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.

Overexpression of P-glycoprotein(P-gp)is one of the major causes of therapeutic resistance to a variety of drugs,in-cluding antitumor drugs.P-gp has a wide range of substrates that are capable of expelling drugs from the cell via a twist-squeeze mechanism,leading to drug resistance.To address the problem of P-gp-mediated multidrug resistance,several inhibitors are being investigated.This article reviews the current small mole-cule compounds,natural source compounds and pharmaceutical excipients capable of inhibiting P-gp,and summarizes the cur-rent mechanisms of action of P-gp inhibitors,which are mainly competitive or non-competitive inhibition,stimulation of ATPase activity,down-regulation of expression,and metamorphic modu-lation.Currently,it is mainly the drug interactions and toxic re-actions that limit their clinical applications.

Objective To observe the clinical effect of femoral neck system(FNS)in the treatment of young and middle-aged adults with femoral neck fractures.Methods A total of 44 young and middle-aged patients with femoral neck fractures who received treatment in our hospital were selected,and divided into the control group(n=22)and the observation group(n=22)according to treatment method.The patients in the control group were fixed with traditional three cannulated compression screws(CCS).The patients in the observation group were fixed with FNS.Perioperative indexes,postoperative visual analogue scale(VAS)score,fracture healing time,postoperative Harris hip score and incidence of complications of patients were recorded and compared between the two groups.Results No postoperative complications occurred in both groups.There was no statistically significant difference in intraoperative blood loss of patients between the two groups(P>0.05).Compared with the control group,the observation group showed a significant reduction in surgical time,intraoperative fluoroscopy frequency,and partial weight bearing time(P<0.05).There was no statistically significant difference in VAS score after surgery of patients between the two groups(P>0.05).Compared with the control group,the fracture healing time of patients in the observation group was significantly shorter(P<0.05),the Harris hip scores 6 and 9 months after surgery of patients were significantly higher(P<0.05).Conclusion The treatment of FNS for young and middle-aged adults with femoral neck fractures has a definitely curative effect,with simple operation,minimal trauma,fast recovery,fewer complications,and high biomechanical performance.

Objective To explore the magnetic resonance imaging(MRI)manifestations of acute cerebral infarction(ACI)and the correlation between lipoprotein-associated phospholipase A2(Lp-PLA2),cystatin C(Cys C)and short-term prognosis.Methods A total of 110 ACI patients admitted to the department of neurology in our hospital from January 1,2022 to January 1,2023 were selected as the study objects.The clinical data and multimodal MRI were collected,and the serum Lp-PLA2 and Cys C levels of patients were detected.The patients were divided into the good prognosis group and the poor prognosis group according to the modified Rankin scale(mRS)score 90 days after onset.The predictive value of MRI manifestations and Lp-PLA2 and Cys C levels for short-term poor prognosis was analyzed.Results There were statistically significant differences in the time from onset to admission,National Institute of Health Stroke Scale(NIHSS)score on admission,hypertension or diabetes,coronary heart disease or atrial fibrillation of patients between the good prognosis group and the poor prognosis group(P<0.05).The proportions of patients with ischemic penumbra,HV positive,cortical-subcortical infarction,large perforating branch infarction,small perforating branch infarction,bilateral anterior circulation infarction,posterior circulation infarction,anterior-posterior circulation infarction,middle cerebral artery(MCA)stenosis or occlusion,both internal carotid artery(ICA)and MCA stenosis or occlusion,posterior cerebral artery(PCA)or vertebral artery(VA)stenosis or occlusion and hemorrhage transformation in the poor prognosis group were significantly higher than those in the good prognosis group(P<0.05).The Lp-PLA2 and Cys C levels of patients in the poor prognosis group were significantly higher than those in the good prognosis group(P<0.05).Small penetrating branch infarction,posterior circulation infarction,anterior-posterior circulation infarction,MCA stenosis or occlusion,both ICA and MCA stenosis or occlusion,hemorrhage transformation,serum Lp-PLA2 and Cys C had certain predictive value for patients with short-term poor prognosis(P<0.05).Conclusion MRI manifestations(ischemic penumbra,HV positivity,different types of cerebral infarction,and vascular stenosis)and serum Lp-PLA2 and Cys C levels can predict the short-term prognosis of ACI patients and provide important reference for the formulation of clinical treatment plans.

Despite significant advancements in treatments for heart failure,the overall prognosis for patients remains poor.Hemodynamic abnormalities in heart failure manifest as elevated left atrial pressure and pulmonary congestion.Previous studies have shown that reducing left atrial pressure can improve symptoms and prognosis for heart failure patients,suggesting that left-sided heart overload may be a potential target for heart failure treatment.Atrial shunting procedures aim to create a stable and controlled left-to-right intracardiac shunt,restoring the decompensated left heart volume and pressure load in heart failure patients to a compensatory state,thereby improving heart failure symptoms and prognosis.Currently,this treatment is still in the clinical research stage globally.Existing data indicate that atrial shunting procedures can lower left atrial pressure at rest or during exercise in heart failure patients,improve pulmonary congestion,enhance patients'exercise tolerance,and clinical cardiac function.However,no studies have yet confirmed that it can improve clinical endpoints such as rehospitalization and mortality due to heart failure.Future research will focus on identifying heart failure patients who may benefit from atrial shunting,with assessments of heart failure etiology,right heart function,and reversibility of pulmonary vascular resistance,as well as heart failure classification based on ejection fraction,serving as potential key factors for patient selection.

Objective To monitor the antifungal resistance of clinical isolates of Candida spp.in the East China region.Methods MALDI-TOF MS or molecular methods were used to re-identify the strains collected from January 2018 to December 2022.Antifungal susceptibility testing was performed using the broth microdilution method.The susceptibility test results were interpreted according to the breakpoints of 2022 Clinical and Laboratory Standards Institute(CLSI)documents M27 M44s-Ed3 and M57s-Ed4.Results A total of 3 026 strains of Candida were collected,65.33％of which were isolated from sterile body sites,mainly from blood(38.86％)and pleural effusion/ascites(10.21％).The predominant species of Candida were Candida albicans(44.51％),followed by Candida parapsilosis complex(19.46％),Candida tropicalis(13.98％),Candida glabrata(10.34％),and other Candida species(0.79％).Candida albicans showed overall high susceptibility rates to the 10 antifungal drugs tested(the lowest rate being 93.62％).Only 2.97％of the strains showed dose-dependent susceptibility(SDD)to fluconazole.Candida parapsilosis complex had a SDD rate of 2.61％and a resistance rate of 9.42％to fluconazole,and susceptibility rates above 90％to other drugs.Candida glabrata had a SDD rate of 92.01％and a resistance rate of 7.99％to fluconazole,resistance rates of 32.27％and 48.24％to posaconazole and voriconazole non-wild-type strains(NWT),respectively,and susceptibility rates above 90％to other drugs.Candida tropicalis had resistance rates of 29.55％and 26.24％to fluconazole and voriconazole,respectively,resistance rates of 76.60％and 21.99％to posaconazole and echinocandins non-wild-type strains(NWT),and a resistance rate of 2.36％to echinocandins.Conclusions The prevalence and species distribution of Candida spp.in the East China region are consistent with previous domestic and international reports.Candida glabrata exhibits certain degree of resistance to fluconazole,while Candida tropicalis demonstrates higher resistance to triazole drugs.Additionally,echinocandins resistance has emerged in Candida albicans,Candida glabrata,Candida tropicalis,and Candida parapsilosis.

Objective To explore the mechanism of intervention of phosphatidylinositol 3-kinase/nerve growth factor/vanilloid receptor 1(NGF/PI3K/TRPV 1)signaling pathway.Methods Forty 10 SPF SD male rats were selected,including 10 in blank group,13 in model group,7 in study 1 and 9 in study 2.The control group and model group will only receive saline ingavage without any other treatment.Study group 1 received 20 mg/kg aqueous solution for gavage,and study 2 group gave 4 g/kg for gavage.The Bristol score,the spleen coefficient and thymus coefficient were analyzed,and the expression levels of IgA,IgG,IgM,IL-1 β,IL-6,TNF-α and NGF/PI3K/TRPV 1 protein expression were measured.Results Compared with the blank group,Bristol score,IgA,IgG,IgM,IL-1 β,IL-6,TNF-α were increased(P＜0.05),Bristol score,spleen coefficient,thymus coefficient,IgA,IgG,IgM,IL-1 β,IL-6,TNF-α levels and NGF,PI3K,and TRPV 1 were decreased(P＜0.05).Conclusion Shenling powder inhibited NGF/PI3K/TRPV 1 pathway,improved gastrointestinal function and stool state,reduced inflammation,and improved the homeostasis of immune function,with remarkable intervention effect.

Objective:To retrospectively analyze the treatment status of tyrosine kinase inhibitors (TKI) in newly diagnosed patients with chronic myeloid leukemia (CML) in China.Methods:Data of chronic phase (CP) and accelerated phase (AP) CML patients diagnosed from January 2006 to December 2022 from 77 centers, ≥18 years old, and receiving initial imatinib, nilotinib, dasatinib or flumatinib-therapy within 6 months after diagnosis in China with complete data were retrospectively interrogated. The choice of initial TKI, current TKI medications, treatment switch and reasons, treatment responses and outcomes as well as the variables associated with them were analyzed.Results:6 893 patients in CP ( n=6 453, 93.6%) or AP ( n=440, 6.4%) receiving initial imatinib ( n=4 906, 71.2%), nilotinib ( n=1 157, 16.8%), dasatinib ( n=298, 4.3%) or flumatinib ( n=532, 7.2%) -therapy. With the median follow-up of 43 ( IQR 22-75) months, 1 581 (22.9%) patients switched TKI due to resistance ( n=1 055, 15.3%), intolerance ( n=248, 3.6%), pursuit of better efficacy ( n=168, 2.4%), economic or other reasons ( n=110, 1.6%). The frequency of switching TKI in AP patients was significantly-higher than that in CP patients (44.1% vs 21.5%, P<0.001), and more AP patients switched TKI due to resistance than CP patients (75.3% vs 66.1%, P=0.011). Multi-variable analyses showed that male, lower HGB concentration and ELTS intermediate/high-risk cohort were associated with lower cytogenetic and molecular responses rate and poor outcomes in CP patients; higher WBC count and initial the second-generation TKI treatment, the higher response rates; Ph + ACA at diagnosis, poor PFS. However, Sokal intermediate/high-risk cohort was only significantly-associated with lower CCyR and MMR rates and the poor PFS. Lower HGB concentration and larger spleen size were significantly-associated with the lower cytogenetic and molecular response rates in AP patients; initial the second-generation TKI treatment, the higher treatment response rates; lower PLT count, higher blasts and Ph + ACA, poorer TFS; Ph + ACA, poorer OS. Conclusion:At present, the vast majority of newly-diagnosed CML-CP or AP patients could benefit from TKI treatment in the long term with the good treatment responses and survival outcomes.

Objective To investigate the risk factors for bronchopulmonary dysplasia(BPD)in twin preterm infants with a gestational age of<34 weeks,and to provide a basis for early identification of BPD in twin preterm infants in clinical practice.Methods A retrospective analysis was performed for the twin preterm infants with a gestational age of<34 weeks who were admitted to 22 hospitals nationwide from January 2018 to December 2020.According to their conditions,they were divided into group A(both twins had BPD),group B(only one twin had BPD),and group C(neither twin had BPD).The risk factors for BPD in twin preterm infants were analyzed.Further analysis was conducted on group B to investigate the postnatal risk factors for BPD within twins.Results A total of 904 pairs of twins with a gestational age of<34 weeks were included in this study.The multivariate logistic regression analysis showed that compared with group C,birth weight discordance of>25%between the twins was an independent risk factor for BPD in one of the twins(OR=3.370,95%CI:1.500-7.568,P<0.05),and high gestational age at birth was a protective factor against BPD(P<0.05).The conditional logistic regression analysis of group B showed that small-for-gestational-age(SGA)birth was an independent risk factor for BPD in individual twins(OR=5.017,95%CI:1.040-24.190,P<0.05).Conclusions The development of BPD in twin preterm infants is associated with gestational age,birth weight discordance between the twins,and SGA birth.

DNA origami is a powerful technique for generating nanostructures with dynamic properties and intelligent controllability. The precise geometric shapes, high programmability, and excellent biocompatibility make DNA origami nanostructures an emerging drug delivery vehicle. The shape, size of the carrier material, as well as the loading and release of drugs are important factors affecting the bioavailability of drugs. This paper focuses on the controllable design of DNA origami nanostructures, efficient drug loading, and intelligent drug release. It summarizes the cutting-edge applications of DNA origami technology in biomedicine, and discusses areas where researchers can contribute to further advancing the clinical application of DNA origami carriers.