Objective To explore the factors affecting the quality of psychological assistance hotline connections in Shaanxi Province, and to provide a basis for optimizing services. Methods A total of 149 calls with suicidal tendencies were included from January to March 2022, and data were collected by 31 trained assessors through standardized questionnaires (general information, suicide risk, emotional intensity, and wiring characteristics). Results The results showed that 56.38% of the callers were female, with age groups concentrated between ≤ 18 years old (29.53%) and 19-34 years old (43.62%). The call duration was mainly between 31 and 45 minutes (50.34%). Operators conducted a suicide risk assessment on the callers, with 38.9% having a comprehensive assessment, 38.9% having an incomplete assessment, and 22.1% having no assessment. The main mental disorders of the callers were depression (48.32%), anxiety (15.44%), and bipolar disorder (14.77%), with 25.50% having comorbidities of ≥ 2 disorders. Emotional scores were as follows: depression (4.11 ± 0.76), sadness (3.97 ± 1.03), and despair (3.78 ± 1.05). There were significant differences in depression, anger, despair, and sadness among the callers with different levels of danger (t=4.79, 3.35, 15.79, 4.24, all P<0.05). Women had higher levels of fear than men (t=3.10, P<0.01). The longer the call duration, the higher the level of despair (t=5.66, P<0.01). Multiple regression analysis showed that incomplete suicide risk assessment by operators (B=-2.36), general procedures for operators' connections (B=5.44), and technical factors (B=2.01) significantly affected the quality of psychological assistance hotlines (all P<0.05). Conclusion Callers with suicidal tendencies generally have serious mental and psychological problems and prominent negative emotions. Strengthening the suicide risk assessment ability of operators and standardizing processes and service attitudes are key to improving the quality of psychological assistance hotlines.

Objective To explore the relationship between intestinal flora imbalance and pulmonary function in patients with chronic obstructive pulmonary disease (COPD), and to analyze the related influencing factors. Methods A total of 310 patients with COPD who were admitted to Air Force Military Medical University Tangdu Hospital from June 2022 to December 2024 were retrospectively analyzed. Based on intestinal flora status, the enrolled patients were classified into imbalance group (n=83) and non-imbalance group (n=227). Logistic regression analysis was conducted to analyze the independent related factors of intestinal flora imbalance in COPD patients. Based on the above factors, a prediction model was constructed, and ROC curve analysis model was applied to analyze the predictive value of the model on intestinal flora imbalance. Results Logistic regression analysis revealed that age, IL-6, albumin, pulmonary function, long-term bed rest and long-term use of antibiotics were related to intestinal flora imbalance in COPD patients (all P<0.05). ROC results of the Logistic prediction model showed that the area under the curve, sensitivity, specificity and 95%CI were 0.961, 0.880, 0.996 and 0.932-0.989 respectively. Conclusion The intestinal flora imbalance in patients with COPD is closely related to lung function, age, inflammatory status, nutritional indicators, activity ability and antibiotic use.

ObjectiveTo analyze the epidemiological and etiological characteristics of a cluster of human metapneumovirus (HMPV) infection in a kindergarten in Gongshu District of Hangzhou City in May 2024, and to provide reference for the prevention and control of similar outbreaks. MethodsAn on-site investigation was conducted using an epidemiological case investigation form. Throat swab specimens collected from cases were screened for 13 respiratory pathogens using real-time fluorescent polymerase chain reaction (PCR). For HMPV nucleic acid positive specimens, the F gene of HMPV was used as the target gene for amplification and sequencing. The sequencing results were then compared with sequences in GenBank database to determine the virus subtypes and perform phylogenetic analyses. ResultsThe outbreak occurred in a kindergarter junior class with a total of 28 preschoolers and 3 teachers and childcare workers. A total of 11 cases (10 preschoolers and 1 teacher) were identified, including 8 male cases and 3 female cases. Clinical manifestations included fever in all 11 cases (100.00%), cough in 8 cases (72.72%), catarrhal symptoms in 4 cases (36.36%), and headache in 3 cases (27.27%). All symptoms were mild, and no severe cases were observed. A total of 11 throat swab samples were collected. Real-time fluorescent PCR test results showed that 3 samples were positive for HMPV nucleic acid, 2 samples were positive for both HMPV and Streptococcus pneumoniae, and 1 sample was positive for both HMPV and rhinovirus. The sequences of the 6 HMPV nucleic acid positive specimens were amplified and analyzed using specific primers, and all were determined to be HMPV subtype A2b. The F gene fragment sequence showed the highest similarity to PV081665.1/Brazil/2024 (99.65%), and also exhibited high similarity to PP683455.1/Indonesia/2021 (99.48%), PV016275.1/Beijing/2024 (99.31%), and PV052230.1/USA/2024 (99.13%). ConclusionThis cluster of acute respiratory tract infection was caused by HMPV subtype A2b, with co-infection of rhinovirus and Streptococcus pneumoniae. The F gene fragment sequences of the HMPV in this outbreak were highly homologous to those of the A2b strains isolated from Brazil, Beijing, Indonesia, and the the United States.

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.

Objective To explore the relationship between osteoporosis and carotid atherosclerosis in patients with coronary heart disease aged≥60 years and analyze prevention suggestions. Methods The clinical data of 380 patients with coronary heart disease aged≥60 years who underwent various examinations in the hospital between April 2024 and April 2025 were retrospectively analyzed. According to the bone mineral density (BMD) classification criteria, the patients were divided into osteoporosis group and non-osteoporosis group. The differences in general data and carotid atherosclerosis-related indicators were compared between osteoporosis group and non-osteoporosis group. Pearson method was used to analyze the correlation between carotid atherosclerosis indicators and clinical indicators in patients with coronary heart disease aged≥60 years. According to the IMT detection thickness in patients with coronary heart disease and osteoporosis aged≥60 years were divided into IMT thickening group and IMT non-thickening group and between plaque group and non-plaque group, and the differences in BMD and bone metabolism indicators were compared. Binary logistics analysis was adopted to analyze the risk factors of IMT thickening and carotid plaque formation in patients with coronary heart disease≥60 years old. Results Age and duration of osteoporosis group TC、LDL-C、CTX、 Carotid artery IMT and carotid atherosclerosis degree were higher than those in the non osteoporosis group, the difference was statistically significant (P<0.05). BMI, OPG, OCN, 25 (OH) D, BMD, carotid artery elasticity coefficient were lower than those in the non osteoporosis group, the difference was statistically significant (P<0.05). Carotid IMT, carotid atherosclerosis degree, and carotid elasticity coefficient were significantly correlated with age, course of disease, TC, LDL-C, CTX, BMI, OPG, OCN, BMD, and 25 (OH) D of coronary heart disease patients ≥60 years old (P<0.05). OPG, OCN, BMD and 25(OH)D in IMT thickening group and plaque group were lower compared to IMT non-thickening group and non-plaque group (P<0.05) while CTX was significantly higher than that in IMT non-thickening group and non-plaque group (P<0.05). Binary logistics regression analysis showed that OPG, OCN, BMD, 25(OH)D and CTX were associated with IMT thickening in patients with coronary heart disease and osteoporosis aged≥60 years (P<0.05). OPG, OCN and BMD were associated with carotid plaque formation in patients with coronary heart disease complicated with osteoporosis aged≥60 years (P<0.05). Conclusion There is a significant correlation between osteoporosis and arteriosclerosis in patients with coronary heart disease aged≥60 years. As the bone mass decreases, the manifestations of arteriosclerosis become become more and more obvious, which needs attention and prevention.

This study employed the "disease-medicine-dose" pattern to mine the medication rules of traditional Chinese medicine(TCM) prescriptions containing Astragali Radix in ancient Chinese medical books, aiming to provide a scientific basis for the clinical application of Astragali Radix and the development of new medicines. The TCM prescriptions containing Astragali Radix were retrieved from databases such as Chinese Medical Dictionary and imported into Excel 2020 to construct the prescription library. Statical analysis were performed for the prescriptions regarding the indications, syndromes, medicine use frequency, herb effects, nature and taste, meridian tropism, dosage forms, and dose. SPSS statistics 26.0 and IBM SPSS Modeler 18.0 were used for association rules analysis and cluster analysis. A total of 2 297 prescriptions containing Astragali Radix were collected, involving 233 indications, among which sore and ulcer, consumptive disease, sweating disorder, and apoplexy had high frequency(>25), and their syndromes were mainly Qi and blood deficiency, Qi and blood deficiency, Yin and Yang deficiency, and Qi deficiency and collateral obstruction, respectively. In the prescriptions, 98 medicines were used with the frequency >25 and they mainly included Qi-tonifying medicines and blood-tonifying medicines. Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Ginseng Radix et Rhizoma, Atractylodis Macrocephalae Rhizoma, and Citri Reticulatae Pericarpium were frequently used. The medicines with high frequency mainly have warm or cold nature, and sweet, pungent, or bitter taste, with tropism to spleen, lung, heart, liver, and kidney meridians. In the treatment of sore and ulcer, Astragali Radix was mainly used with the dose of 3.73 g and combined with Glycyrrhizae Radix et Rhizoma to promote granulation and heal up sores. In the treatment of consumptive disease, Astragali Radix was mainly used with the dose of 37.30 g and combined with Ginseng Radix et Rhizoma to tonify deficiency and replenish Qi. In the treatment of sweating disorder, Astragali Radix was mainly used with the dose of 3.73 g and combined with Glycyrrhizae Radix et Rhizoma to consolidate exterior and stop sweating. In the treatment of apoplexy, Astragali Radix was mainly used with the dose of 7.46 g and combined with Glycyrrhizae Radix et Rhizoma to dispell wind and stop convulsions. Astragali Radix can be used in the treatment of multiple system diseases, with the effects of tonifying Qi and ascending Yang, consolidating exterior and stopping sweating, and expressing toxin and promoting granulation. According to the manifestations of different diseases, when combined with other medicines, Astragali Radix was endowed with the effects of promoting granulation and healing up sores, tonifying deficiency and Qi, consolidating exterior and stopping sweating, and dispelling wind and replenishing Qi. The findings provide a theoretical reference and a scientific basis for the clinical application of Astragali Radix and the development of new medicines.
Drugs, Chinese Herbal/history* ; Humans ; Medicine, Chinese Traditional/history* ; History, Ancient ; Astragalus Plant/chemistry* ; China ; Astragalus propinquus

Objective:To investigate effective strategies to reduce the high risk of recurrence after allogeneic hematopoietic stem cell transplantation(allo-HSCT)in patients with minimal residual disease(MRD)-positive B-lineage acute lymphoblastic leukemia(B-ALL).Methods:A retrospective analysis was performed for ten B-ALL patients with positive MRD before transplantation at our center from November 2022 to November 2024.There were four male patients and six female patients,with a median age of 30(7-56)years.Of all patients,four received transplantation from unrelated donors,and six received haploidentical transplantation from relatives.All ten patients received blinatumomab(28 μg/day for 14 days for patients≥45 kg;5 μg/m2/day for 14 days for patients<45 kg)and were bridged to the conditioning regimen for allo-HSCT within 7 days.Results:After treatment with blinatumomab,all ten patients achieved the clearance of MRD.After allo-HSCT,100%of the patients achieved donor hematopoietic reconstitution.The median time to neutrophil reconstitution was 12(9-22)days,and the median time to platelet reconstitution was 13.5(9-22)days.As of January 2025,the median observation time was 14(2-26)months;of all patients,two experienced recurrence,and one had positive MRD again,with a recurrence rate of 20%.Among the ten patients,nine survived and one died of disease recurrence.One patient achieved complete re-mission again after chimeric antigen receptor T-cell(CAR-T)therapy following recurrence,and the patient with positive MRD achieved the clearance of MRD again after interleukin-2 treatment;both patients were currently alive.During treatment,one patient developed cytokine release syndrome,one patient was comorbid with SARS-CoV-2 infection,one patient had herpes zoster and viral encephalitis,three patients developed grade Ⅰ-Ⅱ acute graft-versus-host disease,and four patients developed chronic graft-versus-host disease;no transplantation-associated thrombotic microangiopathy was observed.Conclusion:For patients with MRD-positive B-ALL,blinatumomab as a bridge therapy for allo-HSCT can significantly reduce recurrence after transplantation,with fewer complica-tions that are easy to control.Multicenter randomized controlled clinical studies can be performed to further verify its efficacy and safety.

Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a complex disease that is often accompanied by mental health disorders. However, the potential mechanisms underlying the heterogeneous clinical presentation of CP/CPPS remain uncertain. This study analyzed widely targeted metabolomic data of expressed prostatic secretions (EPS) and plasma to reveal the underlying pathological mechanisms of CP/CPPS. A total of 24 CP/CPPS patients from The Second Nanning People's Hospital (Nanning, China), and 35 asymptomatic control individuals from First Affiliated Hospital of Guangxi Medical University (Nanning, China) were enrolled. The indicators related to CP/CPPS and psychiatric symptoms were recorded. Differential analysis, coexpression network analysis, and correlation analysis were performed to identify metabolites that were specifically altered in patients and associated with various phenotypes of CP/CPPS. The crucial links between EPS and plasma were further investigated. The metabolomic data of EPS from CP/CPPS patients were significantly different from those from control individuals. Pathway analysis revealed dysregulation of amino acid metabolism, lipid metabolism, and the citrate cycle in EPS. The tryptophan metabolic pathway was found to be the most significantly altered pathway associated with distinct CP/CPPS phenotypes. Moreover, the dysregulation of tryptophan and tyrosine metabolism and elevation of oxidative stress-related metabolites in plasma were found to effectively elucidate the development of depression in CP/CPPS. Overall, metabolomic alterations in the EPS and plasma of patients were primarily associated with oxidative damage, energy metabolism abnormalities, neurological impairment, and immune dysregulation. These alterations may be associated with chronic pain, voiding symptoms, reduced fertility, and depression in CP/CPPS. This study provides a local-global perspective for understanding the pathological mechanisms of CP/CPPS and offers potential diagnostic and therapeutic targets.
Humans ; Male ; Prostatitis/blood* ; Adult ; Pelvic Pain/blood* ; Metabolomics ; Prostate/metabolism* ; Middle Aged ; Chronic Pain/blood* ; Metabolome ; Case-Control Studies ; Tryptophan/blood* ; Depression/blood* ; Oxidative Stress/physiology* ; Chronic Disease ; Lipid Metabolism/physiology*

OBJECTIVES: To investigate the effects of methylenetetrahydrofolate reductase (MTHFR) rs1801133 and γ-glutamyl hydrolase (GGH) rs11545078 gene polymorphisms on plasma concentrations and toxicity following high-dose methotrexate (MTX) therapy in children with acute lymphoblastic leukemia (ALL). METHODS: Children with ALL treated at the Xuzhou Children's Hospital of Xuzhou Medical University from January 2021 to April 2024 were selected for this study. Genotypes of MTHFR rs1801133 and GGH rs11545078 were determined using multiplex polymerase chain reaction. MTX plasma concentrations were measured by enzyme-multiplied immunoassay technique, and toxicity was graded according to the Common Terminology Criteria for Adverse Events version 5.0. The relationships between MTHFR rs1801133 and GGH rs11545078 genotypes and both MTX plasma concentrations and associated toxicities were analyzed. RESULTS: In the low-risk ALL group, the MTHFR rs1801133 genotype was associated with increased MTX plasma concentrations at 72 hours (P<0.05). In the intermediate- to high-risk group, the MTHFR rs1801133 genotype was associated with increased MTX plasma concentrations at 48 hours (P<0.05), and the GGH rs11545078 genotype was associated with increased MTX plasma concentrations at 48 hours (P<0.05). In the intermediate- to high-risk group, the MTHFR rs1801133 genotype was associated with the occurrence of reduced hemoglobin (P<0.05), and the GGH rs11545078 genotype was associated with the occurrence of thrombocytopenia (P<0.05). CONCLUSIONS Detection of MTHFR rs1801133 and GGH rs11545078 genotypes can be used to predict increased MTX plasma concentrations and the occurrence of toxic reactions in high-dose MTX treatment of ALL, enabling timely interventions to enhance safety.
Humans ; Methotrexate/toxicity* ; Methylenetetrahydrofolate Reductase (NADPH2)/genetics* ; Precursor Cell Lymphoblastic Leukemia-Lymphoma/blood* ; Male ; Female ; Child ; Child, Preschool ; gamma-Glutamyl Hydrolase/genetics* ; Antimetabolites, Antineoplastic/adverse effects* ; Infant ; Polymorphism, Genetic ; Adolescent ; Genotype ; Polymorphism, Single Nucleotide