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.

In cases where a tracheal injury exceeds half the length of the adult trachea or one-third of the length of the child trachea, it becomes difficult to perform end-to-end anastomosis after tracheal resection due to excessive tension at the anastomosis site. In such cases, tracheal replacement therapy is required. Advances in tissue engineering technology have led to the development of tissue engineering tracheal substitutes, which have promising applications. Hydrogels, which are highly hydrated and possess a good three-dimensional network structure, biocompatibility, low immunogenicity, biodegradability, and modifiability, have had wide applications in the field of tissue engineering. This article provides a review of the characteristics, advantages, disadvantages, and effects of various hydrogels commonly used in tissue engineering trachea in recent years. Additionally, the article discusses and offers prospects for the future application of hydrogels in the field of tissue engineering trachea.

Heart failure is a complex clinical syndrome and pediatric heart failure (PHF) has a high mortality rate. Early diagnosis is crucial for treatment and management of PHF. In clinical practice, various tests and examinations play a key role in the diagnosis of PHF, including continuously updated biomarkers, echocardiography, and cardiac magnetic resonance imaging. This article focuses on summarizing relevant research on biomarkers, examinations, combined testing, clinical models, and the grading and staging of PHF diagnosis, aiming to provide insights and directions for the diagnosis of PHF.
Humans ; Heart Failure/diagnosis* ; Child ; Biomarkers/blood* ; Echocardiography ; Magnetic Resonance Imaging

OBJECTIVE: To retrospectively analyze the clinical characteristics, co-mutated genes in newly diagnosed acute myeloid leukemia (AML) patients with NRAS and KRAS gene mutations, and the impact of NRAS and KRAS mutations on prognosis. METHODS: The clinical data and next-generation sequencing results of 80 newly diagnosed AML patients treated at our hospital from December 2018 to December 2023 were collected. The clinical characteristics, co-mutated genes of NRAS and KRAS , and the impact of NRAS and KRAS mutations on prognosis in newly diagnosed AML patients were analyzed. RESULTS: Among 80 newly diagnosed AML patients, NRAS mutations were detected in 20 cases(25.0%), and KRAS mutations were detected in 9 cases(11.3%). NRAS mutations predominantly occurred at codons 12 and 13 of exon 2, as well as codon 61 of exon 3, while KRAS mutations were most commonly occurred at codons 12 and 13 of exon 2, all of which were missense mutations. There were no statistically significant differences observed in terms of age, sex, white blood cell count(WBC), hemoglobin(Hb), platelet count(PLT), bone marrow blasts, first induction chemotherapy regimen, CR1/CRi1 rates, chromosome karyotype, 2022 ELN risk classification and allogeneic hematopoietic stem cell transplantation(allo-HSCT) among the NRAS mutation group, KRAS mutation group and NRAS/KRAS wild-type group (P >0.05). KRAS mutations were significantly correlated with PTPN11 mutations (r =0.344), whereas no genes significantly associated with NRAS mutations were found. Survival analysis showed that compared to the NRAS/KRAS wild-type group, patients with NRAS mutation had a relatively higher 5-year overall survival (OS) rate and relapse-free survival (RFS) rate, though the differences were not statistically significant (P =0.097, P =0.249). Compared to the NRAS/KRAS wild-type group, patients with KRAS mutation had a lower 5-year OS rate and RFS rate, with no significant differences observed (P =0.275, P =0.442). There was no significant difference in the 5-year RFS rate between the KRAS mutation group and NRAS mutation group (P =0.157), but the 5-year OS rate of patients with KRAS mutation was significantly lower than that of patients with NRAS mutation (P =0.037). CONCLUSION In newly diagnosed AML patients, KRAS mutation was significantly correlated with PTPN11 mutation. Compared to patients with NRAS/KRAS wild-type, those with NRAS mutation showed a more favorable prognosis, while patients with KRAS mutation showed a poorer prognosis; however, these differences did not reach statistical significance. Notably, the prognosis of AML patients with KRAS mutation was significantly inferior compared to those with NRAS mutation.
Humans ; Leukemia, Myeloid, Acute/diagnosis* ; Mutation ; Prognosis ; Proto-Oncogene Proteins p21(ras)/genetics* ; GTP Phosphohydrolases/genetics* ; Retrospective Studies ; Membrane Proteins/genetics* ; Female ; Male ; Middle Aged ; Adult ; Aged

OBJECTIVE: Hepatocellular carcinoma (HCC) is sensitive to ferroptosis, a new form of programmed cell death that occurs in most tumor types. However, the mechanism through which ferroptosis modulates HCC remains unclear. This study aimed to investigate the oncogenic role and prognostic value of FANCD2 and provide novel insights into the prognostic assessment and prediction of immunotherapy. METHODS: Using clinicopathological parameters and bioinformatic techniques, we comprehensively examined the expression of FANCD2 macroscopically and microcosmically. We conducted univariate and multivariate Cox regression analyses to identify the prognostic value of FANCD2 in HCC and elucidated the detailed molecular mechanisms underlying the involvement of FANCD2 in oncogenesis by promoting iron-related death. RESULTS: FANCD2 was significantly upregulated in digestive system cancers with abundant immune infiltration. As an independent risk factor for HCC, a high FANCD2 expression level was associated with poor clinical outcomes and response to immune checkpoint blockade. Gene set enrichment analysis revealed that FANCD2 was mainly involved in the cell cycle and CYP450 metabolism. CONCLUSION To the best of our knowledge, this is the first study to comprehensively elucidate the oncogenic role of FANCD2. FANCD2 has a tumor-promoting aspect in the digestive system and acts as an independent risk factor in HCC; hence, it has recognized value for predicting tumor aggressiveness and prognosis and may be a potential biomarker for poor responsiveness to immunotherapy.
Humans ; Carcinoma, Hepatocellular/diagnosis* ; Liver Neoplasms/diagnosis* ; Immunotherapy ; Fanconi Anemia Complementation Group D2 Protein/metabolism* ; Prognosis ; Male ; Female ; Middle Aged ; Biomarkers, Tumor/metabolism*

The emerging and re-emerging arthropod-borne infectious diseases pose a serious threat to global public health security. Field and laboratory studies of arthropods of medical importance are essential and critical for the prevention and control of arthropod-borne infectious diseases. Various institutions or universities in China have been conducting research in the field or laboratory study of arthropods of medical importance, but up to 2023, it is still lacking detailed biosafety guidelines or recommendations that can guide the related work for arthropods of medical importance. In order to proactively address potential biosafety issues in the field or laboratory activities related to arthropods of medical importance, improve the standardization of arthropod biosafety classification, operations, and protection, and ensure the safety of practitioners, an expert consensus on the biosafety recommendation of arthropods of medical importance in field and laboratory has been developed, aiming to guide the future work of arthropods and ensure the national biosafety and biosecurity of China.

Objective:To evaluate the clinical application effects of a domestic bone-level implant system for restoring single tooth loss, and provide clinical evidence for the promotion and application of domestic implants.Methods:A prospective, multicenter clinical trial was conducted from April 2018 to January 2020 in three institutions: Department of Oral Implantology, School & Hospital of Stomatology, Wuhan University, Department of Stomatology, The First Affiliated Hospital of Zhejiang University School of Medicine, and Department of Stomatology, The Third Hospital of Hebei Medical University. The trial planned to include 100 patients for single tooth implantation and restoration, followed up for 1 year, to evaluate the implantation success rate and other related outcomes.Results:This study screened a total of 142 patients and ultimately included 100, comprising 43 males and 57 females with age of (47.0±12.2) years. Ninety-eight out of 100 patients completed a one-year follow-up (98.0%), while 2 patients terminated the trial early due to implant loosening (2.0%). After a one-year follow-up, the implants of the 98 patients were all functioning successfully, with a success rate of 98.0% (98/100). The patients were satisfied with the overall restoration effect.Conclusions:This study indicates that the domestic bone-level implant system has achieved favorable short-term clinical outcomes for single-tooth implantation and restoration.

Objective To explore characteristics of clinical parameters and cytokines in patients with drug-induced liver injury(DILI)caused by different drugs and their correlation with clinical indicators. Method The study was conducted on patients who were up to Review of Uncertainties in Confidence Assessment for Medical Tests(RUCAM)scoring criteria and clinically diagnosed with DILI.Based on Chinese herbal medicine,cardiovascular drugs,non-steroidal anti-inflammatory drugs(NSAIDs),anti-infective drugs,and other drugs,patients were divided into five groups.Cytokines were measured by Luminex technology.Baseline characteristics of clinical biochemical indicators and cytokines in DILI patients and their correlation were analyzed. Results 73 patients were enrolled.Age among five groups was statistically different(P=0.032).Alanine aminotransferase(ALT)(P=0.033)and aspartate aminotransferase(AST)(P=0.007)in NSAIDs group were higher than those in chinese herbal medicine group.Interleukin-6(IL-6)and tumor necrosis factor alpha(TNF-α)in patients with Chinese herbal medicine(IL-6:P<0.001;TNF-α:P<0.001)and cardiovascular medicine(IL-6:P=0.020;TNF-α:P=0.001)were lower than those in NSAIDs group.There was a positive correlation between ALT(r=0.697,P=0.025),AST(r=0.721,P=0.019),and IL-6 in NSAIDs group. Conclusion Older age may be more prone to DILI.Patients with NSAIDs have more severe liver damage in early stages of DILI,TNF-α and IL-6 may partake the inflammatory process of DILI.

Objective To explore the mechanism of Yangxue Qingnao Granules(Siwu Decoction modified)in the treatment of hypertension based on network pharmacology and molecular docking.Methods The chemical composition analysis results of Yangxue Qingnao Granules in the early stage of the research group were used as the basis for the screening of active compounds.The oral bioavailability≥30%and drug-likeness≥0.18 were used as the screening conditions,and the blood components were supplemented in combination with the literature.TCMSP,chemical professional database and SWISS database were used to predict the targets of potential active compounds of Yangxue Qingnao Granules.Hypertension-related targets were obtained through GeneCards and DiGSeE databases.The intersection of the targets related to hypertension disease and the targets of the potential active compounds of Yangxue Qingnao Granules(common targets)is the potential target of Yangxue Qingnao Granules for the treatment of hypertension.The potential targets were matched with the potential active compounds of Yangxue Qingnao Granules to obtain the antihypertensive active compounds of Yangxue Qingnao Granules.PPI analysis was performed on the potential targets of serum brain granules in the treatment of hypertension through the STRING database,and the core targets were screened according to the degree value.The David database was used to analyze the GO function and KEGG pathway enrichment of the core targets.The core targets with the top six degrees were selected as the docking target proteins,and molecular docking verification was performed with the antihypertensive active compounds.Results A total of 32 potential active compounds,161 active compound targets and 1 539 hypertension-related targets were obtained.After intersection,88 potential targets(common targets)of Yangxue Qingnao Granules in the treatment of hypertension were obtained,involving 29 antihypertensive active compounds.PPI analysis screened 14 core targets:PPARG,ACHE,IL4,CCL2,JUN,NOS3,APP,IL1B,CAT,PTGS2,CASP3,TP53,TNF,IL6,involving 158 GO entries and 13 signaling pathways.Five key active ingredients,chlorogenic acid,rosmarinic acid,paeoniflorin catechinic acid and aloe emodin,were obtained by molecular docking,which were combined with PTGS2,CASP3,TNF,CAT,TP53 and IL6,respectively.Conclusion Yangxue Qingnao Granules may act on core targets such as PTGS2 and CASP3 through key active components such as chlorogenic acid and rosmarinic acid,regulate key pathways such as TNF signaling pathway,MAPK signaling pathway and Toll-like receptor signaling pathway,and play a role in the treatment of hypertension through anti-inflammatory effects.