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 investigate the distribution characteristics of pathogens causing infections within 90 days after liver transplantation and the influencing factors of infection. Methods Clinical data of 176 recipients who underwent liver transplantation at the Liver Transplant Center of Beijing Friendship Hospital Affiliated to Capital Medical University from September 2021 to August 2024 were retrospectively analyzed. Patients were divided into the infection group (n=124) and the non-infection group (n=52) based on whether they developed infection within 90 days after transplantation. The distribution characteristics of pathogens in infected patients were analyzed. Univariate and multivariate logistic regression analyses were used to explore the influencing factors of infection. Results Among the 176 liver transplant recipients, 124 cases developed 243 episodes of 518 bacterial, fungal, viral or mycoplasma infections within 90 days after transplantation, with an overall infection rate of 70.5% (124/176). The composition of pathogens was mainly Gram-negative bacteria (38.6%, 200/518), followed by Gram-positive bacteria (32.2%, 167/518) and viruses (15.4%, 80/518), and fungi accounted for 13.1% (68/518). Among Gram-negative bacteria, the main pathogen was Klebsiella pneumoniae (6.8%, 35/518), and among Gram-positive bacteria, the main pathogen was Enterococcus faecalis (8.5%, 44/518). Viruses included Epstein-Barr virus (3.7%, 19/518) and cytomegalovirus (3.7%, 19/518), and fungi were mainly Candida albicans (6.8%, 35/518). The most common infection site among the 243 episodes was pulmonary infection (42.0%, 102/243), followed by abdominal infection (22.6%, 55/243) and bloodstream infection (18.1%, 44/243). The infections mainly occurred within 2 weeks after transplantation (60.9%, 148/243). Multivariate logistic regression analysis indicated that preoperative infection within 2 weeks, a high preoperative model for end-stage liver disease (MELD) score, and preoperative sarcopenia were independent risk factors for infection within 90 days after liver transplantation (all odds ratio>1, P<0.05). After multivariate correction, the levels of CD4⁺T cells and CD8⁺T cells within 90 days after surgery were independently associated with the occurrence of infection. Low levels of CD4⁺T cells and CD8⁺T cells might be related to an increased risk of infection. Conclusions The infection rate after liver transplantation is high, and the pathogens are mainly Gram-negative bacteria. The lungs are the most common infection site. Preoperative MELD score, preoperative sarcopenia and preoperative infection within 2 weeks are independent risk factors for infection within 90 days after liver transplantation. Regular monitoring of immune indicators CD4⁺T cells and CD8⁺T cells levels after transplantation is helpful to reduce the occurrence of post-transplantation infection.

Objective To explore the correlation between lymph node metastasis and clinicopathological features of lung adenocarcinoma with diameter≤3 cm. Methods The clinicopathologic data of the patients with lung adenocarcinoma≤3 cm in diameter were retrospectively analyzed. The relationship between lymph node metastasis and age, gender, smoking history, pathological subtype, tumor diameter, pleural invasion, vascular invasion and other factors was analyzed. The risk factors of lymph node metastasis were analyzed by univariate and multivariate logistic regression. Results Finally 1 718 patients were collected, including 697 males and 1 021 females with an average age of (58.89±9.85) years. The total lymph node metastasis rate was 12.9%, among whom 452 patients of adenocarcinoma in situ and minimally invasive adenocarcinoma did not have lymph node metastasis, and the lymph node metastasis rate of invasive lung adenocarcinoma was 17.5%. Multivariate analysis showed that tumor diameter, micropapillary subtype, solid subtype, micropapillary component, solid component, vascular invasion and pleural invasion were independent risk factors for lymph node metastasis of invasive lung adenocarcinoma with diameter≤3 cm (P<0.05). While age, lepidic subtype and lepidic component were independent protective factors for lymph node metastasis (P<0.05). Conclusion Clinicopathological features can help predict lymph node metastasis of lung adenocarcinoma with diameter≤3 cm.

Objective: To explore the latent profile characteristics of regulatory emotional self-efficacy and its relationship with non-suicidal self-injurious (NSSI) behavior among junior and senior high school students, so as to provide a basis for effectively reducing NSSI behaviors. Methods: From April to October 2023, a total of 1 217 junior and senior high school students were selected from Tongren City, Zunyi City and Qiannan Prefecture of Guizhou Province by stratified cluster random sampling method. The Scale of Regulatory Emotional Self-efficacy and the Adolescent Self-injury Scale were administered. Latent profile analysis (LPA) was employed to explore distinct profiles of regulatory emotional self-efficacy, and the Lanza, Tan, and Bray s method (LTB) was used to analyze the relationship between these profiles and NSSI behavior. Results: The prevalence rate of NSSI behavior among junior and senior high school students was 28.6%. Among males, regulatory emotional self-efficacy was categorized into two types: moderate positive expression-low negative management group (59.1%, n =353) and high efficacy group (40.9%, n =244); among females, regulatory emotional self-efficacy was classified into three categories: low efficacy group (18.4%, n =114), high positive expression-low negative management group (56.3%, n =349), and high efficacy group (25.3%, n =157). There were statistically significant differences in total NSSI scores across different potential categories of regulatory emotional self-efficacy within both males and females ( Z/H = -5.75 , 57.58, both P <0.01). The differences in NSSI prevalence rates across the potential categories of regulatory emotional self-efficacy were statistically significant for both males and females ( χ 2=38.00, 69.14, both P <0.01), and among females, the differences in NSSI prevalence rates between the high efficacy group and the low efficacy group ( χ 2=60.01) and between the high efficacy group and the high positive expression-low negative management group ( χ 2=31.34) were also statistically significant (both P < 0.016 7 ). Binary Logistic regression analysis revealed that, compared with the high efficacy group within each gender, the moderate positive expression-low negative management group among males ( OR =2.36), and both the low efficacy group and the high positive expression-low negative management group among females ( OR =6.19, 2.97), were at an increased risk of engaging in NSSI (all P <0.01). Conclusion Different latent profiles of regulatory emotional self efficacy among junior and senior high school students are associated with NSSI behavior.

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 investigate the epidemiological characteristics of lymphoma mortality and potential years of life lost among Wuhan residents, and to provide a scientific basis for the prevention and control of lymphoma. Methods Data on lymphoma deaths among residents in Wuhan from 2010 to 2019 were collected from the population-based Wuhan Mortality Surveillance System. Joinpoint regression model was used to evaluate the trends in age-standardized mortality rates and potential years of life lost due to lymphoma among the residents of different ages and genders. Potential years of life lost rate was used to assess the disease burden. Results There were 4 055 deaths (2481in male and 1 574 in female) from major kidney diseases in Wuhan residents between 2010 to 2019, with an age-standardized mortality rate of 5.11/100 000. The mortality rate of major kidney diseases showed an upward trend with increasing age. Between 2010 and 2019, the age-standardized mortality rates of the multiple myeloma and non-Hodgkin lymphoma were significantly increased (APC=6.924%, APC=1.407%, P＜0.05), and the potential years of life lost rate of non-Hodgkin lymphoma in female were significantly increased (APC=7.935%，P＜0.05). Conclusion From 2010 to 2019, the mortality rate of lymphoma among residents of Wuhan City shows an upward trend, especially for multiple myeloma and non-Hodgkin lymphoma. The disease burden of multiple myeloma shows an increasing trend in the female population, suggesting the need to take corresponding preventive and control measures.

ObjectiveThis paper aims to investigate the distribution patterns of traditional Chinese medicine syndromes in patients with chronic hepatitis B （CHB） comorbid with metabolically associated fatty liver disease （MAFLD） and analyze their correlation with clinical characteristics and the progression of liver fibrosis. MethodsA cross-sectional study method was employed， and 506 patients with CHB comorbid with MAFLD who attended the Hepatology Outpatient Department of Public Health Clinical Center of Chengdu from June 2024 to December 2024 were enrolled. General information， traditional Chinese medicine syndromes information， laboratory indicators， and imaging examination results were collected using case report forms （CRF）. Tongue images of patients were acquired using a tongue diagnosis instrument， and tongue feature parameters were extracted using computer image processing technology. Frequency analysis， factor analysis， and cluster analysis， and other methods were used to explore syndrome categories and distribution patterns. Non-parametric tests were used to compare the differences in clinical characteristics among different syndromes. Univariate and multivariate logistic regression analyses were performed to investigate the correlation between traditional Chinese medicine syndromes and the progression of liver fibrosis. ResultsThe main traditional Chinese medicine syndromes in patients with CHB comorbid with MAFLD were mainly dominated by damp-heat accumulation syndrome， liver stagnation and spleen deficiency syndrome， and phlegm-blood stasis syndrome， with damp-heat accumulation syndrome accounting for the highest proportion （41.89%）. Compared with those without damp-heat accumulation syndrome， patients with damp-heat accumulation syndrome had significantly lower tongue proper H value， tongue coating H value， and tongue coating a^* value （P<0.05）， significantly higher tongue coating b^* value （P<0.05）， significantly increased levels of white blood cell （WBC）， red blood cell （RBC）， hemoglobin （HGB）， and glucose （GLU）， increased CAP values （P<0.05）， a higher proportion of males （P<0.05）， and a younger age （P<0.05）. Univariate and multivariate logistic regression analyses show that age， hepatitis B surface antigen （HBsAg）， diabetes， and damp-heat accumulation syndrome are independent risk factors for liver fibrosis （P<0.05）， and that damp-heat accumulation syndrome is predominantly distributed in liver fibrosis stage F0-F1. ConclusionDamp-heat accumulation syndrome is a typical syndrome in patients with CHB comorbid with MAFLD， which is significantly associated with enhanced inflammatory response， metabolic disorders， and early liver fibrosis， and is a key link in disease progression. Clinical attention and early intervention are needed.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Objective To investigate the predictive value of preoperative combined detection of neutrophil-to-lymphocyte ratio (NLR) and prothrombin time-international normalized ratio to albumin ratio (PTAR) for early abdominal infection after liver transplantation. Methods Clinical data of 287 recipients who underwent liver transplantation at the Liver Transplant Center of Beijing Friendship Hospital, Affiliated to Capital Medical University, from January 2020 to April 2024 were retrospectively analyzed. The patients were divided into infection group (n=60) and non-infection group (n=227) based on whether abdominal infection occurred within 30 days after surgery. The distribution characteristics of pathogens and infection time in infected patients were analyzed. Spearman correlation analysis was used to assess the correlation between NLR, PTAR, Child-Pugh score and preoperative model for end-stage liver disease (MELD) score. Univariate and multivariate logistic regression analyses were performed to identify risk factors for abdominal infection. Receiver operating characteristic (ROC) curves were plotted for NLR, PTAR, and the combined prediction model to evaluate their predictive efficacy for abdominal infection after liver transplantation. Based on the cutoff value of the combined model, recipients were divided into low-risk and high-risk groups, and Kaplan-Meier analysis was used to compare the cumulative incidence of abdominal infection within 30 days after surgery between the two groups. Results Among the 287 recipients who underwent liver transplantation, 60 developed bacterial or fungal abdominal infections postoperatively. A total of 86 strains were isolated from infected patients, with Gram-negative bacteria accounting for 58%, Gram-positive bacteria for 36%, and fungi for 5%. Preoperative NLR and PTAR were positively correlated with Child-Pugh and MELD scores (all 1 > r > 0, P < 0.05). Logistic regression analysis showed that preoperative NLR, preoperative PTAR, postoperative ICU stay duration and postoperative biliary leakage were risk factors for abdominal infection within 30 days after surgery. The area under the curve (AUC) for NLR, PTAR, Child-Pugh score and MELD score were 0.771, 0.735, 0.650 and 0.741, respectively. The AUC for the combined NLR and PTAR prediction model was 0.824 (95% confidence interval: 0.763-0.885, P < 0.001), with a cutoff value of 0.168. Kaplan-Meier analysis showed that the cumulative incidence of abdominal infection within 30 days after surgery was lower in the low-risk group than in the high-risk group, with statistically significant difference (P < 0.001). Conclusions Preoperative NLR and PTAR are independent risk factors for abdominal infection within 30 days after liver transplantation. The combined prediction model of NLR and PTAR may effectively identify high-risk recipients for early abdominal infection after liver transplantation, providing basis for early intervention.