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.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To explore the association between plasma fibrinogen(FBG)levels and the risk of in-hospital mortality among patients with septic shock.Methods The clinical data of 563 patients diagnosed with septic shock in the Intensive Care Unit(ICU)of Shenzhen Second People's Hospital from August 1,2018,to December 31,2020,were collected.Patient demographic information,basic vital signs,and blood routine and biochemical indices upon admission were gathered.Moreover,the Acute Physiology and Chronic Health Evaluation Ⅱ(APACHEⅡ)scores were calculated.Binary logistic regression analysis was conducted to explore the correlation between plasma fibrinogen levels and in-hospital mortality in patients with septic shock.Additionally,a generalized additive model(GAM)and smoothed curve fitting were employed to investigate the nonlinear relationship between plasma fibrinogen and in-hospital mortality.Receiver operating characteristic(ROC)curves were constructed for FBG and APACHEⅡ scores to predict in-hospital mortality in septic shock patients.The area under the curve(AUC)was computed to compare the predictive efficacies of the two.Furthermore,a segmented linear regression model was utilized for quantification.Results Binary logistic regression analysis demonstrated a significant negative correlation between plasma fibrinogen levels and in-hospital mortality among patients with septic shock(P<0.05).GAM modeling and smoothed curve fitting disclosed a nonlinear association between plasma fibrinogen levels and in-hospital mortality,with an inflection point at 5.54 g/L.The segmented linear regression model indicated that,to the left of the inflection point(FBG≤5.54 g/L),for every 1 g/L decrease in plasma fibrinogen,the risk of death increased by 24.5%(OR=0.755,P=0.003).Conversely,to the right of the inflection point(FBG>5.54 g/L),the relationship was not statistically significant(OR=1.049,P=0.685).The findings of the subgroup analyses indicated that the characteristics of the subgroups did not alter the relationship between blood fibrinogen levels and in-hospital mortality.Conclusion There is a nonlinear relationship between FBG levels and in-hospital mortality in patients with septic shock,which has predictive value for evaluating the risk of in-hospital mortality in this patient cohort.

OBJECTIVE To explore the ameliorative effect of Tiaozhi Xiaoban Mixture on atherosclerosis and the potential role of long non-coding RNA(Linc RNA)in anti-atherosclerosis.METHODS A model of atherosclerosis was established in SD rats subjec-ted to a high-fat diet.At 4 weeks post-modeling,thoracic aortic tissues from atherosclerotic rats were collected for hematoxylin-eosin(HE)staining to systematically evaluate the anti-atherosclerotic effects of Tiaozhi Xiaoban Mixture at different doses.Biochemical kits were utilized to assess relevant indices related to blood lipid levels as well as liver and kidney function,thereby evaluating the impact of Tiaozhi Xiaoban Mixture on these parameters.Enzyme-linked immunosorbent assay(ELISA)was employed to measure serum inflam-mation markers influenced by Tiaozhi Xiaoban Mixture.Additionally,TUNEL staining and Western blot analysis were conducted to ex-amine the apoptotic effects of Tiaozhi Xiaoban Mixture on thoracic aorta tissue.Finally,qPCR was used to detect the expression levels of Line-HC,MALAT1,etc.,in order to evaluate how Tiaozhi Xiaoban Mixture affecting these specific RNA molecules.RESULTS Following treatment with Tiaozhi Xiaoban Mixture,the blood lipid profiles indicated that total cholesterol(TC),triglycerides(TG),and low-density lipoprotein cholesterol(LDL-C)were significantly down-regulated(P＜0.05,P＜0.01),while high-density lipopro-tein cholesterol(HDL-C)levels were up-regulated in the atherosclerotic rats.Moreover,serum levels of liver and kidney function markers such as aspartate aminotransferase(AST),alanine aminotransferase(ALT),blood urea nitrogen(BUN),and creatinine(Cr)exhibited down-regulation(P＜0.05,P＜0.01).Additionally,pro-inflammatory factors including interleukin-6(IL-6),interleukin-1 beta(IL-1β),tumor necrosis factor-alpha(TNF-α),high-sensitivity C-reactive protein(hs-CRP),and matrix metallopeptidase 9(MMP-9)were also reduced(P＜0.01),whereas the anti-inflammatory factor interleukin-10(IL-10)was found to be elevated(P＜0.01).Furthermore,after oral administration of Tiaozhi Xiaoban Mixture,expression levels of apoptosis-related factors NLRP3,ASC,Cleaved Caspase-1,Cleaved IL-1 β,Puma,Bax,Noxa,and MDM2 in thoracic aorta tissues from the atherosclerotic rats showed sig-nificant down-regulation(P＜0.05,P＜0.01).Notably,following treatment with Tiaozhi Xiaoban Mixture,mRNA levels of Linc-HC decreased while mRNA expression of MALAT1 increased(P＜0.05,P＜0.01).CONCLUSION Tiaozhi Xiaoban Mixture may inhibit the expression of Linc-HC and up-regulate the expression of MALAT1 to reduce the formation of atherosclerotic plaque,improve ab-normal blood lipids and liver and kidney function,alleviate inflammation and inhibit apoptosis.

OBJECTIVE To explore the ameliorative effect of Tiaozhi Xiaoban Mixture on atherosclerosis and the potential role of long non-coding RNA(Linc RNA)in anti-atherosclerosis.METHODS A model of atherosclerosis was established in SD rats subjec-ted to a high-fat diet.At 4 weeks post-modeling,thoracic aortic tissues from atherosclerotic rats were collected for hematoxylin-eosin(HE)staining to systematically evaluate the anti-atherosclerotic effects of Tiaozhi Xiaoban Mixture at different doses.Biochemical kits were utilized to assess relevant indices related to blood lipid levels as well as liver and kidney function,thereby evaluating the impact of Tiaozhi Xiaoban Mixture on these parameters.Enzyme-linked immunosorbent assay(ELISA)was employed to measure serum inflam-mation markers influenced by Tiaozhi Xiaoban Mixture.Additionally,TUNEL staining and Western blot analysis were conducted to ex-amine the apoptotic effects of Tiaozhi Xiaoban Mixture on thoracic aorta tissue.Finally,qPCR was used to detect the expression levels of Line-HC,MALAT1,etc.,in order to evaluate how Tiaozhi Xiaoban Mixture affecting these specific RNA molecules.RESULTS Following treatment with Tiaozhi Xiaoban Mixture,the blood lipid profiles indicated that total cholesterol(TC),triglycerides(TG),and low-density lipoprotein cholesterol(LDL-C)were significantly down-regulated(P＜0.05,P＜0.01),while high-density lipopro-tein cholesterol(HDL-C)levels were up-regulated in the atherosclerotic rats.Moreover,serum levels of liver and kidney function markers such as aspartate aminotransferase(AST),alanine aminotransferase(ALT),blood urea nitrogen(BUN),and creatinine(Cr)exhibited down-regulation(P＜0.05,P＜0.01).Additionally,pro-inflammatory factors including interleukin-6(IL-6),interleukin-1 beta(IL-1β),tumor necrosis factor-alpha(TNF-α),high-sensitivity C-reactive protein(hs-CRP),and matrix metallopeptidase 9(MMP-9)were also reduced(P＜0.01),whereas the anti-inflammatory factor interleukin-10(IL-10)was found to be elevated(P＜0.01).Furthermore,after oral administration of Tiaozhi Xiaoban Mixture,expression levels of apoptosis-related factors NLRP3,ASC,Cleaved Caspase-1,Cleaved IL-1 β,Puma,Bax,Noxa,and MDM2 in thoracic aorta tissues from the atherosclerotic rats showed sig-nificant down-regulation(P＜0.05,P＜0.01).Notably,following treatment with Tiaozhi Xiaoban Mixture,mRNA levels of Linc-HC decreased while mRNA expression of MALAT1 increased(P＜0.05,P＜0.01).CONCLUSION Tiaozhi Xiaoban Mixture may inhibit the expression of Linc-HC and up-regulate the expression of MALAT1 to reduce the formation of atherosclerotic plaque,improve ab-normal blood lipids and liver and kidney function,alleviate inflammation and inhibit apoptosis.

Objective To explore the association between plasma fibrinogen(FBG)levels and the risk of in-hospital mortality among patients with septic shock.Methods The clinical data of 563 patients diagnosed with septic shock in the Intensive Care Unit(ICU)of Shenzhen Second People's Hospital from August 1,2018,to December 31,2020,were collected.Patient demographic information,basic vital signs,and blood routine and biochemical indices upon admission were gathered.Moreover,the Acute Physiology and Chronic Health Evaluation Ⅱ(APACHEⅡ)scores were calculated.Binary logistic regression analysis was conducted to explore the correlation between plasma fibrinogen levels and in-hospital mortality in patients with septic shock.Additionally,a generalized additive model(GAM)and smoothed curve fitting were employed to investigate the nonlinear relationship between plasma fibrinogen and in-hospital mortality.Receiver operating characteristic(ROC)curves were constructed for FBG and APACHEⅡ scores to predict in-hospital mortality in septic shock patients.The area under the curve(AUC)was computed to compare the predictive efficacies of the two.Furthermore,a segmented linear regression model was utilized for quantification.Results Binary logistic regression analysis demonstrated a significant negative correlation between plasma fibrinogen levels and in-hospital mortality among patients with septic shock(P<0.05).GAM modeling and smoothed curve fitting disclosed a nonlinear association between plasma fibrinogen levels and in-hospital mortality,with an inflection point at 5.54 g/L.The segmented linear regression model indicated that,to the left of the inflection point(FBG≤5.54 g/L),for every 1 g/L decrease in plasma fibrinogen,the risk of death increased by 24.5%(OR=0.755,P=0.003).Conversely,to the right of the inflection point(FBG>5.54 g/L),the relationship was not statistically significant(OR=1.049,P=0.685).The findings of the subgroup analyses indicated that the characteristics of the subgroups did not alter the relationship between blood fibrinogen levels and in-hospital mortality.Conclusion There is a nonlinear relationship between FBG levels and in-hospital mortality in patients with septic shock,which has predictive value for evaluating the risk of in-hospital mortality in this patient cohort.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To study the in vitro expression of three phenylalanine hydroxylase(PAH)mutants(p.R243Q,p.R241C,and p.Y356X)and determine their pathogenicity.Methods Bioinformatics techniques were used to predict the impact of PAH mutants on the structure and function of PAH protein.Corresponding mutant plasmids of PAH were constructed and expressed in HEK293T cells.Quantitative reverse transcription polymerase chain reaction was used to measure the mRNA expression levels of the three PAH mutants,and their protein levels were assessed using Western blot and enzyme-linked immunosorbent assay.Results Bioinformatics analysis predicted that all three mutants were pathogenic.The mRNA expression levels of the p.R243Q and p.R241C mutants in HEK293T cells were similar to the mRNA expression level of the wild-type control(P>0.05),while the mRNA expression level of the p.Y356X mutant significantly decreased(P<0.05).The PAH protein expression levels of all three mutants were significantly reduced compared to the wild-type control(P<0.05).The extracellular concentration of PAH protein was reduced in the p.R241C and p.Y356X mutants compared to the wild-type control(P<0.05),while there was no significant difference between the p.R243Q mutant and the wild type control(P>0.05).Conclusions p.R243Q,p.R241C and p.Y356X mutants lead to reduced expression levels of PAH protein in eukaryotic cells,with p.R241C and p.Y356X mutants also affecting the function of PAH protein.These three PAH mutants are to be pathogenic.[Chinese Journal of Contemporary Pediatrics,2024,26(2):188-193]