Objective: To investigate the nutritional status and influencing factors among Tibetan and Mongolian children and adolescents aged 7-18 years in high-altitude regions, so as to provide evidence for early prevention and control of malnutrition in this population. Methods: From May to June 2022, a cluster sampling method was employed to recruit 1 019 Tibetan and Mongolian children and adolescents aged 7-18 years from two primary and secondary schools in Golmud City. Physical examinations, dietary frequency questionnaires, and physical activity assessments were conducted. Nutritional status was classified as obesity, combined overweight/obesity, underweight, or central obesity according to national standards including Screening for Overweight and Obesity among School-age Children and Adolescents, Screening Standard for Malnutrition of School-age Children and Adolescents, Blue Book on Obesity Prevention and Control in China. Chi-square tests, t-test and Logistic regression analyses were performed to identify factors associated with different nutritional statuses. Results: The detection rates of obesity, combined overweight/obesity, underweight, and central obesity were 8.0%, 18.1%, 5.2%, and 19.7%, respectively. The height of children and adolescents across all age groups was generally lower than the national standard values. Tibetan participants exhibited significantly lower height-for-age Z-scores (HAZ)(9-10, 13-17 years, Z =2.01, 2.78, 4.16, 3.38, 4.12, 3.63, 3.00) and BMI-for-age Z-scores (BAZ) compared to Mongolian participants ( Z =-2.95, -2.47, -2.31, -2.89, -2.14, -2.17)( P < 0.05 ). Multivariate Logistic regression revealed that Mongolian children and adolescents had higher risks of obesity ( OR =2.20) and combined overweight/obesity ( OR = 2.18 ) ( P <0.05). Additionally, insufficient moderate-to-vigorous physical activity (MVPA) was associated with an increased risk of central obesity ( OR =1.48, P <0.05), compared with children and adolescents who meet the standard of MVPA. Conclusions The rates of overweight and obesity among Tibetan and Mongolian children and adolescents in Golmud City are higher, influenced by multiple factors. Nutrition interventions and physical activity strategies tailored to ethnic characteristics should be implemented, with emphasis on promoting MVPA to improve nutritional outcomes in this population.

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.

Liver ischemia-reperfusion injury (LIRI) is a pathological process involving multiple injury factors and cell types, with different stages. Currently, protective drugs targeting a single condition are limited in efficacy, and interventions on immune cells will also be accompanied by a series of side effects. In the current bottleneck research stage, the multi-target and obvious clinical efficacy of Chinese medicine (CM) is expected to become a breakthrough point in the research and development of new drugs. In this review, we summarize the roles of reactive oxygen species (ROS) and reactive nitrogen species (RNS) in various stages of hepatic ischemia-reperfusion and on various types of cells. Combined with the current research progress in reducing ROS/RNS with CM, new therapies and mechanisms for the treatment of hepatic ischemia-reperfusion are discussed.
Reperfusion Injury/drug therapy* ; Reactive Oxygen Species/metabolism* ; Reactive Nitrogen Species/metabolism* ; Humans ; Liver/drug effects* ; Animals ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/pharmacology*

OBJECTIVES: To explore the efficacy of DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy for management of cancer pain and provide reference for its standardized clinical application. Methods and. RESULTS: Recommendations were formulated based on literature review and expert group discussion, and consensus was reached following expert consultation. The consensus recommendations are comprehensive, covering the entire treatment procedures from preoperative assessment and preparation, surgical operation process, postoperative management and traditional Chinese medicine treatment to individualized treatment planning. The study results showed that the treatment plans combining traditional Chinese with Western medicine effectively alleviated cancer pain, reduced the use of opioid drugs, and significantly improved the quality of life and enhanced immune function of the patients. Postoperative follow-up suggested good treatment tolerance among the patients without serious complications. CONCLUSIONS The formulated consensus is comprehensive and can provide reference for clinicians to use DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy. The combined treatment has a high clinical value with a good safety profile for management of cancer pain.
Humans ; Medicine, Chinese Traditional ; Cancer Pain/therapy* ; Drugs, Chinese Herbal/therapeutic use* ; Drug Delivery Systems ; Pain Management/methods* ; China

Pulpotomy, which belongs to vital pulp therapy, has become a strategy for managing pulpitis in recent decades. This minimally invasive treatment reflects the recognition of preserving healthy dental pulp and optimizing long-term patient-centered outcomes. Pulpotomy is categorized into partial pulpotomy (PP), the removal of a partial segment of the coronal pulp tissue, and full pulpotomy (FP), the removal of whole coronal pulp, which is followed by applying the biomaterials onto the remaining pulp tissue and ultimately restoring the tooth. Procedural decisions for the amount of pulp tissue removal or retention depend on the diagnostic of pulp vitality, the overall treatment plan, the patient's general health status, and pulp inflammation reassessment during operation. This statement represents the consensus of an expert committee convened by the Society of Cariology and Endodontics, Chinese Stomatological Association. It addresses the current evidence to support the application of pulpotomy as a potential alternative to root canal treatment (RCT) on mature permanent teeth with pulpitis from a biological basis, the development of capping biomaterial, and the diagnostic considerations to evidence-based medicine. This expert statement intends to provide a clinical protocol of pulpotomy, which facilitates practitioners in choosing the optimal procedure and increasing their confidence in this rapidly evolving field.
Humans ; Calcium Compounds/therapeutic use* ; Consensus ; Dental Pulp ; Dentition, Permanent ; Oxides/therapeutic use* ; Pulpitis/therapy* ; Pulpotomy/standards*

With the growing emphasis on maternal and child oral health, the significance of managing oral health across preconception, pregnancy, and infancy stages has become increasingly apparent. Oral health challenges extend beyond affecting maternal well-being, exerting profound influences on fetal and neonatal oral development as well as immune system maturation. This expert consensus paper, developed using a modified Delphi method, reviews current research and provides recommendations on maternal and child oral health management. It underscores the critical role of comprehensive oral assessments prior to conception, diligent oral health management throughout pregnancy, and meticulous oral hygiene practices during infancy. Effective strategies should be seamlessly integrated across the life course, encompassing preconception oral assessments, systematic dental care during pregnancy, and routine infant oral hygiene. Collaborative efforts among pediatric dentists, maternal and child health workers, and obstetricians are crucial to improving outcomes and fostering clinical research, contributing to evidence-based health management strategies.
Humans ; Pregnancy ; Female ; Infant ; Consensus ; Mouth Diseases/therapy* ; Pregnancy Complications/therapy* ; Oral Health ; Infant, Newborn ; Delphi Technique ; Oral Hygiene

Pelvic organ prolapse (POP), whose etiology is influenced by genetic and clinical risk factors, considerably impacts women's quality of life. However, the genetic underpinnings in non-European populations and comprehensive risk models integrating genetic and clinical factors remain underexplored. This study constructed the first polygenic risk score (PRS) for POP in the Chinese population by utilizing 20 disease-associated variants from the largest existing genome-wide association study. We analyzed a discovery cohort of 576 cases and 623 controls and a validation cohort of 264 cases and 200 controls. Results showed that the case group exhibited a significantly higher PRS than the control group. Moreover, the odds ratio of the top 10% risk group was 2.6 times higher than that of the bottom 10%. A high PRS was significantly correlated with POP occurrence in women older than 50 years old and in those with one or no childbirths. As far as we know, the integrated prediction model, which combined PRS and clinical risk factors, demonstrated better predictive accuracy than other existing PRS models. This combined risk assessment model serves as a robust tool for POP risk prediction and stratification, thereby offering insights into individualized preventive measures and treatment strategies in future clinical practice.
Humans ; Female ; Pelvic Organ Prolapse/epidemiology* ; Middle Aged ; Risk Assessment/methods* ; China/epidemiology* ; Multifactorial Inheritance ; Aged ; Risk Factors ; Genome-Wide Association Study ; Genetic Predisposition to Disease ; Case-Control Studies ; Adult ; Polymorphism, Single Nucleotide ; Genetic Risk Score ; East Asian People

Identifying drug-drug interactions (DDIs) is essential to prevent adverse effects from polypharmacy. Although deep learning has advanced DDI identification, the gap between powerful models and their lack of clinical application and evaluation has hindered clinical benefits. Here, we developed a Multi-Dimensional Feature Fusion model named MDFF, which integrates one-dimensional simplified molecular input line entry system sequence features, two-dimensional molecular graph features, and three-dimensional geometric features to enhance drug representations for predicting DDIs. MDFF was trained and validated on two DDI datasets, evaluated across three distinct scenarios, and compared with advanced DDI prediction models using accuracy, precision, recall, area under the curve, and F1 score metrics. MDFF achieved state-of-the-art performance across all metrics. Ablation experiments showed that integrating multi-dimensional drug features yielded the best results. More importantly, we obtained adverse drug reaction reports uploaded by Xiangya Hospital of Central South University from 2021 to 2023 and used MDFF to identify potential adverse DDIs. Among 12 real-world adverse drug reaction reports, the predictions of 9 reports were supported by relevant evidence. Additionally, MDFF demonstrated the ability to explain adverse DDI mechanisms, providing insights into the mechanisms behind one specific report and highlighting its potential to assist practitioners in improving medical practice.

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Objective To evaluate the predictors of biochemical recurrence after laparoscopic radical prostatectomy.Methods The study cohort consisted of 416 consecutive prostatecancer patients who underwent radical prostatectomy in Zhongshan Hospital,Fudan University between Jan 2016 and Jun 2018.No patient received adjuvant therapy until documented biochemical recurrence.Biochemical recurrence-free survival(BCRFS)was estimated using the Kaplan-Meier method.Univariable and multivariable Cox proportional hazards regression models were utilized to determine variables predictive of biochemical recurrence.Results The median follow-up period was 174 weeks(inter quartile range 133-209 weeks).The overall biochemical recurrence rate was 21.39%(88/416).The time to biochemical recurrence was(51.11±47.71)weeks.Until the end of follow-up,the biochemical recurrence rates were 10%(1/10),6.12%(3/49),16.41%(43/262)and 43.16%(41/95)for low-risk,medium-risk,high-risk and locally advanced prostate cancer,respectively.On multivariable analysis,tumor invasion of the seminal vesicles(HR:2.119,95%CI:1.154-3.891,P=0.016);Seminal vesicle invasion(HR:1.824,95%CI:1.034-3.220,P=0.038),Gleason score≥8(HR:2.746,95%CI:1.268-5.943,P=0.010),prostate-specific antigen(PSA)=10-20 ng/mL(HR:4.240,95%CI:2.550-7.050,P<0.001);PSA>20 ng/mL(HR:6.341,95%CI:3.296-12.202,P<0.001)were the main predictors of biochemical recurrence.Conclusion Laparoscopic radical prostatectomy provides effective control of biochemical recurrence during the mid-term follow-up period.Tumor invasion of the seminal vesicles,seminal vesicle invasion,GS≥8,PSA=10-20 ng/mL,PSA>20 ng/mL were important predictors of biochemical recurrence after radical prostatectomy.