targeted therapies,the discernment of novel targets and biomarkers has facilitated novel perspectives on breast cancer treatment.Based on advanced comprehension of tumor heterogeneity,researchers constantly optimize precision treatment strategies through multiomics analysis,thus offering patients with breast cancer enhanced personalized treatment options.Concurrently,the implementation of novel technologies has been instrumental in facilitating the advancement of precision treatment for breast cancer.For instance,the application of artificial intelligence technology has demonstrated considerable potential in the early screening,diagnosis,efficacy assessment and prognosis prediction of breast cancer.Conversely,the advent of innovative drug delivery systems facilitated by nanotechnology has led to enhanced targeting and efficacy of pharmaceutical agents.Furthermore,research into hydrogel patch technology and tumor vaccines has yielded novel strategies for the treatment of breast cancer.Overall,China has accomplished remarkable achievements in the field of basic translational research on breast cancer.These findings not only enhance our understanding of the molecular mechanisms of breast cancer,but also provide new directions and hope for the development of future therapeutic strategies.With the advancement of multidisciplinary integration and the application of new emerging technologies,precision therapy is expected to provide more benefits to breast cancer patients.