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 relationship between physical activity and genetic risk and their combined effects on the risk of developing chronic obstructive pulmonary disease. METHODS: This prospective cohort study included 318,085 biobank participants from the UK. Physical activity was assessed using the short form of the International Physical Activity Questionnaire. The participants were stratified into low-, intermediate-, and high-genetic-risk groups based on their polygenic risk scores. Multivariate Cox regression models and multiplicative interaction analyses were used. RESULTS: During a median follow-up period of 13 years, 9,209 participants were diagnosed with chronic obstructive pulmonary disease. For low genetic risk, compared to low physical activity, the hazard ratios ( HRs) for moderate and high physical activity were 0.853 (95% confidence interval [ CI]: 0.748-0.972) and 0.831 (95% CI: 0.727-0.950), respectively. For intermediate genetic risk, the HRs were 0.829 (95% CI: 0.758-0.905) and 0.835 (95% CI: 0.764-0.914), respectively. For participants with high genetic risk, the HRs were 0.809 (95% CI: 0.746-0.877) and 0.818 (95% CI: 0.754-0.888), respectively. A significant interaction was observed between genetic risk and physical activity. CONCLUSION Moderate or high levels of physical activity were associated with a lower risk of developing chronic obstructive pulmonary disease across all genetic risk groups, highlighting the need to tailor activity interventions for genetically susceptible individuals.
Humans ; Pulmonary Disease, Chronic Obstructive/epidemiology* ; Exercise ; Male ; Female ; Middle Aged ; Prospective Studies ; Aged ; Genetic Predisposition to Disease ; Risk Factors ; United Kingdom/epidemiology* ; Incidence ; Adult

Objective To analyze the changing trends of the burden of non-alcoholic fatty liver disease(NAFLD)in China from 1990 to 2021 and provide a basis for formulating prevention and treatment strategies.Methods The standardized incidence rate,prevalence,mortality,and disability-adjusted life year(DALY)rate of NAFLD in China from 1990 to 2021 were extracted from the Global Burden of Disease Study 2021.The average annual percentage change of rate data was calculated by Joinpoint 4.2 and the age,period,and birth cohort effects of the prevalence and DALY rate were analyzed by the age-period-cohort model.Results Compared to 1990,the incidence rate and prevalence of NAFLD have been on the rise,while the mortality and DALY rate have been declining.The age effect curves of prevalence and DALY rate showed an upward trend followed by a downward trend for both males and females.With the period from 1992 to 1996 as the reference group,the period effect curve of prevalence showed a downward trend followed by an upward trend,being the lowest in the period from 2002 to 2006(RR=0.93).The period effect curve of DALY rate showed a downward trend from 1992 to 2011 and then tended to flatten out.With the period from 1972 to 1981 as the reference group,the birth cohort effect curve of prevalence showed a steady upward trend in the general population and both male and female populations.The birth cohort effect curve of DALY rate showed an overall upward trend followed by a downward trend,with the peak occurring in the birth cohort group between 1922 and 1931.The DALY rate of NAFLD caused by smoking and high fasting blood glucose has shown a downward trend since 2014,and fasting blood glucose gradually became the dominant factor as age increased.Conclusions From 1990 to 2021,NAFLD in China has shown a rising prevalence but a significantly declining DALY rate.This suggests that current prevention and control strategies are effective,and further efforts should be made to raise residents' health awareness in controlling the occurrence and development of NAFLD.
Humans ; Non-alcoholic Fatty Liver Disease/epidemiology* ; China/epidemiology* ; Prevalence ; Female ; Male ; Incidence ; Disability-Adjusted Life Years ; Middle Aged ; Adult

OBJECTIVES: To explore the risk factors of feeding intolerance (FI) in critically ill children receiving enteral nutrition (EN) and to construct a prediction nomogram model for FI. METHODS: A retrospective study was conducted to collect data from critically ill children admitted to the Pediatric Intensive Care Unit of Xiangya Hospital, Central South University, between January 2015 and October 2020. The children were randomly divided into a training set (346 cases) and a validation set (147 cases). The training set was further divided into a tolerance group (216 cases) and an intolerance group (130 cases). Multivariate logistic regression analysis was used to screen for risk factors for FI in critically ill children receiving EN. A nomogram was constructed using R language, which was then validated on the validation set. The model's discrimination, calibration, and clinical net benefit were evaluated using receiver operating characteristic curves, calibration curves, and decision curves. RESULTS: Duration of bed rest, shock, gastrointestinal decompression, use of non-steroidal anti-inflammatory drugs, and combined parenteral nutrition were identified as independent risk factors for FI in critically ill children receiving EN (P<0.05). Based on these factors, a nomogram prediction model for FI in critically ill children receiving EN was developed. The area under the receiver operating characteristic curve for the training set and validation set was 0.934 (95%CI: 0.906-0.963) and 0.852 (95%CI: 0.787-0.917), respectively, indicating good discrimination of the model. The Hosmer-Lemeshow goodness-of-fit test showed that the model had a good fit (χ 2=12.559, P=0.128). Calibration curve and decision curve analyses suggested that the model has high predictive efficacy and clinical application value. CONCLUSIONS Duration of bed rest, shock, gastrointestinal decompression, use of non-steroidal anti-inflammatory drugs, and combined parenteral nutrition are independent risk factors for FI in critically ill children receiving EN. The nomogram model developed based on these factors exhibits high predictive efficacy and clinical application value.
Humans ; Critical Illness ; Enteral Nutrition/adverse effects* ; Male ; Risk Factors ; Female ; Child, Preschool ; Infant ; Nomograms ; Retrospective Studies ; Child ; Logistic Models

OBJECTIVES: To evaluate the efficacy and safety of avatrombopag in promoting platelet engraftment after allogeneic hematopoietic stem cell transplantation (allo-HSCT) in children, compared with recombinant human thrombopoietin (rhTPO). METHODS: A retrospective analysis was conducted on 53 pediatric patients who underwent allo-HSCT at the Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences from April 2023 to August 2024. Based on medications used during the periengraftment period, patients were divided into two groups: the avatrombopag group (n=15) and the rhTPO group (n=38). RESULTS: At days 14, 30, and 60 post-transplant, platelet engraftment was achieved in 20% (3/15), 60% (9/15), and 93% (14/15) of patients in the avatrombopag group, and in 39% (15/38), 82% (31/38), and 97% (37/38) in the rhTPO group, respectively. There were no significant differences between the two groups in platelet engraftment rates at each time point, cumulative incidence of platelet engraftment, overall survival, and relapse-free survival (all P>0.05). Multivariable Cox proportional hazards analysis indicated that acute graft-versus-host disease was an independent risk factor for delayed platelet engraftment (P=0.043). CONCLUSIONS In children undergoing allo-HSCT, avatrombopag effectively promotes platelet engraftment, with efficacy and safety comparable to rhTPO, and represents a viable therapeutic option.
Humans ; Retrospective Studies ; Hematopoietic Stem Cell Transplantation/adverse effects* ; Male ; Female ; Child ; Child, Preschool ; Infant ; Adolescent ; Transplantation, Homologous ; Blood Platelets/drug effects* ; Thiazoles/therapeutic use* ; Thrombopoietin/therapeutic use* ; Thiophenes

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

Enamel demineralization, the formation of white spot lesions, is a common issue in clinical orthodontic treatment. The appearance of white spot lesions not only affects the texture and health of dental hard tissues but also impacts the health and aesthetics of teeth after orthodontic treatment. The prevention, diagnosis, and treatment of white spot lesions that occur throughout the orthodontic treatment process involve multiple dental specialties. This expert consensus will focus on providing guiding opinions on the management and prevention of white spot lesions during orthodontic treatment, advocating for proactive prevention, early detection, timely treatment, scientific follow-up, and multidisciplinary management of white spot lesions throughout the orthodontic process, thereby maintaining the dental health of patients during orthodontic treatment.
Humans ; Consensus ; Dental Caries/etiology* ; Dental Enamel/pathology* ; Tooth Demineralization/etiology* ; Tooth Remineralization

Objective: There were associations between emotional abuse and neglect (EAN) and depression, but few studies had tested potential mechanisms underlying these relationships. We aimed to provide insights on how (the mediation role of neuroticism), and under what conditions (the moderator role of psychological resilience), led to a higher level of depression. Methods: This study was a cross-sectional study that used a random cluster sampling method. We randomly selected 3,993 participants from four junior middle schools in northern city of China. Participants were asked to complete four self-reported questionnaires, including the Childhood Trauma Questionnaire, Children Depression Inventory-Short Form, Chinese Big Five Personality Inventory Brief Version, and Chinese Resilience Scale. Results: The results showed that neuroticism mediated the associations between EAN and depression. In addition, the mediating effect of neuroticism was moderated by psychological resilience (p<0.05). Conclusion EAN and neuroticism could have an adverse impact on depression, and psychological resilience could alleviate these negative effects as a moderator. Our model suggested psychological resilience could be a particularly effective intervention point for victims of EAN.

Objective: There were associations between emotional abuse and neglect (EAN) and depression, but few studies had tested potential mechanisms underlying these relationships. We aimed to provide insights on how (the mediation role of neuroticism), and under what conditions (the moderator role of psychological resilience), led to a higher level of depression. Methods: This study was a cross-sectional study that used a random cluster sampling method. We randomly selected 3,993 participants from four junior middle schools in northern city of China. Participants were asked to complete four self-reported questionnaires, including the Childhood Trauma Questionnaire, Children Depression Inventory-Short Form, Chinese Big Five Personality Inventory Brief Version, and Chinese Resilience Scale. Results: The results showed that neuroticism mediated the associations between EAN and depression. In addition, the mediating effect of neuroticism was moderated by psychological resilience (p<0.05). Conclusion EAN and neuroticism could have an adverse impact on depression, and psychological resilience could alleviate these negative effects as a moderator. Our model suggested psychological resilience could be a particularly effective intervention point for victims of EAN.

ObjectiveTo investigate the role of 4-week high-intensity interval training (HIIT) in modulating the metabolic homeostasis of the pyruvate-lactate axis in the hippocampus of rats with chronic unpredictable mild stress (CUMS) to improve their depressive-like behavior. MethodsForty-eight SPF-grade 8-week-old male SD rats were randomly divided into 4 groups: the normal quiet group (C), the CUMS quiet group (M), the normal exercise group (HC), and the CUMS exercise group (HM). The M and HM groups received 8 weeks of CUMS modeling, while the HC and HM groups were exposed to 4 weeks of HIIT starting from the 5th week (3 min (85%-90%) S_max+1 min (50%-55%) S_max, 3-5 cycles, S_max is the maximum movement speed). A lactate analyzer was used to detect the blood lactate concentration in the quiet state of rats in the HC and HM groups at week 4 and in the 0, 2, 4, 8, 12, and 24 h after exercise, as well as in the quiet state of rats in each group at week 8. Behavioral indexes such as sucrose preference rate, number of times of uprightness and number of traversing frames in the absenteeism experiment, and other behavioral indexes were used to assess the depressive-like behavior of the rats at week 4 and week 8. The rats were anesthetized on the next day after the behavioral test in week 8, and hippocampal tissues were taken for assay. LC-MS non-targeted metabolomics, target quantification, ELISA and Western blot were used to detect the changes in metabolite content, lactate and pyruvate concentration, the content of key metabolic enzymes in the pyruvate-lactate axis, and the protein expression levels of monocarboxylate transporters (MCTs). Results4-week HIIT intervention significantly increased the sucrose preference rate, the number of uprights and the number of traversed frames in the absent field experiment in CUMS rats; non-targeted metabolomics assay found that 21 metabolites were significantly changed in group M compared to group C, and 14 and 11 differential metabolites were significantly dialed back in the HC and HM groups, respectively, after the 4-week HIIT intervention; the quantitative results of the targeting showed that, compared to group C, lactate concentration in the hippocampal tissues of M group, compared with group C, lactate concentration in hippocampal tissue was significantly reduced and pyruvate concentration was significantly increased, and 4-week HIIT intervention significantly increased the concentration of lactate and pyruvate in hippocampal tissue of HM group; the trend of changes in blood lactate concentration was consistent with the change in lactate concentration in hippocampal tissue; compared with group C, the LDHB content of group M was significantly increased, the content of PKM2 and PDH, as well as the protein expression level of MCT2 and MCT4 were significantly reduced. The 4-week HIIT intervention upregulated the PKM2 and PDH content as well as the protein expression levels of MCT2 and MCT4 in the HM group. ConclusionThe 4-week HIIT intervention upregulated blood lactate concentration and PKM2 and PDH metabolizing enzymes in hippocampal tissues of CUMS rats, and upregulated the expression of MCT2 and MCT4 transport carrier proteins to promote central lactate uptake and utilization, which regulated metabolic homeostasis of the pyruvate-lactate axis and improved depressive-like behaviors.