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 clarify the risk factors of diaphragmatic dysfunction (DD) after cardiac surgery with extracorporeal circulation. Methods A retrospective analysis was conducted on the data of patients who underwent cardiac surgery with extracorporeal circulation in the Department of Cardiovascular Surgery of Peking University People's Hospital from January 2023 to March 2024. Patients were divided into two groups according to the results of bedside diaphragm ultrasound: a DD group and a control group. The preoperative, intraoperative, and postoperative indicators of the patients were compared and analyzed, and independent risk factors for DD were screened using multivariate logistic regression analysis. Results A total of 281 patients were included, with 32 patients in the DD group, including 23 males and 9 females, with an average age of (64.0±13.5) years. There were 249 patients in the control group, including 189 males and 60 females, with an average age of (58.0±11.2) years. The body mass index of the DD group was lower than that of the control group [(18.4±1.5) kg/m2 vs. (21.9±1.8) kg/m2, P=0.004], and the prevalence of hypertension, chronic obstructive pulmonary disease, heart failure, and renal insufficiency was higher in the DD group (P<0.05). There was no statistical difference in intraoperative indicators (operation method, extracorporeal circulation time, aortic clamping time, and intraoperative nasopharyngeal temperature) between the two groups (P>0.05). In terms of postoperative aspects, the peak postoperative blood glucose in the DD group was significantly higher than that in the control group (P=0.001), and the proportion of patients requiring continuous renal replacement therapy was significantly higher than that in the control group (P=0.001). The postoperative reintubation rate, tracheotomy rate, mechanical ventilation time, and intensive care unit stay time in the DD group were higher or longer than those in the control group (P<0.05). Multivariate logistic regression analysis showed that low body mass index [OR=0.72, 95%CI (0.41, 0.88), P=0.011], preoperative dialysis [OR=2.51, 95%CI (1.89, 4.14), P=0.027], low left ventricular ejection fraction [OR=0.88, 95%CI (0.71, 0.93), P=0.046], and postoperative hyperglycemia [OR=3.27, 95%CI (2.58, 5.32), P=0.009] were independent risk factors for DD. Conclusion The incidence of DD is relatively high after cardiac surgery, and low body mass index, preoperative renal insufficiency requiring dialysis, low left ventricular ejection fraction, and postoperative hyperglycemia are risk factors for DD.

Objective To study the spatial correlation characteristics of the number of large medical equipment alloca-tion in China's provinces and cities,with a view to providing a reference basis for the optimization of the allocation of large medical equipment.Methods It analyzed the spatial autocorrelation of China's large medical equipment alloca-tion and its influencing factors by using the Moran's I,grey correlation and other methods.Results The results of the spatial autocorrelation analysis showed that the allocation of large medical equipment in China was positively corre-lated spatially,and the spatial agglomeration was significant(Global Moran's I index value was 0.392,P＜0.05).The grey correlation of GDP,year-end resident population,geographic area,number of tertiary hospitals,number of beds in medical institutions,number of practicing(assistant)physicians,and annual discharges in each province and city were 0.913,0.919,0.745,0.883,0.907,0.929,0.880,respectively.Conclusion China's large-scale medi-cal equipment configuration of spatial autocorrelation properties,distributed in the eastern Beijing-Tianjin-Hebei,Yangtze River Delta region and some provinces and cities in the west of the large-scale medical equipment configura-tion level in the formation of high-value agglomeration and low-value agglomeration area respectively.At the same time,the equipment configuration has the characteristics of high-quality medical resources concentration,oriented to the needs of the masses,taking into account economic and social development,etc.It is recommended to fur-ther optimise the spatial structure of equipment allocation,incorporate the configuration of large-scale medical equip-ment into the consideration of regional health resource planning at all levels,and enhance the linkage of the equip-ment configuration planning between provinces and cities.

Alzheimer's disease(AD)is the most common cause of cognitive impairment in the elderly,and the formation of intracellular neurofibrillary tangles(NFT)due to the hyperphos-phorylation of Tau is one of its important pathological features.Compared to β-amyloid,the hyperphosphorylation of Tau and the resulting NFT are more closely related to the decline in cognitive ability.This review focuses on anti-AD drugs targeting Tau,em-phasizing the latest progress in inhibiting the hyperphosphoryla-tion of Tau protein,alleviating the aggregation of Tau protein,re-ducing the cytoskeletal damage caused by the hyperphosphoryla-tion of Tau protein by stabilizing microtubules,and immunothera-py,in the hope of providing new insights into drug research for AD and related cognitive disorders associated with Tau protein.

Objective·To analyze the clinicopathologic characteristics,gene mutation profile,and prognostic factors of patients with adrenal diffuse large B-cell lymphoma(DLBCL).Methods·From March 2002 to December 2022,a total of 105 patients with adrenal DLBCL admitted to Ruijin Hospital,Shanghai Jiao Tong University School of Medicine were retrospectively analyzed for their clinicopathological data,survival outcomes,and prognostic factors.Patients'gene mutation profiles were evaluated by targeted sequencing of 152 lymphoma-related genes.Results·The median age of the patients was 62(15?82)years and the male-to-female ratio was 2.3∶1.Among them,63 patients(60.0%)were over 60 years old,22 patients(21.0%)had an Eastern Cooperative Oncology Group(ECOG)performance status of two or higher,87 patients(82.9%)were staged Ann Arbor Ⅲ?Ⅳ,92 patients(87.6%)had elevated serum lactate dehydrogenase(LDH)levels(above the upper limit of reference),84 patients(80.0%)had extranodal invasion in at least two organs,67 patients(63.8%)were of non-germinal center B-cell(non-GCB)origin,and 95 patients(90.5%)had an international prognosis index(IPI)scored over 2.With a median follow-up of 28.3(0.7?191.9)months,the estimated 2-year overall survival(OS)rate and progression-free survival(PFS)rate were 68.3%and 53.1%,respectively.The estimated 5-year OS rate and PFS rate were 52.6%and 44.0%,respectively.Among 93 patients who could be evaluated for clinical outcomes,62(66.7%)got a complete response(CR).Univariate analysis and multivariate Cox analysis revealed that age over 60 years was an adverse prognostic factor for PFS,and ECOG performance status of two or higher was an adverse prognostic factor for both OS and PFS.Targeted gene sequencing in 46 adrenal diffuse DLBCL patients showed high mutation frequencies in lysine methyltransferase 2D(KMT2D;n=17,37%),Pim-1 proto-oncogene,serine/threonine kinase(PIM1;n=17,37%),MYD88 innate immune signal transduction adaptor(MYD88;n=15,33%),CD79b molecule(CD79B;n=13,28%),and BTG anti-proliferation factor 2(BTG2;n=10,22%).Conclusion·Age over 60 years is an adverse prognostic factor for PFS,and ECOG performance status of two or higher is an adverse prognostic factor for both OS and PFS in patients with adrenal DLBCL.Patients exhibited high frequencies of KMT2D,PIM1,MYD88,CD79B,and BTG2 mutations,as well as an increased proportion of the MCD-like subtype.

Objective:To explore the latent categories of barriers to PhaseⅡ cardiac rehabilitation in patients after coronary artery bypass grafting (CABG), and to analyze the influencing factors of different latent classes.Methods:A total of 340 CABG patients in PhaseⅡ cardiac rehabilitation were recruited by convenience sampling from two Class Ⅲ Grade A hospitals in Shanghai between January and August 2024. Data were collected using a general information questionnaire, the Cardiac Rehabilitation Barriers Scale (CRBS), and the Fear of Exercise Scale for Cardiac Patients. Latent profile analysis was used to classify the cardiac rehabilitation barriers, and multinomial Logistic regression was conducted to identify influencing factors for different latent classes.Results:Of the 340 questionnaires distributed, 319 valid responses were obtained after excluding incomplete or patterned questionnaires, with a valid response rate of 93.82% (319/340). The cardiac rehabilitation barriers among the 319 CABG patients were classified into three latent profiles: low-barrier, active rehabilitation type; moderate-barrier, poor-functioning type; and moderate-barrier, insufficient-perception type. Multinomial logistic regression analysis indicated that smoking, comorbidities, age, educational level, and fear of exercise were statistically significant influencing factors for different barrier profiles ( P<0.05) . Conclusions:Cardiac rehabilitation barriers in CABG patients exhibit heterogeneity. Medical staff should adopt targeted intervention strategies based on the specific barrier profiles, reduce patients' fear of exercise, and thereby improve rehabilitation outcomes.

AIM:This study aims to investigate the sensitizing effects of lycorine(Lyc)in combination with cisplatin(Cis)on human osteosarcoma cells and to explore the underlying mechanisms of action.METHODS:Human osteosarcoma cell lines MG63,HOS,and cisplatin-resistant HOS/DDP cells were utilized to evaluate the effects of Lyc and cisplatin,both alone and in combination,on cell viability using the CCK8 assay.The clonogenic assay was performed to assess cell proliferation capacity,while the scratch assay evaluated the drugs' effects on cell migration.Reactive oxygen species(ROS)levels were measured using a ROS assay kit,and changes in intracellular glutathione(GSH)levels were assessed with a GSH/oxidized glutathione(GSSG)assay kit.The mitochondrial membrane potential was analyzed via JC-1 staining to determine the drugs' effects on mitochondrial function.Intracellular iron(Ⅱ)content changes were detected us-ing FerrOrange,a fluorescence probe,and cellular malondialdehyde(MDA)levels were measured using an MDA assay kit.RT-qPCR was employed to evaluate the expression levels of key genes related to ferroptosis,and Western blot analysis was conducted to detect changes in the protein expression levels of Yes-associated protein 1(YAP1),acyl-CoA synthetase long-chain family member 4(ACSL4),glutathione peroxidase 4(GPX4),heme oxygenase-1(HO-1),and transferrin re-ceptor(TFRC).RESULTS:Both Lyc and cisplatin effectively inhibited the proliferation of human osteosarcoma cells.Notably,the combination of Lyc and cisplatin led to a more substantial reduction in cell viability,proliferation,and migra-tion abilities in MG63,HOS,and HOS/DDP cells compared to cisplatin alone.Additionally,this combination significant-ly increased ROS levels while decreasing GSH content,indicating mitochondrial damage and elevated iron(Ⅱ)and MDA levels.RT-qPCR results revealed that the combination treatment more significantly downregulated ferroptosis-promoting genes and upregulated ferroptosis-inhibiting genes compared to cisplatin treatment alone(P<0.05).Western blot results showed a slight decrease in GPX4 protein expression following Lyc and cisplatin treatment,while expression levels of YAP1,TFRC,ACSL4,and HO-1 were significantly increased(P<0.05).CONCLUSION:Lyc enhances the sensitivi-ty of MG63,HOS,and HOS/DDP cells to cisplatin by promoting ferroptosis through the YAP1/TFRC signaling pathway.

Objective:To analyze the association between remnant cholesterol (RC) and the risk of atherosclerotic cardiovascular disease (ASCVD) in community population in Shanghai.Methods:Using baseline and follow-up data from the Shanghai Suburban Adult Cohort and Biobank, individuals with ASCVD (including coronary heart disease, stroke, myocardial infarction, and peripheral artery disease) at baseline were excluded. A Cox proportional hazards regression model was employed to analyze the relationship between RC and ASCVD risk and the association under different LDL-C levels.Results:A total of 57 281 participants were included, with a median follow-up of 5.61 person-years. During the follow-up, 1 436 ASCVD events (2.51%) were recorded. After adjusting for potential confounders, individuals with moderate ( HR=1.18, 95% CI: 1.03-1.36) or high RC levels ( HR=1.32, 95% CI: 1.15-1.51) had an increased risk of ASCVD. The association was stronger in participants younger than 60 years-old (interaction P=0.048). Participants with RC ≥0.97 mmol/L and LDL-C <3.40 mmol/L demonstrated a 19% ( HR=1.19, 95% CI: 1.06-1.35) increased risk of ASCVD. When RC ≥0.97 mmol/L and LDL-C ≥3.40 mmol/L, ASCVD risk increased by 42% ( HR=1.42, 95% CI: 1.21-1.67). Conclusions:Elevated RC increases ASCVD risk, regardless of LDL-C levels. RC can serve as a valuable predictor and intervention target for ASCVD.

Objective To study the spatial correlation characteristics of the number of large medical equipment alloca-tion in China's provinces and cities,with a view to providing a reference basis for the optimization of the allocation of large medical equipment.Methods It analyzed the spatial autocorrelation of China's large medical equipment alloca-tion and its influencing factors by using the Moran's I,grey correlation and other methods.Results The results of the spatial autocorrelation analysis showed that the allocation of large medical equipment in China was positively corre-lated spatially,and the spatial agglomeration was significant(Global Moran's I index value was 0.392,P＜0.05).The grey correlation of GDP,year-end resident population,geographic area,number of tertiary hospitals,number of beds in medical institutions,number of practicing(assistant)physicians,and annual discharges in each province and city were 0.913,0.919,0.745,0.883,0.907,0.929,0.880,respectively.Conclusion China's large-scale medi-cal equipment configuration of spatial autocorrelation properties,distributed in the eastern Beijing-Tianjin-Hebei,Yangtze River Delta region and some provinces and cities in the west of the large-scale medical equipment configura-tion level in the formation of high-value agglomeration and low-value agglomeration area respectively.At the same time,the equipment configuration has the characteristics of high-quality medical resources concentration,oriented to the needs of the masses,taking into account economic and social development,etc.It is recommended to fur-ther optimise the spatial structure of equipment allocation,incorporate the configuration of large-scale medical equip-ment into the consideration of regional health resource planning at all levels,and enhance the linkage of the equip-ment configuration planning between provinces and cities.

Objective:To evaluate the cost-effectiveness and impact on mortality of health management services for the elderly aged 65 years and older in national essential public health service project.Methods:Based on the data of county-level medical institutions in Henan Province from 2019 to 2024,the Random Forest Method was used to construct a counterfactual framework to predict the hospitalization expenses under the unmanaged scenario,and then the cost-benefit ratio(BCR)and net income were calculated.Time-dependent Cox proportional hazards model was used to evaluate the effect of health management on all-cause mortality and cardiovascular and cerebrovascular disease mortality in the elderly.Results:A total of 962 955 elderly patients were included,451 119(46.85%)were included in the management group.The average hospitalization cost of the management group was significantly lower than that of the non-management group(P<0.05).Except for 2020-2021,BCRS in 2019 and 2022-2024 were 6.34,2.05,4.45 and 6.60,respectively.The risk of all-cause death was reduced by 76.96%,and the risk of cardiovascular and cerebrovascular death was reduced by 75.57%in the elderly patients included in the management group compared with those not included in the management group.Suggestions:It is necessary to establish a health outcomes-based evaluation system and promote the transformation and upgrading of the service model from single chronic disease management to"integrated health services with multi-disease management".