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 assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged

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

Dopamine, as a catecholamine neurotransmitter widely distributed in the central nervous system, is involved in physiological functions such as motivation, arousal, reinforcement, and movement through various dopamine signaling pathways. The hippocampus receives dopaminergic neuron projections from regions such as the ventral tegmental area, locus coeruleus, and substantia nigra. Through D1-like and D2-like receptors, dopamine exerts significant regulatory effects such as spatial navigation, episodic memory, fear, anxiety, and reward. This review mainly summarizes the research progress on the functions of dopamine in the hippocampus from aspects including the sources of dopamine, receptor distribution and function, and the association of hippocampal dopamine system dysregulation with neurodegenerative diseases. The aim is to provide insights into the involvement of the dopamine system in hippocampal functions and the diagnosis and treatment of related diseases.
Hippocampus/physiology* ; Dopamine/physiology* ; Humans ; Animals ; Receptors, Dopamine D2/physiology* ; Memory/physiology* ; Signal Transduction/physiology* ; Neurodegenerative Diseases/physiopathology*

PURPOSE: The secondary damage of spinal cord injury (SCI) starts from the collapse of the blood spinal cord barrier (BSCB) to chronic and devastating neurological deficits. Thereby, the retention of the integrity and permeability of BSCB is well-recognized as one of the major therapies to promote functional recovery after SCI. Previous studies have demonstrated that activation of hypoxia inducible factor-1α (HIF-1α) provides anti-apoptosis and neuroprotection in SCI. Endogenous HIF-1α, rapidly degraded by prolylhydroxylase, is insufficient for promoting functional recovery. Dimethyloxalylglycine (DMOG), a highly selective inhibitor of prolylhydroxylase, has been reported to have a positive effect on axon regeneration. However, the roles and underlying mechanisms of DMOG in BSCB restoration remain unclear. Herein, we aim to investigate pathological changes of BSCB restoration in rats with SCI treated by DOMG and evaluate the therapeutic effects of DMOG. METHODS: The work was performed from 2022 to 2023. In this study, Allen's impact model and human umbilical vein endothelial cells were employed to explore the mechanism of DMOG. In the phenotypic validation experiment, the rats were randomly divided into 3 groups: sham group, SCI group, and SCI + DMOG group (10 rats for each). Histological analysis via Nissl staining, Basso-Beattie-Bresnahan scale, and footprint analysis was used to evaluate the functional recovery after SCI. Western blotting, TUNEL assay, and immunofluorescence staining were employed to exhibit levels of tight junction and adhesion junction of BSCB, HIF-1α, cell apoptosis, and endoplasmic reticulum (ER) stress. The one-way ANOVA test was used for statistical analysis. The difference was considered statistically significant at p < 0.05. RESULTS: In this study, we observed the expression of HIF-1α reduced in the SCI model. DMOG treatment remarkably augmented HIF-1α level, alleviated endothelial cells apoptosis and disruption of BSCB, and enhanced functional recovery post-SCI. Besides, the administration of DMOG offset the activation of ER stress induced by SCI, but this phenomenon was blocked by tunicamycin (an ER stress activator). Finally, we disclosed that DMOG maintained the integrity and permeability of BSCB by inhibiting ER stress, and inhibition of HIF-1α erased the protection from DMOG. CONCLUSIONS Our findings illustrate that the administration of DMOG alleviates the devastation of BSCB and HIF-1α-induced inhibition of ER stress.
Spinal Cord Injuries/pathology* ; Animals ; Apoptosis/drug effects* ; Amino Acids, Dicarboxylic/therapeutic use* ; Recovery of Function/drug effects* ; Rats ; Rats, Sprague-Dawley ; Hypoxia-Inducible Factor 1, alpha Subunit/metabolism* ; Male ; Spinal Cord/blood supply*

Objective:To investigate the safety and therapeutic effect of split liver transplantation (SLT) in clinical application.Methods:This is a retrospective case-series study. The clinical data of 203 consecutive SLT, 79 living donor liver transplantation (LDLT) and 1 298 whole liver transplantation (WLT) performed at the Third Affiliated Hospital of Sun Yat-sen University from July 2014 to July 2023 were retrospectively analyzed. Two hundred and three SLT liver grafts were obtained from 109 donors. One hundred and twenty-seven grafts were generated by in vitro splitting and 76 grafts were generated by in vivo splitting. There were 90 adult recipients and 113 pediatric recipients. According to time, SLT patients were divided into two groups: the early SLT group (40 cases, from July 2014 to December 2017) and the mature SLT technology group (163 cases, from January 2018 to July 2023). The survival of each group was analyzed and the main factors affecting the survival rate of SLT were analyzed. The Kaplan-Meier method and Log-rank test were used for survival analysis.Results:The cumulative survival rates at 1-, 3-, and 5-year were 74.58%, 71.47%, and 71.47% in the early SLT group, and 88.03%, 87.23%, and 87.23% in the mature SLT group, respectively. Survival rates in the mature SLT group were significantly higher than those in the early SLT group ( χ2=5.560, P=0.018). The cumulative survival rates at 1-, 3- and 5-year were 93.41%, 93.41%, 89.95% in the LDLT group and 87.38%, 81.98%, 77.04% in the WLT group, respectively. There was no significant difference among the mature SLT group, the LDLT group and the WLT group ( χ2=4.016, P=0.134). Abdominal hemorrhage, infection, primary liver graft nonfunction,and portal vein thrombosis were the main causes of early postoperative death. Conclusion:SLT can achieve results comparable to those of WLT and LDLT in mature technology liver transplant centers, but it needs to go through a certain time learning curve.

The biological clock(also known as the circadian rhythm)is the fundamental reliance for all organisms on Earth to adapt and survive in the Earth's rotation environment.Circadian rhythm is the most basic regulatory mechanism of life activities,and plays a key role in maintaining normal physiological and biochemical homeostasis,disease occurrence and treatment.Recent studies have shown that the biologi-cal clock plays an important role in the development of oral tissues and in the occurrence and treatment of oral diseases.Since there is cur-rently no guiding literature on the research methods of biological clock in stomatology,researchers mainly conduct research based on pub-lished references,which has led to controversy about the research methods of biological clock in stomatology,and there are many confusions about how to rationally apply the research methods of circadia rhythms.In view of this,this expert consensus summarizes the characteristics of the biological clock and analyzes the shortcomings of the current biological clock research in stomatology,and organizes relevant experts to summarize and recommend 10 principles as a reference for the rational implementation of the biological clock in stomatology research.

Neck dissection(ND)is one of the main treatment methods for oral and maxillofacial malignancies.Although ND type is in con-stant improvement,but intraoperative peal-pull-push injury of the accessory nerve,muscle,muscle membrane,fascia and ligament induced shoulder syndrome(SS)is still a common postoperative complication,combined with the influence of radiochemotherapy,not only can cause pain,stiffness,numbness,limited dysfunction of shoulder neck and arm,but also may have serious impact on patient's life quality and phys-ical and mental health.At present,there is still a lack of a systematic evaluation and rehabilitation management program for postoperative SS of oral and maxillofacial malignant tumors.Based on the previous clinical practice and the current available evidence,refer to the relevant lit-erature at home and abroad,the experts in the field of maxillofacial tumor surgery and rehabilitation were invited to discuss,modify and reach a consenusus on the etiology,assessment diagnosis,differential diagnosis,rehabilitation strategy and prevention of SS,in order to provide clinical reference.

Ferroptosis is a novel strategy for regulating cell death, and its occurrence is closely related to intracellular iron metabolism, lipid metabolism, amino acid metabolism, and various signaling pathways. Ferroptosis plays a pivotal role in the pathogenesis of acute kidney injury (AKI). Ferroptosis may serve as an important target for the treatment of AKI caused by various reasons such as ischemia-reperfusion injury, nephrotoxic drugs, rhabdomyolysis syndrome, sepsis, and so on. This paper reviewed the regulatory mechanisms of ferroptosis and its research progress in AKI.

Objective To explore the potential influencing factors of post-operative healthcare-associated infection(HAI)in colorectal cancer patients,as well as the mediating effect relationship between the influencing factors and the diagnosis-intervention packet(DIP)payment differentials.Methods Medical data of patients who underwent colorectal cancer surgery in a tertiary first-class cancer hospital in Guangzhou were retrospectively analyzed.According to HAI status,patients were divided into infection group and non-infection group.Baseline demographic information and differences in DIP payment differentials between two groups of patients were compared by rank sum test or chi-square test.The influence of each potential factor on the occurrence of HAI was analyzed by logistic re-gression.Mediating analysis was preformed by bootstrap method,and mediating effect of HAI and total hospitaliza-tion days on DIP payment differentials was evaluated.Results A total of 350 patients were included in analysis,50 were in the infection group and 300 in the non-infection group.The incidence of HAI was 14.29％.Logistic regres-sion analysis result showed that risk of HAI in patients with central venous catheterization ≥10.00 days was 13.558 times higher than that＜10.00 days(P＜0.001);risk of HAI in patients with urinary catheterization ≥3.00 days was 2.388 times higher than that＜3.00 days(P=0.022).There were all statistically significant differences in DIP payment differentials among patients with different ages,prognostic nutritional index(PNI),HAI status,total length of hospitalization stay,duration of surgery,central venous catheterization days,and catheterization days(all P＜0.05).The mediating analysis results showed that the occurrence of HAI resulted a change in DIP payment di-fferentials by affecting the total number of hospitalization days.The mediating effect value of total hospitalization days was 0.038,accounting for 35.68％of the total effect.Conclusion Medical institutions should pay attention to HAI resulting from prolonged central venous and urinary catheterization in patients underwent surgery for colorectal cancer,reducing the total length of hospital stay,thus reducing the overruns associated with the increased DIP pay-ment differentials.