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.

This study aims to establish the S_(180) tumor-bearing mice model, and to investigate the influence of Shenqi Erpi Granules(SQEPG) on immune function, as well as the drug's tumor-suppressive effect and mechanism. SPF grade KM mice(half male and half female) were randomly divided into 6 groups: a control group, a model group, a cyclophosphamide group(50 mg·kg~(-1)), as well as SQEPG groups in low-, medium-, and high-dose(5.25, 10.5, 21 g·kg~(-1)). The control group and the model group were given distilled water, and the other 4 groups were given the corresponding drugs by gavage. The administration continued for 10 days before the mice were sacrificed. The antitumor and immune regulation effects of SQEPG were evaluated. The effect of SQEPG on delayed type hypersensitivity reaction(DTH), carbon clearance index, and serum hemolysin antibody level was observed to reflect the effect on the immune function of tumor-bearing mice. Tumor weight was recorded to calculate the tumor suppression rate and the immune organ index. Hematoxylin-eosin(HE) staining was used to detect morphological changes in tumor tissues. Flow cytometry was employed to detect the percentage of CD4~+ and CD8~+ T-cells in the spleen tissues and the tumor tissue apoptosis levels. Immunohistochemistry was conducted to detect the KI67 protein expression level of tumor tissues. ELISA resorted to the detection of the following expression levels in tumor tissues: tumor necrosis factor-α(TNF-α), interleukin-2(IL-2), interferon-γ(IFN-γ). Western blot was performed to detect the expression levels of caspase-3, B-cell lymphoma-2(Bcl-2), Bcl-2-associated X protein(Bax), cyclin-dependent kinases 4(CDK4), G_1/S-specific cyclin D1(cyclin D1), and vascular endothelial growth factor A(VEGFA). The results showed that, compared with the model group, the SQEPG could increase the swelling of the auricle of the tumor-bearing mice; significantly increase the phagocytic index of carbon granule contour(P<0.05 or P<0.01), and the middle dose of SQEPG could significantly increase the antibody level of hemolysin(P<0.05); different doses of SQEPG significantly inhibit the growth of the tumor, and decrease the mass of the tumor tissues(P<0.05 or P<0.01); the low dose of SQEPG significantly decreased spleen index(P<0.05), low and high doses of SQEPG increased thymus index, while medium doses of SQEPG decreased thymus index. High doses of SQEPG significantly elevated the levels of CD4~+ and CD8~+ T-cells in the spleens of the homozygous mice(P<0.01 or P<0.001), and increased the apoptosis rate of the cells of the tumor tissues(P<0.05); Meanwhile, high-dose SQEPG elevated the levels of immunity factors such as IL-2, IFN-γ and TNF-α in the serum of tumor-bearing mice(P<0.01); medium-and high-dose SQEPG significantly lowered the rate of positive expression of KI67 protein in tumor tissues(P<0.01). Compared with the model group, high-dose SQEPG significantly up-regulated the expression of caspase-3 and Bax proteins in tumor tissues(P<0.05), and significantly down-regulated the expression of CDK4, cyclin D1, and VEGFA proteins(P<0.05 or P<0.01). In conclusion, SQEPG has the effect of improving immune function and inhibiting tumor growth in tumor-bearing mice. Its mechanism of tumor-suppressive effects may be related to apoptosis promotion, cell cycle progression block, and tumor cell proliferation inhibition.
Animals ; Mice ; Drugs, Chinese Herbal/pharmacology* ; Male ; Female ; Apoptosis/drug effects* ; Sarcoma 180/genetics* ; Humans

Alzheimer's disease (AD) is the major form of dementia in the elderly and is closely related to the toxic effects of microglia sustained activation. In AD, sustained microglial activation triggers impaired synaptic pruning, neuroinflammation, neurotoxicity, and cognitive deficits. Accumulating evidence has demonstrated that aberrant expression of deubiquitinating enzymes is associated with regulating microglia function. Here, we use RNA sequencing to identify a deubiquitinase YOD1 as a regulator of microglial function and AD pathology. Further study showed that YOD1 knockout significantly improved the migration, phagocytosis, and inflammatory response of microglia, thereby improving the cognitive impairment of AD model mice. Through LC-MS/MS analysis combined with Co-IP, we found that Myosin heavy chain 9 (MYH9), a key regulator maintaining microglia homeostasis, is an interacting protein of YOD1. Mechanistically, YOD1 binds to MYH9 and maintains its stability by removing the K48 ubiquitin chain from MYH9, thereby mediating the microglia polarization signaling pathway to mediate microglia homeostasis. Taken together, our study reveals a specific role of microglial YOD1 in mediating microglia homeostasis and AD pathology, which provides a potential strategy for targeting microglia to treat AD.

Somatostatin receptor 1 (SSTR1) is a crucial therapeutic target for various neuroendocrine and oncological disorders. Current SSTR1-targeted treatments, including the first-generation somatostatin analog lanreotide (Lan) and the second-generation analog pasireotide (Pas), show promise but encounter challenges related to selectivity and efficacy. This study presents high-resolution cryo-electron microscopy structures of SSTR1 complexed with Lan or Pas, revealing the distinct mechanisms of ligand-binding and activation. These structures illustrate unique conformational changes in the SSTR1 orthosteric pocket induced by each ligand, which are critical for receptor activation and ligand selectivity. Combined with the biochemical assays and molecular dynamics simulations, our results provide a comparative analysis of binding characteristics within the SSTR family, highlighting subtle differences in SSTR1 activation by Lan and Pas. These insights pave the way for designing next-generation therapies with enhanced efficacy and reduced side effects through improved receptor subtype selectivity.

Traditional development of small protein scaffolds has relied on display technologies and mutation-based engineering, which limit sequence and functional diversity, thereby constraining their therapeutic and application potential. Protein design tools have significantly advanced the creation of novel protein sequences, structures, and functions. However, further improvements in design strategies are still needed to more efficiently optimize the functional performance of protein-based drugs and enhance their druggability. Here, we extended an evolution-based design protocol to create a novel minibinder, BindHer, against the human epidermal growth factor receptor 2 (HER2). It not only exhibits super stability and binding selectivity but also demonstrates remarkable properties in tissue specificity. Radiolabeling experiments with ^99mTc, ⁶⁸Ga, and ¹⁸F revealed that BindHer efficiently targets tumors in HER2-positive breast cancer mouse models, with minimal nonspecific liver absorption, outperforming scaffolds designed through traditional engineering. These findings highlight a new rational approach to automated protein design, offering significant potential for large-scale applications in therapeutic mini-protein development.

Chronic, unresolved inflammation correlates with persistent hepatic injury and fibrosis, ultimately progressing to hepatocellular carcinoma (HCC). Bisdemethoxycurcumin (BDMC) demonstrates therapeutic potential against HCC, yet its mechanism in preventing hepatic "inflammation-carcinoma transformation" remains incompletely understood. In the current research, clinical HCC specimens underwent analysis using hematoxylin-eosin (H&E) staining and immunohistochemistry (IHC) to evaluate the expression of fibrosis markers, M2 macrophage markers, and CXCL12. In vitro, transforming growth factor-β1 (TGF-β1)-induced LX-2 cells and a co-culture system of LX-2, THP-1, and HCC cells were established. Cell functions underwent assessment through 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), flow cytometry, and Transwell assays. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR), Western blotting and immunofluorescence evaluated the differential expression of molecules. The interaction between β-catenin/TCF4 and CXCL12 was examined using co-immunoprecipitation (Co-IP), dual luciferase, and chromatin immunoprecipitation (ChIP) assays. A DEN-induced rat model was developed to investigate BDMC's role in liver fibrosis-associated HCC (LFAHCC) development in vivo. Our results showed that clinical HCC tissues exhibited elevated fibrosis and enriched M2 macrophages. BDMC delayed liver fibrosis progression to HCC in vivo. BDMC inhibited the inflammatory microenvironment induced by activated hepatic stellate cells (HSCs). Furthermore, BDMC suppressed M2 macrophage-induced fibrosis and HCC cell proliferation and metastasis. Mechanistically, BDMC repressed TCF4/β-catenin complex formation, thereby reducing CXCL12 transcription in LX-2 cells. Moreover, CXCL12 overexpression reversed BDMC's inhibitory effect on macrophage M2 polarization and its mediation of fibrosis, as well as HCC proliferation and metastasis. BDMC significantly suppressed LFAHCC development through CXCL12 in rats. In conclusion, BDMC inhibited LFAHCC progression by reducing M2 macrophage polarization through suppressing β-catenin/TCF4-mediated CXCL12 transcription.
Animals ; Liver Neoplasms/etiology* ; Humans ; Carcinoma, Hepatocellular/immunology* ; Liver Cirrhosis/complications* ; Macrophages/drug effects* ; Male ; Rats ; Chemokine CXCL12/genetics* ; Diarylheptanoids/pharmacology* ; Rats, Sprague-Dawley ; beta Catenin/genetics*

Objective:To evaluate the treatment strategies and outcomes for contracted nasal deformity.Methods:A retrospective review was conducted of the patients with contracted noses who underwent surgery at the Department of Plastic and Aesthetic Surgery, the Second Xiangya Hospital of Central South University, between January 2021 and January 2024. Based on the pathologic-anatomic features and severity of the deformity, patients were categorized as having mild, moderate or severe contraction. Mild cases received extensive subcutaneous dissection and framework reconstruction with various grafts. Moderate cases underwent preoperative nasal-skin distraction and intra-operative reconstruction with lower lateral or septal cartilage. Severe cases, in addition to reconstruction of the lower lateral cartilage and nasal septum, underwent individualized repair, including mucosal or cutaneous defect resurfacing. Postoperative follow-up assessed nasal appearance, complications and recurrence of contraction. Nasal aesthetics were quantified with visual analogue scale (VAS, 0-10 points; higher scores = less deformity), and patient satisfaction with the rhinoplasty outcome evaluation (ROE) questionnaire (0 = very dissatisfied, 100 = very satisfied) before surgery and at final follow-up. Paired t-test was used for VAS and ROE comparisons; categorical variables were analyzed with the χ2 test. A P-value < 0.05 denoted statistical significance. Results:A total of 96 patients were included, comprising 7 males and 89 females, aged (27.4 ± 8.0) years (19-58 years). There were 64 cases of mild, 19 cases of moderate, and 13 cases of severe contracted nose deformities. Postoperative follow-up(14.0 ± 4.6) months (6-19 months). No cases of abnormal nasal appearance, infection, necrosis, scar hyperplasia, or recurrence of contracted nose were observed during follow-up. Significant improvements in nasal aesthetic outcomes were observed. The VAS scores for mild, moderate, and severe contracted noses increased significantly from preoperative values of 4.7 ± 1.0, 3.0 ± 1.2, and 2.2± 1.1 to postoperative values of 8.6 ± 0.7, 8.9 ± 0.7, and 8.2 ± 0.9, respectively (all P < 0.01). Similarly, the ROE scores improved significantly from 59.1 ± 10.0, 34.2 ± 12.1, and 28.5± 6.3 preoperatively to 90.2 ± 9.5, 91.5 ± 7.5, and 93.3 ± 5.8 postoperatively (all P < 0.01). Conclusion:Selecting appropriate surgical methods based on the pathological and anatomical characteristics and severity of contracted nose deformities can achieve favorable outcomes. Postoperative nasal aesthetic appearance is significantly improved, and patient satisfaction is high.

Objective:To analyze the distribution characteristics and influencing factors of prolonged length in the elderly patients at a tertiary hospital.Methods:Medical records of patients receiving inpatient care at Xiangya Hospital, Central South University in Hunan province during January 1, 2021 and December 31, 2023 were collected.The generalized estimating equation(GEE)model was used to analyze the factors influencing prolonged hospitalization in elderly patients.Results:A total of 144 921 elderly inpatients were included, aged 60 to 104 years, with 84 950 males and 59 971 females.The average length of hospitalization was 7.81 days, with 2 614 patients hospitalized for more than 30 days (1 663 males and 951 females), and the average length of stay for these patients was 44.93 days.Most of the patients with prolonged length were hospitalized for 30 to 40 days, and in the group of aged 60-74 years.Disease categories mainly were related to health conditions, healthcare facility contact, tumors, and circulatory system diseases.The GEE model analysis showed that nosocomial infection [ OR(95% CI): 5.836(4.716-7.221)], age≥90 [ OR(95% CI): 2.415(1.680-3.472)], surgery [ OR(95% CI): 3.543(2.925-4.291)], number of complications>4[ OR(95% CI): 2.378(2.091-2.704)], unplanned hospital readmissions within 31 days [ OR(95% CI): 1.748(1.525-2.004)]were risk factors of prolonged hospitalization; female [ OR(95% CI): 0.901(0.824-0.986)] and no transferred hospitalization [ OR(95% CI): 0.154(0.140-0.169)] were protective factors. Conclusions:Prolonged hospitalization is related to the clinical and social factors.Administration department of the hospital should strengthen the monitoring of these influencing factors, reduce or prevent the occurrence of prolonged length of stay by adopting targeted measures, and further realize rational allocation of medical resources.

Objective To systematically evaluate the factors affecting taste alteration in patients undergoing cancer chemotherapy.Methods PubMed,Cochrane Library,Web of Science,CINAHL,Embase,CBM,CNKI,WanFang Data and VIP were searched from the establishment until August 1,2024.The retrieved literature was independently screened,evaluated and the data were extracted by 2 researchers,and statistical analysis was performed using Stata 17.0 software.Results A total of 18 studies were included,involving 4 686 patients.The incidence of taste changes is 73.46％.Totally 9 influencing factors were extracted through quantitative analysis,including oral mucositis(OR=1.98),dry mouth(OR=1.82),nausea(OR=3.05),loss of appetite(OR=2.41),use of triple antiemetic drugs(OR=2.45),gynecological cancers(OR=0.67),lung cancer(OR=0.57),paclitaxel types of chemotherapy d rugs(OR=2.86),and smoking(β=9.38).Conclusion The alteration of taste in cancer chemotherapy patients is in-fluenced by multiple factors.Nurses should regularly and dynamically assess changes in taste and implement individualized and refined nursing interventions in clinical practice to prevent or delay the development of taste alterations,thereby improving patients' quality of life and treatment adherence.

Objective To investigate the relationship between sleep disorders and coronary heart disease through big data combined with Mendelian randomization analysis.Methods Data from 2005 to 2018 National Health and Nutrition Examination Survey in the United States were utilized.Logistic regression analysis was employed to evaluate the association between sleep disorders and coronary heart disease,while analyzing relevant influencing factors.A two-sample Mendelian randomization approach was implemented using Genome-Wide Association Studies to establish causal relationships.Results Logistic regression analysis demonstrated a significant association between sleep disorders and coronary heart disease(P＜0.001),with the neutrophil-to-lymphocyte ratio serving as a mediating factor in this relationship(P＜0.001).Mendelian randomization analysis revealed a positive correlation between sleep disorders and coronary heart disease(OR=1.030,95％CI:1.01-1.04).Conclusion Sleep disorders can increase the risk of coronary heart disease by activating inflammatory factors.