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 safety and efficacy of novel bioabsorbable vascular scaffold(BVS)in the treatment of patients with complex coronary artery disease.Methods This was a retrospective,matched,single-center observational study.45 patients with coronary atherosclerotic cardiopathy received BVS treatment in the cardiovascular medicine department Department of the Affiliated Hospital of Guangdong Medical University from June 2020 to June 2021(BVS),and 45 patients treated with drug-eluting stents(DES)group were selected according to matching study requirements during the same period.Baseline,surgical,and follow-up data were compared between the two groups to evaluate safety and efficacy.The main measures of safety were:surgical time,intraoperative adverse events,etc.,and the end point of efficacy was target lesion failure(TLF),including cardiac death,target vessel myocardial infarction,and ischa-driven target lesion revascularization.Results A total of 90 patients were enrolled in this study,all of whom were followed up for at least 3 years.There were 20 cases of bifurcation lesions and 25 cases of diffuse long lesions in the two groups,and 50 cases of imaging were reviewed among the 90 patients.The proportion of stable coronary heart disease,history of diabetes,history of hypertension,history of smoking,pre-dilated balloon pressure and postoperative diastolic blood pressure in BVS group was higher than that in DES group,and the proportion of family history was lower than that in DES group(all P＜0.05).There were no statistically significant differences in the rates of cardiac death,target vessel myocardial infarction,and ischemia-driven revascularization of target lesions between the two groups(all P＞0.05).Binary Logistic regression model analysis showed that the diameter stenosis ratio of target lesions was an independent risk factor for intrastent restenosis(OR 2.786,95％CI 1.096-7.081,P=0.031).Conclusions Compared with traditional DES,BVS implantation has consistent safety and efficacy in the treatment of complex coronary artery disease within 3 years.The diameter stenosis ratio of target lesions was an independent risk factor for intrastent restenosis.

Objective:To determine the risk factors of reoperation and mortality after complete atrioventricular septal defect repair, and to evaluate the medium and long-term prognosis.Methods:From March 2008 to March 2022, a total of 266 children were selected from the Department of Thoracic and Cardiovascular Surgery, Nanjing Children's Hospital, who underwent the complete atrioventricular septal defect repair. Exclusion of children with conotrucal anomaly such as tetralogy of Fallot, transposition of the great arteries, and right ventricular double outlet. Demographic characteristics, surgical data, postoperative follow-up and associated risk factors were analyzed.Results:All the children were repaired with modified single-piece method for the first time, and 26 children were reoperated because of severe left atrioventricular valve regurgitation, left ventricular outflow tract obstruction and atrioventricular block. The 1-year, 3-year and 5-year overall survival rate and freedom from reoperation rate of all children were (98.1±0.8)%, (97.3±1.0)%, (96.2±1.2)%, (96.6±1.1)%, (93.9±1.5)% and (92.2±1.7)%, respectively. A total of 11 (42.3%) early reoperations and 15 (57.7%) late reoperations were performed, of which 1-year, 3-year and 5-year survival rates were (92.3±5.2)%, (82.1±8.3)% and (76.6±9.4)% respectively. Multifactorial analysis showed that age <3 months and left atrioventricular regurgitation >grade 2 at 24 hours postoperatively were independent risk factors for reoperation, whereas age <3 months and experience of reoperation were independent risk factors for death of children.Conclusion:Complete atrial septal defects have excellent surgical outcomes, but some children still require reoperation, and age <3 months and postoperative left atrioventricular valve regurgitation(LAVVR)>2 grades remain important predictors of their surgical prognosis.

Accurate occupation classification is essential in various fields, including policy development and epidemiological studies. This study aims to develop an occupation classification model based on DistilKoBERT.

Accurate occupation classification is essential in various fields, including policy development and epidemiological studies. This study aims to develop an occupation classification model based on DistilKoBERT.

AIM:To investigate the impact of aquaporin 4(AQP4)expression inhibition on autophagy and apoptosis in a mouse model of cerebral ischemia-reperfusion(I/R)injury,and to elucidate its underlying mechanism.METHODS:Cerebral I/R injury was induced in mice via transient middle cerebral artery occlusion(tMCAO).Totally 60 mice were randomly divided into sham group,I/R group,AQP4 inhibition group,and 3-methyladenine(3-MA)group,with 15 mice in each group.Among them,the mice in sham and I/R groups received intraperitoneal injections of normal saline,while those in AQP4 inhibition group and 3-MA group received intraperitoneal injections of AER-271(2 mg·kg-1·d-1)and AER-271+3-MA(2 mg·kg-1·d-1)for 3 d,respectively,once per day.Longa score was adopted to assess the neu-rological function,and to record changes in body weight.Cerebral infarction volume and histopathological alterations were evaluated using hematoxylin-eosin staining.Western blot analysis was performed to determine the levels of AQP4,LC3-Ⅱ,P62 and cleaved caspase-3,while the LC3-Ⅱ,P62,cleaved caspase-3 and NeuN(neuronal marker)colocalization and expression assessment were conducted with immunofluorescence.RESULTS:The mice in I/R and AQP4 inhibition groups exhibited extensive cerebral infarction,cerebral edema,and elevated Longa scores.However,in comparision to I/R group,the mice in AQP4 inhibition group showed significantly reduced cerebral infarct volume,cerebral edema vol-ume,and Longa score(P<0.05).Additionally,in contrast to sham group,the mice in I/R group displayed increased ex-pression of AQP4,LC3-Ⅱ and cleaved caspase-3(P<0.01),accompanied by decreased body weight and P62 expression(P<0.05 or P<0.01).Furthermore,compared with I/R group,the mice in both AQP4 inhibition group and 3-MA group demonstrated a decrease in the expression levels of AQP4,LC3-Ⅱ and cleaved caspase-3(P<0.05 or P<0.01),along with increased body weight and P62 expression(P<0.05 or P<0.01).Nonetheless,no significant differences were ob-served between AQP4 inhibition group and 3-MA group regarding Longa score,cerebral infarct volume,body weight,and the expression of AQP4,LC3-Ⅱ,cleaved caspase-3 and P62.CONCLUSION:Inhibition of AQP4 expression signifi-cantly reduces cerebral infarction area and nerve injury severity in tMCAO mice.Moreover,AQP4 expression inhibition decelerates autophagy and apoptosis after cerebral infarction,with the additional autophagy inhibitor showing no notable impact on the protective effect of AQP4 inhibition.

BACKGROUND:Knee osteoarthritis is a degenerative disease caused by multiple factors.Its pathogenesis is complex and still unclear.Chinese medicine in the treatment of knee osteoarthritis is fruitful,and in-depth study of Chinese medicine in the treatment of knee osteoarthritis is of great significance. OBJECTIVE:To review the progress of Chinese medicine monomers and compounds in the treatment of knee osteoarthritis and to provide ideas and reference for the effective prevention and treatment of knee osteoarthritis. METHODS:CNKI,WanFang,VIP,PubMed,MEDLINE,Nature,and Cochrane databases were retrieved for relevant literature published from database inception to 2022.The keywords were"knee osteoarthritis,cartilage damage,traditional Chinese medicine,Chinese herbal compound,treatment"in Chinese and English.Duplicates and obsolete non-referenced literature were excluded,and a total of 62 standard papers were included for further review. RESULTS AND CONCLUSION:Some of the pathogeneses of knee osteoarthritis include immune inflammatory response,chondrocyte autophagy and apoptosis,vascular endothelial growth factor level and biomechanical imbalance.The mechanisms by which traditional Chinese medicine treats knee osteoarthritis mainly focus on regulating inflammatory factor levels,chondrocyte autophagy and apoptosis,and vascular endothelial growth factor level and improving cartilage performance,so as to delay the occurrence and development of knee osteoarthritis.

BACKGROUND:The nuclear factor-κB signaling pathway plays an important role in the pathogenesis of osteoporosis.In recent years,increasing studies have shown that terpenoid herbal monomer compounds can inhibit the activity of bone resorbing cells and promote the differentiation of bone forming cells via the nuclear factor-κB signaling pathway,thus reducing bone resorption and increasing bone formation,which has certain preventive and therapeutic effects on osteoporosis. OBJECTIVE:By analyzing and summarizing the domestic and international literature,to investigate the relationship between nuclear factor-κB signaling pathway and osteoporosis in depth,elucidate the mechanism of terpenoid monomer compounds in regulating the nuclear factor-κB signaling pathway to prevent osteoporosis,and systematically summarize the terpenoid monomer compounds targeting to regulate the nuclear factor-κB signaling pathway to prevent osteoporosis. METHODS:According to the proposed inclusion and exclusion criteria,two researchers searched for relevant articles published from database inception to December 2022 in CNKI and PubMed using the search terms"NF-κB,osteoporosis,osteoblasts,osteoclasts,angiogenesis,traditional Chinese medicine,terpenoid"in Chinese and English,respectively.A third researcher summarized and organized the literature and 75 articles were finally included for a systematic review. RESULTS AND CONCLUSION:The nuclear factor-κB signaling pathway mediates the onset and progression of osteoporosis by regulating the differentiation and proliferation of osteoblasts and osteoclasts,as well as angiogenesis.Activation of the nuclear factor-κB signaling pathway negatively regulates the proliferation and differentiation of osteoblasts.Activation of the nuclear factor-κB signaling pathway enhances osteoclast activity and inhibits osteoblast growth,thereby inhibiting compensatory bone production to maintain bone homeostasis.However,over-activation of the nuclear factor-κB signaling pathway can lead to osteoporosis.The nuclear factor-κB signaling pathway is involved in the"angiogenesis-osteogenesis"coupling by upregulating the expression levels of cytokines such as angiopoietin-1,platelet-derived growth factor BB and vascular endothelial growth factor,which promote the growth of blood vessels in bone.The terpenoid herbal monomer compounds are used in the field of tissue engineering to promote the proliferation and differentiation of bone cells,thereby promoting the growth and repair of bone tissue.Terpenoid herbal monomer compounds can prevent and treat osteoporosis by inhibiting the degradation of nuclear factor-κB inhibitor,blocking nuclear factor-κB/p65 phosphorylation and nuclear translocation,thereby weakening the nuclear factor-κB signaling pathway,promoting osteoblast differentiation and inhibiting osteoclast formation.Currently,research on the regulation of nuclear factor-κB signaling pathway by monomeric compounds of terpenoids to prevent osteoporosis is mainly based on in vitro cellular experiments and animal models,and there is a lack of research on the complex physiological and pathological processes in humans.In the future,more clinical trials and studies are needed to further clarify the mechanism of action and efficacy of the nuclear factor-κB signaling pathway involved in the intervention of osteoporosis.

Transcatheter aortic valve replacement(TAVR)has become one of the effective methods for treating patients with aortic valve disease.With the continuous maturity of technology,innovation of instruments and increasing experience,the indications for TAVR has been expanded.Following international trends,the number of TAVR in China has steadily increased with each passing year.In 2023,the long-term follow-up results of TAVR in low-risk AS patients further confirm the long-term benefits of TAVR.The relevant research on TAVR for patients with aortic regurgitation and patients with bicuspid aortic stenosis provide evidence support for the expansion of TAVR indications.At the same time,the development of valve devices and new technological innovations are emerging in an endless stream,and the new concept of full life cycle management is increasingly being valued.Especially in China,the development of local devices is progressing rapidly,and multiple devices have entered the clinical research stage.The clinical manifestations and research results are worth pursuing.

Objective To explore whether the cognitive function of central obese mice is decreased by affecting the expression of brain-derived neurotrophic factor(BDNF)in hippocampus.Methods Healthy mice at the neonatal stage were divided into normal group and model group at random.To obtain the obese models,model group mice were injected at cervical subcutaneous with 10％L-monosodium glutamate(MSG;3 mg·g-1·d-1)for 5 days.The normal group was injected with the same dose of 0.9％NaCl.In addition,mice were removed according to the requirements.Finally,we got 8 mice in each group.The following parameters were compared:body weight,Lee's index and levels of the serum lipid.The BDNF expression levels in hippocampal tissue were measured using western blotting.Results At the 8th weekend,the body weight of the model and normal groups was(49.01±2.47)and(41.27±3.28)g;the Lee's indexes were(357.14±9.24)and(330.15±7.37)g1/3·cm-1;triglyceride levels were(1.37±0.52)and(0.73±0.31)mmol·L-1;total cholesterol levels were(2.98±0.18)and(1.98±0.30)mmol·L-1;low-density lipoprotein levels were(0.31±0.03)and(0.24±0.02)mmol·L-1;high-density lipoprotein levels were(2.70±0.15)and(1.98±0.40)mmol·L-1;the differences were statistically significant(P＜0.05,P＜0.01),which were consistent with the characteristics of the central obesity model.The BDNF protein expression levels in the hippocampus of the model and normal groups were 6.02 x 104±626.53 and 7.04 x 104±1 440.81,which has statistically significant(P＜0.01).Conclusion The cognitive function of central obese mice may be decreased by down-regulating the expression of BDNF in hippocampus.