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.

PURPOSE: To assess the relationship between dislocation and functional outcomes in supination-external rotation (SER) ankle fractures. METHODS: A retrospective case series study was performed on patients with ankle fractures treated surgically at a large trauma center from January 2015 to December 2021. The inclusion criteria were young and middle-aged patients of 18 - 65 years with SER ankle fractures that can be classified by Lauge-Hansen classification and underwent surgery at our trauma center. Exclusion criteria were serious life-threatening diseases, open fractures, fractures delayed for more than 3 weeks, fracture sites ≥ 2, etc. Then patients were divided into dislocation and no-dislocation groups. Patient demographics, injury characteristics, surgery-related outcomes, and postoperative functional outcomes were collected and analyzed. The functional outcomes of SER ankle fractures were assessed postoperatively at 1-year face-to-face follow-up using the foot and ankle outcome score (FAOS) and American Orthopedic Foot and Ankle Society ankle hindfoot score and by 2 experienced orthopedic physicians. Relevant data were analyzed using SPSS version 22.0 by Chi-square or t-test. RESULTS: During the study period, there were 371 ankle fractures. Among them, 190 (51.2%) were SER patterns with 69 (36.3%) combined with dislocations. Compared with the no-dislocation group, the dislocation group showed no statistically significant differences in gender, age composition, fracture type, diabetes, or smoking history, preoperative waiting time, operation time, and length of hospital stay (all p > 0.05), but a significantly higher Lauge-Hansen injury grade (p < 0.001) and syndesmotic screw fixation rate (p = 0.033). Moreover, the functional recovery was poorer, revealing a significantly lower FAOS in the sport/rec scale (p < 0.001). Subgroup analysis showed that among SER IV ankle fracture patients, FAOS was much lower in pain (p = 0.042) and sport/rec scales (p < 0.001) for those with dislocations. American Orthopedic Foot and Ankle Society ankle hindfoot score revealed no significant difference between dislocation and no-dislocation patients. CONCLUSION Dislocation in SER ankle fractures suggests more severe injury and negatively affects functional recovery, mainly manifested as more pain and poorer motor function, especially in SER IV ankle cases.
Humans ; Ankle Fractures/physiopathology* ; Male ; Female ; Retrospective Studies ; Adult ; Middle Aged ; Supination ; Aged ; Young Adult ; Rotation ; Joint Dislocations/surgery* ; Fracture Fixation, Internal/methods* ; Adolescent ; Recovery of Function ; Treatment Outcome

PURPOSE: To evaluate the diagnostic accuracy of the observational chart for traumatic limb swelling (OCTLS) for osteofascial compartment syndrome (OCS). METHODS: This was a descriptive-longitudinal study. Data of 316 patients who underwent surgical treatment for tibial fractures in our department from January 2015 to December 2023 were collected. Patients with Gustilo type II or higher open fractures, vascular injury, or bilateral fractures were excluded from the study. Two groups of double-blinded investigators independently assessed patients for the presence of OCS using 2 distinct diagnostic methods. Three senior orthopedic trauma surgeons evaluated patients with post-fracture calf swelling for OCS and the need for fasciotomy based on clinical signs and their extensive clinical experience. Subsequently, fasciotomy was performed according to their judgment, followed by postoperative examination of muscle and soft tissue conditions. Additionally, a follow-up evaluation was conducted to assess for complications such as ischemic muscle contracture. Another 3 trained researchers used OCTLS to grade swelling severity and determine the need for fasciotomy. The final diagnostic gold standard of OCS was determined by referring to whether there was escape of muscles at fasciotomy and/or color change in the muscles or muscle necrosis intraoperatively, and neurological abnormality or contracture at the last follow-up. The results of the 2 diagnostic methods were compared with the final diagnostic result. Kappa consistency test, paired χ² test (McNemar test), and receiver operating characteristic curve were used to evaluate the diagnostic efficacy of the 2 diagnostic methods. RESULTS: Of the 316 patients, 211 were finally included in the study, including 160 males and 51 females, with an average follow-up time of (14.5 ± 2.7) months. Among the 211 patients with tibial fracture-associated swelling, 42 were definitively diagnosed with OCS. Based on clinical symptoms and signs judgment, among the 65 fasciotomy patients, 38 were confirmed as correct, while among the 146 non-fasciotomy patients, 4 developed ischemic muscle contractures. Based on the OCTLS for assessment, fasciotomy was correctly recommended in 36 out of 43 cases, while 6 out of 168 non-fasciotomy patients developed OCS. Compared to the use of the gold standard, clinical signs judgment showed moderate consistency (McNemar's test p < 0.001, Kappa = 0.618, p < 0.001), whereas OCTLS demonstrated strong agreement (McNemar's test p = 1.000, Kappa = 0.808, p < 0.001). Receiver operating characteristic analysis revealed higher diagnostic accuracy for OCTLS (area under curve = 0.908, 95% CI: 0.843 - 0.972) compared to clinical signs judgment (area under curve = 0.872, 95% CI: 0.812 - 0.933). OCTLS achieved superior accuracy (93.8% vs. 85.3%, χ² = 8.221, p < 0.001) and a lower fasciotomy rate (20.4% vs. 30.8%, χ² = 6.023, p = 0.014). CONCLUSION Compared to clinical signs judgment, OCTLS significantly reduces unnecessary fasciotomy, improves diagnostic accuracy for OCS, and enables non-invasive, dynamic, and quantitative assessment, making it a valuable tool for clinical practice.
Humans ; Compartment Syndromes/etiology* ; Male ; Female ; Adult ; Tibial Fractures/surgery* ; Middle Aged ; Fasciotomy ; Edema/etiology* ; Longitudinal Studies ; Aged ; Young Adult

OBJECTIVE: To investigate the expression and potential mechanism of calcium/calmodulin-dependent protein kinase II gamma (CaMKIIγ) in patients with acute myeloid leukemia (AML). METHODS: Peripheral blood samples were collected from 90 AML patients, and mononuclear cells were isolated. The expression of CaMKIIγ was measured using real-time quantitative PCR and Western blot. The diagnostic value of CaMKIIγ for AML was assessed, and its correlation with clinical characteristics was analyzed using the clinical data of patients. Additionally, the molecular mechanisms of CaMKIIγ were preliminarily explored. RESULTS: Compared with the control group, the expression of CaMKIIγ was significantly upregulated in AML patients. Receiver operating characteristic (ROC) curve analysis showed that CaMKIIγ could serve as a promising biomarker for distinguishing AML patients from healthy individuals. Furthermore, CaMKIIγ was significantly correlated with white blood cell (WBC) count and FLT3-ITD mutation. CaMKIIγ was highly expressed in both newly diagnosed and relapsed AML patients, while decreased during remission. In AML cell lines, the expression levels of CaMKIIγ were all elevated. Inhibition of phosphorylated CaMKIIγ by berbamine led to a decrease in pAKT and pSTAT5 expression. CONCLUSION CaMKIIγ is significantly upregulated in AML patients, and is associated with poor clinicopathological features and unfavorable prognosis. It may serve as a prognostic marker and potential therapeutic target in AML. Its expression may be related to the activation of pAKT and pSTAT5, suggesting that CaMKIIγ may contribute to the development and progression of AML through the activation of the AKT/STAT5 signaling pathway.
Humans ; Leukemia, Myeloid, Acute/metabolism* ; Calcium-Calmodulin-Dependent Protein Kinase Type 2/metabolism* ; STAT5 Transcription Factor/metabolism* ; Male ; Female ; Proto-Oncogene Proteins c-akt/metabolism* ; Mutation ; Middle Aged ; Adult ; Clinical Relevance

BACKGROUND: Our understanding of the correlation between postdischarge cancer and mortality in patients with coronary artery disease (CAD) remains incomplete. The aim of this study was to investigate the relationships between postdischarge cancers and all-cause mortality and cardiovascular mortality in CAD patients. METHODS: In this retrospective cohort study, 25% of CAD patients without prior cancer history who underwent coronary artery angiography between January 1, 2011 and December 31, 2015, were randomly enrolled using SPSS 26.0. Patients were monitored for the incidence of postdischarge cancer, which was defined as cancer diagnosed after the index hospitalization, survival status and cause of death. Cox regression analysis was used to explore the association between postdischarge cancer and all-cause mortality and cardiovascular mortality in CAD patients. RESULTS: A total of 4085 patients were included in the final analysis. During a median follow-up period of 8 years, 174 patients (4.3%) developed postdischarge cancer, and 343 patients (8.4%) died. A total of 173 patients died from cardiovascular diseases. Postdischarge cancer was associated with increased all-cause mortality risk (HR = 2.653, 95% CI: 1.727-4.076, P < 0.001) and cardiovascular mortality risk (HR = 2.756, 95% CI: 1.470-5.167, P = 0.002). Postdischarge lung cancer (HR = 5.497, 95% CI: 2.922-10.343, P < 0.001) and gastrointestinal cancer (HR = 1.984, 95% CI: 1.049-3.750, P = 0.035) were associated with all-cause mortality in CAD patients. Postdischarge lung cancer was significantly associated with cardiovascular death in CAD patients (HR = 4.979, 95% CI: 2.114-11.728, P < 0.001), and cardiovascular death was not significantly correlated with gastrointestinal cancer or other types of cancer. CONCLUSIONS Postdischarge cancer was associated with all-cause mortality and cardiovascular mortality in CAD patients. Compared with other cancers, postdischarge lung cancer had a more significant effect on all-cause mortality and cardiovascular mortality in CAD patients.

Colonic mucosal healing is the ultimate goal of ulcerative colitis (UC) treatment, but it remains difficult to realize. Given the higher incidence of UC in males and the beneficial effect of estrogen on UC, we conducted this study to examine the therapeutic potential of estrogen receptor β (ERβ), the primary ER subtype in colon, on mucosal healing in UC. Our study is the first to report that ERβ activation degree was positively correlated with mucosal healing in patients with UC. Furthermore, ERβ activation enhanced mucosal healing in mice with dextran sulfate sodium-induced and biopsy-induced colonic injuries. Mechanistically, ERβ activation promoted autophagy of colonic epithelial cells by inhibiting branched-chain amino acid transport, leading to focal adhesion kinase (FAK) activation. Activated FAK promoted focal adhesion turnover and colonic epithelial cell migration, ultimately facilitating mucosal healing. ERβ ^-/- colitis mice exhibited impaired mucosal healing compared to wild-type littermates, highlighting the crucial effect of ERβ. Importantly, combination with ERβ-agonist diarylpropionitrile enhanced the amelioration of 5-aminosalicylic acid, a standard UC treatment agent, against mouse colitis. These findings attest to the crucial role of ERβ activation in colonic mucosal healing and may further inform the development of novel strategies for UC treatment.

Glutamine provides carbon and nitrogen to support the proliferation of cancer cells. However, the precise reason why cancer cells are particularly dependent on glutamine remains unclear. In this study, we report that glutamine modulates the tumor suppressor F-box and WD repeat domain-containing 7 (FBW7) to promote cancer cell proliferation and survival. Specifically, lysine 604 (K604) in the sixth of the 7 substrate-recruiting WD repeats of FBW7 undergoes glutaminylation (Gln-K604) by glutaminyl tRNA synthetase. Gln-K604 inhibits SCFFBW7-mediated degradation of c-Myc and Mcl-1, enhances glutamine utilization, and stimulates nucleotide and DNA biosynthesis through the activation of c-Myc. Additionally, Gln-K604 promotes resistance to apoptosis by activating Mcl-1. In contrast, SIRT1 deglutaminylates Gln-K604, thereby reversing its effects. Cancer cells lacking Gln-K604 exhibit overexpression of c-Myc and Mcl-1 and display resistance to chemotherapy-induced apoptosis. Silencing both c-MYC and MCL-1 in these cells sensitizes them to chemotherapy. These findings indicate that the glutamine-mediated signal via Gln-K604 is a key driver of cancer progression and suggest potential strategies for targeted cancer therapies based on varying Gln-K604 status.
Glutamine/metabolism* ; Myeloid Cell Leukemia Sequence 1 Protein/genetics* ; Humans ; Proto-Oncogene Proteins c-myc/genetics* ; Cell Proliferation ; Signal Transduction ; Neoplasms/pathology* ; F-Box-WD Repeat-Containing Protein 7/genetics* ; Cell Survival ; Cell Line, Tumor ; Apoptosis

Advancements in artificial intelligence (AI) and emerging technologies are rapidly expanding the exploration of chemical space, facilitating innovative drug discovery. However, the transformation of novel compounds into safe and effective drugs remains a lengthy, high-risk, and costly process. Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development. Despite this need, no comprehensive tool currently supports systematic evaluation and efficient screening. Here, we present druglikeFilter, a deep learning-based framework designed to assess drug-likeness across four critical dimensions: 1) physicochemical rule evaluated by systematic determination, 2) toxicity alert investigated from multiple perspectives, 3) binding affinity measured by dual-path analysis, and 4) compound synthesizability assessed by retro-route prediction. By enabling automated, multidimensional filtering of compound libraries, druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates, which can be freely accessed at https://idrblab.org/drugfilter/.

OBJECTIVE: CRISPR-Cas protects bacteria from exogenous DNA invasion and is associated with bacterial biofilm formation and pathogenicity. METHODS: We analyzed the type I-F CRISPR-Cas system of Legionella pneumophila WX48, including Cas1, Cas2-Cas3, Csy1, Csy2, Csy3, and Cas6f, along with downstream CRISPR arrays. We explored the effects of the CRISPR-Cas system on the in vitro growth, biofilm-forming ability, and pathogenicity of L. pneumophila through constructing gene deletion mutants. RESULTS: The type I-F CRISPR-Cas system did not affect the in vitro growth of wild-type or mutant strains. The biofilm formation and intracellular proliferation of the mutant strains were weaker than those of the wild type owing to the regulation of type IV pili and Dot/Icm type IV secretion systems. In particular, Cas6f deletion strongly inhibited these processes. CONCLUSION The type I-F CRISPR-Cas system may reduce biofilm formation and intracellular proliferation in L. pneumophila.
Legionella pneumophila/pathogenicity* ; CRISPR-Cas Systems ; Biofilms/growth & development* ; Phenotype ; Bacterial Proteins/metabolism* ; Gene Deletion