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.

Hypoxic injury (HI) in the prenatal period often causes neonatal neurological disabilities. Due to the difficulty in obtaining clinical samples, the molecular and cellular mechanisms remain unclear. Here we use vascularized cerebral organoids to investigate the hypoxic injury phenotype and explore the intercellular interactions between vascular and neural tissues under hypoxic conditions. Our results indicate that fused vascularized cerebral organoids exhibit broader hypoxic responses and larger decreases in panels of neural development-related genes when exposed to low oxygen levels compared to single cerebral organoids. Interestingly, vessels also exhibit neural protective effects on T-box brain protein 2⁺ intermediate progenitors (IPs), which are markedly lost in HI cerebral organoids. Furthermore, we identify the role of bone morphogenic protein signaling in protecting IPs. Thus, this study has established an in vitro organoid system that can be used to study the contribution of vessels to brain injury under hypoxic conditions and provides a strategy for the identification of intervention targets.
Organoids/pathology* ; Animals ; Mice ; Hypoxia, Brain/metabolism* ; Brain/blood supply* ; Neurons/metabolism*

This study aimed to comprehensively examine the association of gallstones, cholecystectomy, and cancer risk. Multivariable logistic regressions were performed to estimate the observational associations of gallstones and cholecystectomy with cancer risk, using data from a nationwide cohort involving 239 799 participants. General and gender-specific two-sample Mendelian randomization (MR) analysis was further conducted to assess the causalities of the observed associations. Observationally, a history of gallstones without cholecystectomy was associated with a high risk of stomach cancer (adjusted odds ratio (aOR)=2.54, 95% confidence interval (CI) 1.50-4.28), liver and bile duct cancer (aOR=2.46, 95% CI 1.17-5.16), kidney cancer (aOR=2.04, 95% CI 1.05-3.94), and bladder cancer (aOR=2.23, 95% CI 1.01-5.13) in the general population, as well as cervical cancer (aOR=1.69, 95% CI 1.12-2.56) in women. Moreover, cholecystectomy was associated with high odds of stomach cancer (aOR=2.41, 95% CI 1.29-4.49), colorectal cancer (aOR=1.83, 95% CI 1.18-2.85), and cancer of liver and bile duct (aOR=2.58, 95% CI 1.11-6.02). MR analysis only supported the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer. This study added evidence to the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer, highlighting the importance of cancer screening in individuals with gallstones.
Humans ; Mendelian Randomization Analysis ; Gallstones/complications* ; Female ; Male ; Cholecystectomy/statistics & numerical data* ; Middle Aged ; Risk Factors ; Aged ; Adult ; Neoplasms/etiology* ; Stomach Neoplasms/epidemiology*

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*

BackgroundAlcohol use disorder （AUD） is a common chronic and relapsing psychiatric disorders. Identifying severe AUD early and intervening promptly is crucial to prevent irreversible harm. Currently， the assessment of AUD severity primarily relies on psychiatric examination by clinicians， and there is limited research on the factors influencing AUD severity and the development of prediction models. ObjectiveTo analyze the factors influencing AUD severity， and construct a risk prediction model to aid in the assessment of disease progression in AUD patients. MethodsA retrospective analysis was conducted on 1 358 first-time hospitalized patients admitted to Nanning Fifth People's Hospital from January 1， 2017 to December 31， 2022. These patients met the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5） criteria for AUD. Basic patient data was collected， and the patients were divided into two groups based on disease severity： mild-moderate group （n=330） and severe group （n=1 028）. The patients were randomly divided into training and test sets in a 7∶3 ratio. A Logistic regression model was constructed in the training set， and the predictive ability of the model for disease severity was evaluated using the receiver operating characteristic （ROC） curve in the test set. ResultsCompared with the mild-moderate group， the severe group had a higher proportion of patients living in urban areas （χ²=7.804）， were farmers （χ²=17.991）， had a higher frequency of alcohol consumption （more than 1 to 2 drinks/day） （χ²=35.267）， had a higher age at first drinking （t=-3.858）， had a greater number of comorbid somatic disorders （Z=-22.782）， and had higher proportions of γ-Glutamyl transpeptidase （χ²=259.940） and total bilirubin abnormalities （χ²=148.552） （P<0.01）. Logistic analysis conducted in the training set showed that being a farmer （OR=2.024， 95% CI： 1.352~3.029）， having an older age at first drinking （OR=1.075， 95% CI： 1.025~1.129）， drinking outside of mealtimes （OR=3.988， 95% CI： 2.408~6.606）， having total bilirubin abnormalities （OR=1.034， 95% CI： 1.000~1.069）， and having more comorbid somatic diseases （OR=4.386， 95% CI： 2.636~7.298） were identified as risk factors for disease severity in AUD patients. The area under curve （AUC） for this model in the test set was 0.906. ConclusionIn psychiatric hospitals， being a farmer， having an older age at first drinking， drinking outside of mealtimes， having abnormal total bilirubin levels， and having comorbidities with somatic illnesses may be risk factors for severe AUD.

BACKGROUND:The shoulder joint,as a non-weight-bearing joint of the human upper limb,is considered a perfect compromise between flexibility and stability.The traditional experimental mechanics research of shoulder joints has some limitations due to the complexity of internal structure,measurement techniques and ethical issues.The finite element analysis method is applied to the research of shoulder joints,which provides valuable reference conclusions for the discussion of shoulder joint diseases and the decision of surgical methods. OBJECTIVE:To review the status of finite element research in the field of the shoulder joint,and to put forward the prospect of future research. METHODS:The finite element analysis method was used to search the literature on shoulder joint complex-related diseases in PubMed,Web of Science,WanFang and CNKI databases by computer.Chinese search terms were"shoulder joint,finite element analysis,rotator cuff injury,glenoid labrum,shoulder joint replacement".English search terms were"FE,should joint,glenohumeral joint,rotator cuff tears,glenoid labrum,shoulder arthroplasty".The search period was mainly from January 2010 to January 2023.Some important documents were also tracked,retrieved and read. RESULTS AND CONCLUSION:(1)With the open network of model data and the establishment of relevant model databases,finite element research has become more and more standardized and reproducible.(2)The widely validated finite element model of the shoulder joint deepens our understanding of the shoulder field to enable more efficient clinical decision-making.(3)With the continuous development of computer technology and software development,future finite element research is bound to become an indispensable practical tool for clinical scientific research.

Objective To understand the prevalence status quo of mild cognitive impairment(MCI)in the elderly people by conducting the investigation on the elderly people in somewhere,and to explore the influ-encing factors of MCI in the elderly people to provide reference for constructing the MCI localized computer screening and diagnosis system in the elderly.Methods A multi-stage sampling method was used to deter-mine the survey population.The self-made questionnaires,mini mental state examination(MMSE),geriatric depression screening scale(GDS-15),geriatric anxiety screening scale,geriatric psychiatric symptoms scale,and daily living ability scale were used to collect or evaluate basic information,cognitive impairment,depres-sion,anxiety,psychiatric symptoms,and daily living ability of elderly people from March 5,2022 to July 22,2022.The index system affecting MCI was screened by the receiver operating characteristic(ROC)curve and unconditional binary logistic regression,and the localized computer screening diagnosis system was construc-ted.Results A total of 1 004 elderly individuals were surveyed,among them there were 262 cases(26.1％)of MCI,194 cases(19.3％)of anxious state,21 cases(2.1％)of depression,313 cases(31.2％)of psychotic symptoms and 32 cases(3.2％)of impaired ability of activities of daily living(ADL).The ROC curve analysis showed that the area under the curves(AUC)of depression,anxiety and psychotic symptoms for predicting MCI in elderly individuals were 0.640,0.645,and 0.586,respectively.AUC of anxiety combined with depres-sion(anxiety+depression),depression+psychotic symptoms,anxiety+psychotic symptoms and depression+anxiety+psychotic symptoms were 0.676,0.652,0.645 and 0.676,respectively.The multivariate analysis found that the age,whether or not anyone close to you died in the last two years,ability of activities of daily living,anxiety degree,whether or not having psychotic symptoms,education level,whether or not having joint habitation with the family members and suffering from multiple chronic diseases were the influencing factors of MCI.Conclusion The age,education level,death of close persons in the past two years,ability to live daily life,depression,and psychotic symptoms could serve as the indicators system of the MCI localized computer screening and diagnosis system.

Objective To evaluate the stability,safety and immune enhancement and anti-tumor effects of Wilms'tumor gene 1(WT1)peptide combined with AddaVaxTM emulsion vaccine for acute myeloid leukemia.Methods The stability of WT1 peptide in the adjuvant vaccine was evaluated using MALDI-TOF-MS time-of-flight mass spectrometry.Female C57BL/6 mice were randomly divided into PBS group,WT1 peptide group,and WT1 peptide+AddaVaxTMemulsion adjuvant vaccine group.The immunization was performed at a dose of 50 μg/mouse for antigen and 50 μg/mouse for adjuvant,with intramuscular injection on days 0,14,and 28.HE staining was used to assess the toxicity of intramuscular vaccination on mouse organ tissues.Cytokine levels were detected by ELISA,and the number of IFN-γ-secreting splenocytes was measured by ELISpot.Flow cytometry was employed to detect the maturation of bone marrow-derived dendritic cells(BMDCs)promoted by the vaccine in vitro and the promotion for lymphocyte activation,and H-2Db WT1 tetramer was utilized to detect the proportion of specific CD8+T cells.After establishing a mouse leukemia tumor model using the C1498-mWT1 stable cell line,the anti-tumor effects of the vaccine for prevention and treatment were evaluated.Results The WT1 peptide stably existed in the vaccine without causing significant organ tissue changes in mice after intramuscular injection.Compared to the mice immunized with WT1 aqueous solution,the mice after intramuscular injection of the WT1 peptide emulsion adjuvant vaccine showed stronger immune responses of Th1 cells,including IFN-γ and TNF-α,as well as Th17 cells of IL-17A(P＜0.05),and the mice had not only promoted number of IFN-γ secreting splenocytes(P＜0.01)but also enhanced maturation of BMDCs,as indicated by an increase in the proportions of CD40+/CD11c+and CD86+CD80+/CD11c+ cells(P＜0.05).Additionally,there were increases in both the proportion of CD4+/CD3+T and CD69+/CD8+T cells(P＜0.05)and the proportion of specific CD8+T cells(P＜0.05).In the anti-tumor effect study using the C1498-mWT1 mouse model,the median survival time of the WT1+AddaVaxTM group was extended by 6 d compared to the WT1 aqueous solution group.At day 50,the survival rate of mice in the WT1+AddaVaxTM group was still 28.5％,while all mice in the other groups had died(P＜0.05).Conclusion The vaccine with the WT1 peptide and AddaVaxTM emulsion adjuvant exhibits good immunological and anti-tumor effects.

Objective To investigate the antibacterial effect and its preliminary mechanism of lavender essential oil on multi-drug resistant Acinetobacter baumannii.Methods Micro-dilution method was used to determine the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC)of lavender essential oil against multi-drug resistant Acinetobacter baumannii,and bactericidal kinetic study was employed to determine the onset and maintenance time of lavender essential oil.Meanwhile,the promoting and therapeutic effects of lavender essential oil on wound healing were observed in a mouse model of infection.Subsequently,crystal violet staining was used to determine the inhibition and clearance of multi-drug resistant Acinetobacter baumannii biofilm by lavender essential oil,and laser confocal microscopy was utilized to observe the survival of bacteria in biofilms.NanoDrop instrument was utilized to quantify the leakage of bacterial DNA nucleic acid and protein after intervention with 3 and 6 mg/mL lavender essential oil,and the leakage of bacterial potassium ion was measured by potassium ion test kit.Proteomics technology combined with bio-informatics were applied to explore the action mechanism of lavender essential oil against multi-drug resistant Acinetobacter baumannii.Results The MIC and MBC of lavender essential oil were both 6 mg/mL,which could kill almost all multi-drug resistant Acinetobacter baumannii at the time point of 120 min,and showed an obvious dose-and time-dependent manner.The overall animal model evaluation showed that both 3 and 6 mg/mL lavender essential oil could promote wound healing,and the curative effect was obvious.Further studies confirmed that 3 mg/mL lavender essential oil had a certain biofilm inhibitory effect on multi-drug resistant Acinetobacter baumannii,and 6 mg/mL also had a certain biofilm clearance effect under the same conditions.Meanwhile,when incubated at 37℃ for 1 h,the dose of 3 mg/mL could increase the leakage of DNA nucleic acid and protein,and significantly promote the efflux of potassium ions.Proteomic analysis suggested that the antibacterial effect of lavender essential oil may be related to affecting the oxidorereductase activity and cell metabolic process of multi-drug resistant Acinetobacter baumannii,and interfering with the biosynthesis of cell wall/membrane/envelope and other structures.Conclusion Lavender essential oil at 3 mg/mL can play an antibacterial effect against multi-drug resistant Acinetobacter baumannii,and its mechanism may be related to the destruction of bacterial biofilm and interference with bacterial metabolism.

Objective:To understand the level of radiation doses from digital mammography in Tianjin and the associated influencing factors.Methods:The stratified quota sampling method was used for analysis of 374 digital mammography-examined individuals by using 12 digital mammography devices in 12 selected medical institutions. The examinations were carried out in terms of exposure positions[(craniocaudal (CC) and mediolateral oblique (MLO)], compressed breast thickness, tube voltage, time product of tube current (mAs) and target/filter.Results:The median age of the examined individuals in this survey was 43 years, the median tube voltage (kV) was 29 kV, the median tube current time product was 60.3 mAs, the median compressed breast thickness was 48 mm, and the median average glandular dose (AGD) was 1.32 mGy. The mean dose to the analyzed glandular tissue in the conditions of different target/filters varies in the descent order of Mo/Mo > Mo/Rh > Rh/Rh > W/Rh > W/Al, with the difference being statistically significant difference ( χ2=885.90, P<0.05). The mean dose to the glandular tissue increased with the increase in compressed breast thickness, and the difference was statistically significant ( χ2=31.58, 8.56, 76.13, 118.47, 24.09, P<0.05). Conclusions:The median average glandular dose in Tianjin was 1.32 mGy. This level is lower than in Guangxi province and Fuzhou city, similar to that in Beijing and Guangdong province, and lower than the national survey result of average breast dose. The efforts should be dedicated to further strengthening the research on the related factors of the average glandular dose in order to protect the health and safety of the examined individuals.