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.

The effect of porcine SIRT5 on replication of foot and mouth disease virus type O(FMDV-O)and the underlying regulatory mechanism were investigated.Western blot and RT-qPCR analyses were employed to monitor expression of endoge-nous SIRT5 in PK-15 cells infected with FMDV-O.Three pairs of SIRT5-specific siRNAs were synthesized.Changes to SIRT5 and FMDV-O protein and transcript levels,in addition to virus copy numbers,were measured by western blot and RT-qPCR analyses.PK-15 cells were transfected with a eukaryotic SIRT5 expression plasmid.Western blot and RT-qPCR analyses were used to explore the impact of SIRT5 overexpression on FMDV-O replication.Meanwhile,RT-qPCR analysis was used to detect the effect of SIRT5 overexpression on the mRNA expression levels of type I interferon-stimulated genes induced by SeV and FMDV-O.The results showed that expression of SIRT5 was up-regulated in PK-15 cells infected with FMDV-O and siRNA interfered with SIRT5 to inhibit FMDV-O replication.SIRT5 overexpression promoted FMDV-O replication.SIRT5 over-expression decreased mRNA expression levels of interferon-stimulated genes induced by SeV and FMDV-O.These results suggest that FMDV-O infection stimulated expression of SIRT5 in PK-15 cells,while SIRT5 promoted FMDV-O rep-lication by inhibiting production of type I interferon-stimula-ted genes.These findings provide a reference to further ex-plore the mechanism underlying the ability of porcine SIRT5 to promote FMDV-O replication.

Objective To construct a continuous nursing quality evaluation indicator system for inflam-matory bowel disease patients and provide a basis for the evaluation of continuous nursing quality.Methods On the basis of Donabedian's three-dimensional(structure,process,and outcome)quality structure,we employed liter-ature review,qualitative interview,Delphi method,and hierarchical analysis to determine the content and weights of indicators of continuous nursing quality for the patients with inflammatory bowel disease.Results A total of 15 experts completed 2 rounds of consultation,which had the questionnaire recovery rates of 100％,the expert authority coefficients of 0.930 and 0.919,and the Kendall harmony coefficients of 0.149 and 0.177(both P＜0.001),respectively.The established nursing quality evaluation indicator system included 3 first-level indicators,10 sec-ond-level indicators,and 39 third-level indicators.Conclusion The continuous nursing quality evaluation indi-cator system for the patients with inflammatory bowel disease that was constructed in this study was reasonable,reliable,and practical,providing reference for evaluating the continuous nursing quality for the patients with in-flammatory bowel disease.

Obｊective To investigate the protective mechanism of tricholoma matsutake polysaccharides(TMP) against 1-methy-4-pehnyl-pyridine ion (MPP

Objective To investigate the attributable risk(AR)of Acinetobacter baumannii(AB)infection in criti-cally ill patients.Methods A multicenter retrospective cohort study was conducted among adult patients in inten-sive care unit(ICU).Patients with AB isolated from sterile body fluid and confirmed with AB infection in each cen-ter were selected as the infected group.According to the matching criteria that patients should be from the same pe-riod,in the same ICU,as well as with similar APACHE Ⅱ score(±5 points)and primary diagnosis,patients who did not infect with AB were selected as the non-infected group in a 1:2 ratio.The AR was calculated.Results The in-hospital mortality of patients with AB infection in sterile body fluid was 33.3％,and that of non-infected group was 23.1％,with no statistically significant difference between the two groups(P=0.069).The AR was 10.2％(95％CI:-2.3％-22.8％).There is no statistically significant difference in mortality between non-infected pa-tients and infected patients from whose blood,cerebrospinal fluid and other specimen sources AB were isolated(P＞0.05).After infected with AB,critically ill patients with the major diagnosis of pulmonary infection had the high-est AR.There was no statistically significant difference in mortality between patients in the infected and non-infec-ted groups(P＞0.05),or between other diagnostic classifications.Conclusion The prognosis of AB infection in critically ill patients is highly overestimated,but active healthcare-associated infection control for AB in the ICU should still be carried out.

Objective:To assess the prevalence of dentinal hypersensitivity (DH) and related factors in urban adults in China.Methods:The study was designed as an observational, cross-sectional epidemiological study carried out in adults aged 18-69 years old in seven cities (Beijing, Shanghai, Wuhan, Chengdu, Xi′an, Guangzhou, and Harbin) of China. The study was conducted from March 2021 to May 2023. Patients were required to complete a questionnaire regarding the subjects′ socio-economic factors, dietary behavior, oral health behavior and personal antecedent factors. DH was clinically diagnosed by judging whether the tooth cold air stimulation provoked DH or not, and recorded by investigator pain rating Schiff score. Compare the findings of six cities (Harbin excluded) with a similar study conducted in 2008.Results:In total, 11 622 subjects from seven cities in China participated the study. Fifty two point two percent (6 072/11 622) of subjects reported DH in questionnaire, 36.7% (4 266/11 622) of subjects reported experiencing DH in response to cold air stimulation for at least one study tooth. Risk factors including age, sex, city, toothbrush method and acid reflux showed marked associations with DH ( P<0.05). The prevalence of DH of urban residents in six cities (Harbin excluded) was 33.7% (3 335/9 882), higher than that in 2008 [29.7%(2 354/7 939)]. Conclusions:Overall, DH was common among urban adults in China and the prevalence increased in recent years. Better understanding of DH and its associated factors should be considered in its prevention and management by dental professionals.

Objective This study aimed to comprehensively analyze and compare the clinicopathological features and prognosis of Chinese patients with human epidermal growth factor receptor 2(HER2)-low early breast cancer(BC)and HER2-IHC0 BC. Methods Patients diagnosed with HER2-negative BC(N=999)at our institution between January 2011 and December 2015 formed our study population.Clinicopathological characteristics,association between estrogen receptor(ER)expression and HER2-low,and evolution of HER2 immunohistochemical(IHC)score were assessed.Kaplan-Meier method and log-rank test were used to compare the long-term survival outcomes(5-year follow-up)between the HER2-IHC0 and HER2-low groups. Results HER2-low BC group tended to demonstrate high expression of ER and more progesterone receptor(PgR)positivity than HER2-IHC0 BC group(P<0.001).The rate of HER2-low status increased with increasing ER expression levels(Mantel-Haenszel χ2 test,P<0.001,Pearson's R=0.159,P<0.001).Survival analysis revealed a significantly longer overall survival(OS)in HER2-low BC group than in HER2-IHC0 group(P=0.007)in the whole cohort and the hormone receptor(HR)-negative group.There were no significant differences between the two groups in terms of disease-free survival(DFS).The discordance rate of HER2 IHC scores between primary and metastatic sites was 36.84%. Conclusion HER2-low BC may not be regarded as a unique BC group in this population-based study due to similar clinicopathological features and prognostic roles.

Following the principles of evidence-based medicine,in accordance with the structure and drafting rules of standardized documents,based on literature research,according to the characteristics of chronic cough in children and issues that need to form a consensus,the TCM Guidelines for Diagnosis and Treatment of Chronic Cough in Children was formulated based on the Delphi method,expert discussion meetings,and public solicitation of opinions.The guideline includes scope of application,terms and definitions,eti-ology and diagnosis,auxiliary examination,treatment,prevention and care.The aim is to clarify the optimal treatment plan of Chinese medicine in the diagnosis and treatment of this disease,and to provide guidance for improving the clinical diagnosis and treatment of chronic cough in children with Chinese medicine.

Decoction is a classical dosage form of traditional Chinese medicines. In the process of decocting, various complex components produce physical interactions and chemical reactions, among which physical interactions include van der Waals force, hydrogen bond, electrostatic interaction, π-π stacking, etc., and chemical reactions include Maillard reaction, oxidation reaction, hydrolysis reaction, degradation reaction, polymerization reaction, etc. New substances and original ingredients from chemical reactions can be further activated. These effects form the basis of particle formation in the broth. The sizes of the particles in decoctions range from nanoscale to micron scale, mostly composed of polysaccharide, protein matrix, wrapped in water insoluble molecules, can increase the dispersion of insoluble components and the stability of unstable components, as well as reduce the volatile components and toxic components of volatile components, and ultimately achieve the purpose of efficient absorption and toxicity reduction. From the angle of physical change and chemical reaction in the process of decoction, this paper expounds the formation mechanism of particles in decoction, expounds the research method of particles, analyzes the components in particles and the interaction between components, and then explains the pharmacodynamic characteristics of traditional Chinese medicine decoction, which provides the foundation for the modernization of Chinese decoction.

Ankylosing spondylitis (AS) combined with spinal fractures with thoracic and lumbar fracture as the most common type shows characteristics of unstable fracture, high incidence of nerve injury, high mortality and high disability rate. The diagnosis may be missed because it is mostly caused by low-energy injury, when spinal rigidity and osteoporosis have a great impact on the accuracy of imaging examination. At the same time, the treatment choices are controversial, with no relevant specifications. Non-operative treatments can easily lead to bone nonunion, pseudoarthrosis and delayed nerve injury, while surgeries may be failed due to internal fixation failure. At present, there are no evidence-based guidelines for the diagnosis and treatment of AS combined with thoracic and lumbar fracture. In this context, the Spinal Trauma Academic Group of Orthopedics Branch of Chinese Medical Doctor Association organized experts to formulate the Clinical guideline for the diagnosis and treatment of adult ankylosing spondylitis combined with thoracolumbar fracture ( version 2023) by following the principles of evidence-based medicine and systematically review related literatures. Ten recommendations on the diagnosis, imaging evaluation, classification and treatment of AS combined with thoracic and lumbar fracture were put forward, aiming to standardize the clinical diagnosis and treatment of such disorder.