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.

BACKGROUND: Temozolomide (TMZ) resistance is a significant challenge in treating glioblastoma (GBM). Collagen remodeling has been shown to be a critical factor for therapy resistance in other cancers. This study aimed to investigate the mechanism of TMZ chemoresistance by GBM cells reprogramming collagens. METHODS: Key extracellular matrix components, including collagens, were examined in paired primary and recurrent GBM samples as well as in TMZ-treated spontaneous and grafted GBM murine models. Human GBM cell lines (U251, TS667) and mouse primary GBM cells were used for in vitro studies. RNA-sequencing analysis, chromatin immunoprecipitation, immunoprecipitation-mass spectrometry, and co-immunoprecipitation assays were conducted to explore the mechanisms involved in collagen accumulation. A series of in vitro and in vivo experiments were designed to assess the role of the collagen regulators prolyl 4-hydroxylase subunit alpha 1 (P4HA1) and yes-associated protein (YAP) in sensitizing GBM cells to TMZ. RESULTS: This study revealed that TMZ exposure significantly elevated collagen type I (COL I) expression in both GBM patients and murine models. Collagen accumulation sustained GBM cell survival under TMZ-induced stress, contributing to enhanced TMZ resistance. Mechanistically, P4HA1 directly binded to and hydroxylated YAP, preventing ubiquitination-mediated YAP degradation. Stabilized YAP robustly drove collagen type I alpha 1 ( COL1A1) transcription, leading to increased collagen deposition. Disruption of the P4HA1-YAP axis effectively reduced COL I deposition, sensitized GBM cells to TMZ, and significantly improved mouse survival. CONCLUSION P4HA1 maintained YAP-mediated COL1A1 transcription, leading to collagen accumulation and promoting chemoresistance in GBM.
Temozolomide ; Humans ; Glioblastoma/drug therapy* ; Animals ; Mice ; Cell Line, Tumor ; Drug Resistance, Neoplasm/genetics* ; YAP-Signaling Proteins ; Hydroxylation ; Dacarbazine/pharmacology* ; Adaptor Proteins, Signal Transducing/metabolism* ; Transcription Factors/metabolism* ; Collagen/biosynthesis* ; Collagen Type I/metabolism* ; Prolyl Hydroxylases/metabolism* ; Antineoplastic Agents, Alkylating/therapeutic use*

Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a complex disease that is often accompanied by mental health disorders. However, the potential mechanisms underlying the heterogeneous clinical presentation of CP/CPPS remain uncertain. This study analyzed widely targeted metabolomic data of expressed prostatic secretions (EPS) and plasma to reveal the underlying pathological mechanisms of CP/CPPS. A total of 24 CP/CPPS patients from The Second Nanning People's Hospital (Nanning, China), and 35 asymptomatic control individuals from First Affiliated Hospital of Guangxi Medical University (Nanning, China) were enrolled. The indicators related to CP/CPPS and psychiatric symptoms were recorded. Differential analysis, coexpression network analysis, and correlation analysis were performed to identify metabolites that were specifically altered in patients and associated with various phenotypes of CP/CPPS. The crucial links between EPS and plasma were further investigated. The metabolomic data of EPS from CP/CPPS patients were significantly different from those from control individuals. Pathway analysis revealed dysregulation of amino acid metabolism, lipid metabolism, and the citrate cycle in EPS. The tryptophan metabolic pathway was found to be the most significantly altered pathway associated with distinct CP/CPPS phenotypes. Moreover, the dysregulation of tryptophan and tyrosine metabolism and elevation of oxidative stress-related metabolites in plasma were found to effectively elucidate the development of depression in CP/CPPS. Overall, metabolomic alterations in the EPS and plasma of patients were primarily associated with oxidative damage, energy metabolism abnormalities, neurological impairment, and immune dysregulation. These alterations may be associated with chronic pain, voiding symptoms, reduced fertility, and depression in CP/CPPS. This study provides a local-global perspective for understanding the pathological mechanisms of CP/CPPS and offers potential diagnostic and therapeutic targets.
Humans ; Male ; Prostatitis/blood* ; Adult ; Pelvic Pain/blood* ; Metabolomics ; Prostate/metabolism* ; Middle Aged ; Chronic Pain/blood* ; Metabolome ; Case-Control Studies ; Tryptophan/blood* ; Depression/blood* ; Oxidative Stress/physiology* ; Chronic Disease ; Lipid Metabolism/physiology*

Abstract In recent years, the prevalence of overweight and obesity among children and adolescents has risen rapidly, posing a serious threat to their physical and mental health. To provide scientific, systematic, and standardized weight management guidance for overweight and obese children and adolescents, the study focuses on the core concept of healthy lifestyle intervention, integrates multidisciplinary expert opinions and research findings,and proposes a comprehensive multidisciplinary intervention framework covering scientific exercise intervention, precise nutrition and diet, optimized sleep management, and standardized psychological support. It calls for the establishment of a multi agent collaborative management mechanism led by the government, implemented by families, fostered by schools, initiated by individuals, optimized by communities, reinforced by healthcare, and coordinated by multiple stakeholders. Emphasizing a child and adolescent centered approach, the consensus advocates for comprehensive, multi level, and personalized guidance strategies to promote the internalization and maintenance of a healthy lifestyle. It serves as a reference and provides recommendations for the effective prevention and control of overweight and obesity, and enhancing the health level of children and adolescents.

Patients with chronic kidney disease (CKD) have a relatively high risk of cardiovascular disease (CVD). Risk stratification guided by CVD risk prediction models is essential for managing CKD populations. We reviewed the outcome events, predictive variables, modeling methods, and predictive performance of CVD risk prediction models in CKD populations. We found a large variability in predictive outcomes, number of predictors, and sample sizes across studies. The models tended to overestimate the CVD risk of CKD populations. There are few independently validated or constructed CVD risk prediction models for CKD populations in developing countries, and in particular, there is a lack of independent external validation studies of model calibration. Future studies should comply with the reporting standards of risk prediction models to better support the application of CVD risk prediction models for CKD populations.

There are huge differences between tumor cells and normal cells in material metabolism, and tumor cells mainly show increased anabolism, decreased catabolism, and imbalance in substance metabolism. These differences provide the necessary material basis for the growth and reproduction of tumor cells, and also provide important targets for the treatment of tumors. Ferroptosis is an iron-dependent form of cell death characterized by an imbalance of iron-dependent lipid peroxidation and lipid membrane antioxidant systems in cells, resulting in excessive accumulation of lipid peroxide, causing damage to lipid membrane structure and loss of function, and ultimately cell death. The regulation of ferroptosis involves a variety of metabolic pathways, including glucose metabolism, lipid metabolism, amino acid metabolism, nucleotide metabolism and iron metabolism. In order for tumor cells to grow rapidly, their metabolic needs are more vigorous than those of normal cells. Tumor cells are metabolically reprogrammed to meet their rapidly proliferating material and energy needs. Metabolic reprogramming is mainly manifested in glycolysis and enhancement of pentose phosphate pathway, enhanced glutamine metabolism, increased nucleic acid synthesis, and iron metabolism tends to retain more intracellular iron. Metabolic reprogramming is accompanied by the production of reactive oxygen species and the activation of the antioxidant system. The state of high oxidative stress makes tumor cells more susceptible to redox imbalances, causing intracellular lipid peroxidation, which ultimately leads to ferroptosis. Therefore, in-depth study of the molecular mechanism and metabolic basis of ferroptosis is conducive to the development of new therapies to induce ferroptosis in cancer treatment. Ferroptosis, as a regulated form of cell death, can induce ferroptosis in tumor cells by pharmacologically or genetically targeting the metabolism of substances in tumor cells, which has great potential value in tumor treatment. This article summarizes the effects of cellular metabolism on ferroptosis in order to find new targets for tumor treatment and provide new ideas for clinical treatment.

Based on the background of a multidisciplinary treatment team and the increasing high-quality life aspirations of patients,the preservation of anal function for patients with low rectal cancer has undergone changes in recent years.With the optimization of neoadjuvant therapy,refinement of surgical techniques,and the deepening of the concept of anal preservation after surgery,the concept of anal preservation for low rectal cancer has gradually shifted from traditional simple surgery to comprehensive treatment,and anal preservation surgery tends to be more accurate preservation.The goal of comprehensive treatment is to preserve good anal function and reduce surgical damage.However,comprehensive treatment for anal preservation in low rectal cancer is still in its infancy,and there is no consensus on the strategy planning for anal preservation.Therefore,summarizing various preoperative,intraoperative,and postoperative treatment strategies for low rectal cancer is of great significance for the selection of anal preservation schemes for patients with low rectal cancer.This article focus on exploring the optimization of neoadjuvant therapy models,"watch and wait"plans,the development of anal preservation techniques,and postoperative and preservation strategies,aiming to review the current status of anal preservation strategy planning for low rectal cancer.

Sepsis is a life-threatening organ dysfunction caused by the host disordered response to infections.As one of the most important innate immune cells in the body，macrophages can maintain the immune homeostasis by recruiting other immune cells，clearing pathogens，presenting antigens，and play important regulatory roles in infectious diseases such as sepsis by releasing inflammatory factors.As a critical neurotransmitter，dopamine not only participates in the neurological processes such as learning and cognition，but also regulates the immune processes，including regulating the activation，proliferation and functional changes of immune cells such as neutrophils，lymphocytes，monocytes and macrophages.Current studies demonstrate that during the infection and inflammation process of sepsis，the phagocytosis，polarization，and release of inflammatory factors of macrophages are regulated by dopamine.This review summarized the recent research progress on the regulatory functions and the underlying mechanisms of dopamine on macrophages in sepsis.

Nanozymes, a groundbreaking discovery by Chinese scientists, represent a novel and remarkable property of nanomaterials. They not only exhibit catalytic activity comparable to natural enzymes, but also boast exceptional stability, tunable reactivity, and the ability to catalyze reactions under mild conditions. The identification of nanozymes has unveiled the biocatalytic potential of inorganic nanomaterials. In parallel, inorganic minerals have long been regarded as pivotal catalysts in the origin of life, driving the synthesis of early biomolecules. These minerals not only facilitate redox reactions that convert simple inorganic compounds into organic molecules but also enable chiral selection, the synthesis of biomacromolecules, and radioprotective functions via their surface structures. Recent advances suggest that inorganic nanomaterials can delicately catalyze the formation of biomolecules, aid in macromolecular assembly, and provide radiation shielding. Furthermore, nanominerals are found in abundance across Earth and extraterrestrial environments. This paper seeks to explore the potential of nanozymes as catalytic agents in the processes that gave rise to life, integrating the catalytic roles of inorganic minerals with the unique attributes of nanozymes, which will provide a new perspective for research of origin of life.

Objective To understand the current status and influencing factors of patient perception for humanistic care in China hospitals,and to provide a basis for developing nursing humanistic care measures and improving the quality of nursing humanistic care services.Methods A total of 30,099 outpatients and inpatients from 107 hospitals in 30 provinces(autonomous regions and municipalities)from July to August 2022 as survey subjects.A general information questionnaire and the Relational Caring Questionnaire-Patient Form were used for a cross-sectional survey,and a single-factor analysis was used to analyze the influencing factors of patient relationship care.Results Finally,29 108 valid questionnaires were collected,and the effective questionnaire recovery rate was 96.7％.The patient evaluation of relationship care was(65.72±8.61)points.Single-factor analysis showed that gender,age,marital status,children's situation,education level,occupation,place of residence,average family income,medical insurance type,visiting department,and location of the visiting hospital,and whether or not surgery were influencing factors of patient relationship care(P＜0.05).Conclusion The evaluation score of caregiver-patient relationship care among Chinese hospital patients is above average,but there is still room for improvement in western and rural regions,seriously ill and outpatient patients,low-income and low-medical insurance reimbursement populations,and non-surgical patients.Medical institutions at all levels should optimize and improve nursing humanistic care services based on influencing factors,and further enhance patients'perception of nursing humanistic care.