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Abstract Diabetes mellitus (DM) is a chronic metabolic disease that is highly susceptible to kidney injury. Di’ao XinXueKang capsules (DXXK) is a novel Chinese herbal medicine that has been used in clinical trials for the therapy of DM and kidney disease, but the underlying pharmacological mechanism remains unclear. This study aims to integrate network pharmacology, molecular docking and in vivo experiments to explore the potential mechanisms of DXXK in the treatment of diabetic kidney injury. The chemical constituents of DXXK were extracted from the ETCM and Batman-TCM databases, and then evaluated for their pharmacological activity via the Swiss ADME platform. Multiple disease databases were searched and integrated for DM-related targets. Overlapping targets were then collected to construct a protein–protein interaction (PPI) network. KEGG and GO enrichment analyses were performed based on the Metascape database, and molecular docking was performed using AutoDock Vina software. The main components in DXXK were analyzed by HPLC. The results of network pharmacology and molecular docking were validated in an animal model of DM induced by the combination of a high-fat diet (HFD) and streptozotocin (STZ). We screened and obtained 7 ingredients and identified dioscin, protodioscin, and pseudoprotodioscin as the major components of DXXK by HPLC. A total of 2,216 DM-related pathogenic genes were obtained from DrugBank, GeneCards, OMIM, and DisGeNET databases. KEGG and GO enrichment analyses indicated that the TGF-beta signaling pathway is a critical pathway associated with DM therapy. Molecular docking revealed that the ingredients in DXXK bind to the pivotal targets TGFβ1, Smad2, and Smad3. In diabetic mice, we found that DXXK alleviated diabetic symptoms, lowered blood glucose, improved insulin tolerance, and modulated lipid metabolism. Furthermore, DXXK attenuated renal lesions and fibrosis by downregulating TGFβ1, Smad2, and Smad3. Collectively, our results suggest that DXXK has the potential to regulate glucolipid metabolism in DM, and it may serve as a viable therapeutic option for renoprotection by inhibiting of the TGF-β1/Smad2/3 pathway.

Abstract Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by motor neuron degeneration. Dysregulation of long non-coding RNAs (lncRNAs) has been implicated in ALS pathogenesis but their roles remain unclear. Previous studies found lnc-ABCA12-3 was downregulated in ALS patients. We aim to characterize the expression and function of lnc-ABCA12-3 in ALS and explore its mechanisms of action. Lnc-ABCA12-3 expression was analyzed in PBMCs from ALS patients and correlated with clinical outcomes. Effect of modulating lnc-ABCA12-3 expression was assessed in cell models using assays of apoptosis, protein homeostasis and pathway analysis. RNA pull-down and interaction studies were performed to identify lnc-ABCA12-3 binding partners. Lnc-ABCA12-3 was downregulated in ALS patients, correlating with faster progression and shorter survival. Overexpression of lnc-ABAC12-3 conferred protection against oxidative stress-induced apoptosis, while knockdown lnc-ABCA12-3 enhanced cell death. Lnc-ABCA12-3 maintained protein quality control pathways, including ubiquitination, autophagy and stress granule formation, by regulating the ubiquitin shuttle protein UBQLN1. This study identified lnc-ABCA12-3 as a novel regulatory lncRNA implicated in ALS pathogenesis by modulating cellular survival and stress responses through interactions with UBQLN1, influencing disease progression. Lnc-ABCA12-3 may influence ALS through regulating protein homeostasis pathways.

Abstract The aim of this study was to investigate the effect of zoledronic acid (ZA) on postoperative healing and functional rehabilitation in osteoporotic patients with rotator cuff (RC) injury. 96 Patients were divided into three groups according to bone mineral density and ZA use (Group A: normal BMD; Group B: osteoporosis and intravenous ZA use; Group C: osteoporosis, without ZA use). Radiologic, functional and Serological outcomes were evaluated 6 months after surgery. The functional scores in all groups exhibited significant improvement 6 months after surgery. Inter-group comparison showed that Constant Shoulder joint function Score (CSS) of group A not significantly differing from that of group B, the other indicators were significantly better than those of group B and C. There were no significant differences in shoulder forward flexion, abductive Range of Motion between group B and C. Other indicators of group B were significantly improved compared to group C. The retear rate in group C (30.3%, 10/33) was higher than group A (6.1%, 2/33) and group B (13.3%, 4/30). In conclusion, the application of ZA can significantly reduce the rate of RC retear in elderly patients with osteoporosis after surgery, which is significant for postoperative shoulder joint functional rehabilitation.

Abstract Abnormal expression of circRNAs has been observed in different types of carcinomas, and they play significant roles in the biology of these cancers. Nevertheless, the clinical relevance and functional mechanisms of the majority of circRNAs implicated in breast cancer progression remain unclear. The primary objective of our investigation is to uncover new circRNAs in breast cancer and elucidate the underlying mechanisms by which they exert their effects. The circRNA expression profile data for breast cancer and RNA-sequencing data were acquired from distinct public databases. Differentially expressed circRNAs and mRNA were identified through fold change filtering. The establishment of the competing endogenous RNAs (ceRNAs) network relied on the interplay between circular RNAs, miRNAs, and mRNAs. The hub genes were identified from the protein–protein interaction (PPI) regulatory network using the CytoHubba plugin in Cytoscape. Moreover, the expression levels and prognostic value of these hub genes in the PPI network were assessed using the GEPIA and Kaplan–Meier plotter databases. Fluorescence in situ hybridization (FISH) was used to identified the expression and intracellular localization of hsa_circ_0059665 by using the tissue microarray. Transwell analysis and CCK-8 analysis were performed to assess the invasion, migration, and proliferation abilities of breast cancer cells. Additionally, we investigated the interactions between hsa_circ_0059665 and miR-602 through various methods, including FISH, RNA-binding protein immunoprecipitation (RIP), and luciferase reporter assay. Rescue experiments were conducted to determine the potential regulatory role of hsa_circ_0059665 in breast cancer progression. A total of 252 differentially expressed circRNAs were identified. Among them, 246 circRNAs were up-regulated, while 6 circRNAs were down-regulated. Based on prediction and screening of circRNA-miRNA and miRNA-mRNA binding sites, we constructed a network consisting of circRNA-miRNA-mRNA interactions. In addition, we constructed a Protein–Protein Interaction (PPI) network and identified six hub genes. Moreover, the expression levels of these six hub genes in breast cancer tissues were found to be significantly lower. Furthermore, the survival analysis results revealed a significant correlation between low expression levels of KIT, FGF2, NTRK2, CAV1, LEP and poorer prognosis in breast cancer patients. The FISH experiment results indicated that hsa_circ_0059665 exhibits significant downregulation in breast cancer, and its decreased expression is linked to poor prognosis in breast cancer patients. Functional in vitro experiments revealed that overexpression of hsa_circ_0059665 can inhibit proliferation, migration and invasion abilities of breast cancer cells. Further molecular mechanism studies showed that hsa_circ_0059665 exerts its anticancer gene role by acting as a molecular sponge for miR-602. In our study, we constructed and analyzed a circRNA-related ceRNA regulatory network and found that hsa_circ_0059665 can act as a sponge for miR-602 and inhibit the proliferation, invasion and migration of breast cancer cells.

Abstract The aim of this study was to explore the related factors linked to the development and infectivity of tuberculosis. This was achieved by comparing the clinical characteristics of patients with pulmonary tuberculosis (TB) who tested positive in smear Mycobacterium tuberculosis tests with this who tested negative in smear mycobacterium tests but positive in sputum Gene Xpert tests. We gathered clinical data of 1612 recently hospitalized patients diagnosed with pulmonary tuberculosis who tested positive either in sputum Gene-Xpert test or sputum smear Mycobacterium tuberculosis tests. The data was collected from January 1, 2018 to August 5, 2023, at Sichuan Provincial People's Hospital. We conducted separately analyzes and comparisons of the clinical characteristics between the two groups of patients, aiming to discussed the related factors influencing the development and infectivity of tuberculosis. In comparison to the GeneXpert positive group, the sputum smear positive group exhibited a higher proportion of elderly patients (aged 75–89) and individuals classified as underweight (BMI

Abstract Even though the capability of aircraft manufacturing has improved, human factors still play a pivotal role in flight accidents. For example, fatigue-related accidents are a common factor in human-led accidents. Hence, pilots’ precise fatigue detections could help increase the flight safety of airplanes. The article suggests a model to recognize fatigue by implementing the convolutional neural network (CNN) by implementing flight trainees' face attributions. First, the flight trainees’ face attributions are derived by a method called the land-air call process when the flight simulation is run. Then, sixty-eight points of face attributions are detected by employing the Dlib package. Fatigue attribution points were derived based on the face attribution points to construct a model called EMF to detect face fatigue. Finally, the proposed PSO-CNN algorithm is implemented to learn and train the dataset, and the network algorithm achieves a recognition ratio of 93.9% on the test set, which can efficiently pinpoint the flight trainees’ fatigue level. Also, the reliability of the proposed algorithm is validated by comparing two machine learning models.

Abstract Investigate the impact of remnant cholesterol (RC) levels on carotid artery intima thickness (CIT) in type 2 diabetes mellitus (T2DM) patients. From September 2021 to September 2023, a prospective multicenter study involved 158 T2DM patients. They were divided into a higher RC group (n = 80) and a lower RC group (n = 78) based on median RC levels. Additionally, 92 healthy volunteers served as the control group. CIT, carotid media thickness (CMT), and carotid intima-media thickness (CIMT) were measured. General clinical data, lab results, CIMT, CIT, and CMT differences among the three groups were compared. Multiple regression analysis explored CIT factors in T2DM patients. 1. No significant sex, age, BMI, high-density lipoprotein cholesterol (HDL-C), T2DM duration, fasting blood glucose, or glycated hemoglobin differences were found among the groups (p > 0.05). 2. CIMT and CIT were significantly higher in T2DM than the control group (p 0.05). Multiple linear regression analysis showed RC as an influencing CIT factor in T2DM patients (β = 0.473, p = 0.005). CIT is significantly thicker in T2DM patients with higher RC than in those with lower RC, and RC is the influence factor of CIT, which suggests that more attention should be paid to the detection of RC in T2DM patients.

Abstract Researchers have investigated the potential of leveraging pre-trained language models, such as CodeBERT, to enhance source code-related tasks. Previous methodologies have relied on CodeBERT’s ‘[CLS]’ token as the embedding representation of input sequences for task performance, necessitating additional neural network layers to enhance feature representation, which in turn increases computational expenses. These approaches have also failed to fully leverage the comprehensive knowledge inherent within the source code and its associated text, potentially limiting classification efficacy. We propose CodeClassPrompt, a text classification technique that harnesses prompt learning to extract rich knowledge associated with input sequences from pre-trained models, thereby eliminating the need for additional layers and lowering computational costs. By applying an attention mechanism, we synthesize multi-layered knowledge into task-specific features, enhancing classification accuracy. Our comprehensive experimentation across four distinct source code-related tasks reveals that CodeClassPrompt achieves competitive performance while significantly reducing computational overhead.

Abstract This study addresses the growing anxiety and depression among Chinese university students by evaluating and ranking music education strategies to alleviate these issues. We integrates Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). FAHP was utilized to determine the weight of factors such as academic pressures, social relationships, and cultural norms, while fuzzy TOPSIS ranked the effectiveness of music education interventions based on these weights. The results revealed that ‘Mental health stigma’ and ‘Academic Pressures and Rigidity’ are among the highest weighted factors, significantly impacting student anxiety. ‘Music Appreciation and Music-Based Self-Care’ emerged as the most effective strategy. These results highlight the importance of direct involvement in music-related activities for improving student mental health.

Abstract Atrial fibrillation (A-fib) is the most common type of heart arrhythmia, typically treated with radiofrequency catheter ablation to isolate the heart from abnormal electrical signals. Monitoring the formation of ablation-induced lesions is crucial for preventing recurrences and complications arising from excessive or insufficient ablation. Existing imaging modalities lack real-time feedback, and their intraoperative usage is in its early stages. A critical need exists for an imaging-based lesion indexing (LSI) method that directly reflects tissue necrosis formation. Previous studies have indicated that spectroscopic photoacoustic (sPA) imaging can differentiate ablated tissues from their non-ablated counterparts based on PA spectrum variation. In this paper, we introduce a method for detecting ablation lesion boundaries using sPA imaging. This approach utilizes ablation LSI, which quantifies the ratio between the signal from ablated tissue and the total tissue signal. We enhance boundary detection accuracy by adapting a regression model-based compensation. Additionally, the method was cross-validated with clinically used intraoperative monitoring parameters. The proposed method was validated with ex vivo porcine cardiac tissues with necrotic lesions created by different ablation durations. The PA-measured lesion size was compared with gross pathology. Statistical analysis demonstrates a strong correlation (R > 0.90) between the PA-detected lesion size and gross pathology. The PA-detected lesion size also exhibits a moderate to strong correlation (R > 0.75) with local impedance changes recorded during procedures. These results suggest that the introduced PA imaging-based LSI has great potential to be incorporated into the clinical workflow, guiding ablation procedures intraoperatively.

Abstract Pre-treatment host and viral factors may affect serum ferritin levels in patients with hepatitis C virus (HCV) infection. We delineated pre-treatment factors associated with hyperferritinemia in these patients. 1682 eligible patients underwent pre-treatment assessment for serum ferritin and various host/viral factors. Univariate and multivariate logistic regression analyses were conducted to evaluate factors associated with hyperferritinemia. Multivariate logistic regression analyses revealed that age > 50 years (adjusted odds ratio [OR]: 1.38 (95% confidence interval [CI] 1.09–1.74), p = 0.008), fibrosis stage ≥ F3 (adjusted OR: 1.36 (95% CI 1.04–1.77), p = 0.02), fibrosis index based on four parameters (FIB-4) > 3.25 (adjusted OR: 1.46 (95% CI 1.11–1.92), p = 0.01), presence of metabolic dysfunction-associated steatotic liver disease (MASLD) (adjusted OR: 1.43 (95% CI 1.21–1.76), p = 0.001), and alanine transaminase (ALT) > 2 folds upper limit of normal (ULN) (adjusted OR: 2.87 (95% CI 2.20–3.75), p

Abstract Plants are affected by many environmental factors during their various stages of growth, among which salt stress is a key factor. WRKY transcription factors play important roles in the response to stress in plants. In this study, SmWRKY40 from eggplant (Solanum melongena L.) was found to belong to the subfamily of WRKY transcription factor group II, closely related to the evolution of wild tomato ScWRKY40 (Solanum chilense). The expression of SmWRKY40 could be induced by several abiotic stresses (drought, salt, and high temperature) and ABA to different degrees, with salt stress being the most significant. In Arabidopsis thaliana, the seed germination rate of SmWRKY40 overexpression seedlings was significantly higher than those of the wild type under high concentrations of NaCl and ABA, and root elongation of overexpression lines was also longer than wild type under NaCl treatments. SmWRKY40 overexpression lines were found to enhance Arabidopsis tolerance to salt with lower ROS, MDA, higher soluble protein, proline accumulation, and more active antioxidant enzymes. The expression level of genes related to stress and ABA signaling displayed significant differences in SmWRKY40 overexpression line than that of WT. These results indicate that SmWRKY40 regulates ABA and salt stress responses in Arabidopsis.

Abstract Adverse events (AEs) are a significant concern for healthcare systems. However, it is difficult to evaluate their influence because of the complexity of various medical services. This study aimed to assess the influence of AEs on the outcomes of hospitalized patients using a diagnosis-related group (DRG) database. We conducted a case–control study of hospitalized patients at a multi-district tertiary hospital with 2200 beds in China, using data from a DRG database. An AE refers to an unintended physical injury caused or contributed to by medical care that requires additional hospitalization, monitoring, treatment, or even death. Relative weight (RW), a specific indicator of DRG, was used to measure the difficulty of diagnosis and treatment, disease severity, and medical resources utilized. The primary outcomes were hospital length of stay (LOS) and hospitalization costs. The secondary outcome was discharge to home. This study applied DRG-based matching, Hodges–Lehmann estimate, regression analysis, and subgroup analysis to evaluate the influence of AEs on outcomes. Two sensitivity analyses by excluding short LOS and changing adjustment factors were performed to assess the robustness of the results. We identified 2690 hospitalized patients who had been divided into 329 DRGs, including 1345 patients who experienced AEs (case group) and 1345 DRG-matched normal controls. The Hodges–Lehmann estimate and generalized linear regression analysis showed AEs led to prolonged LOS (unadjusted difference, 7 days, 95% confidence interval [CI] 6–8 days; adjusted difference, 8.31 days, 95% CI 7.16–9.52 days) and excess hospitalization costs (unadjusted difference, $2186.40, 95% CI: $1836.87-$2559.16; adjusted difference, $2822.67, 95% CI: $2351.25-$3334.88). Logistic regression analysis showed AEs were associated with lower odds of discharge to home (unadjusted odds ratio [OR] 0.66, 95% CI 0.54–0.82; adjusted OR 0.75, 95% CI 0.61–0.93). The subgroup analyses showed that the results for each subgroup were largely consistent. LOS and hospitalization costs increased significantly after AEs in complex diseases (RW ≥ 2) and in relation to high degrees of harm subgroups (moderate harm and above groups). Similar results were obtained in sensitivity analyses. The burden of AEs, especially those related to complex diseases and severe harm, is significant in China. The DRG database serves as a valuable source of information that can be utilized for the evaluation and management of AEs.

Abstract To explore the clinical characteristics of patients infected with SARS-CoV-2 nationwide, especially the effect factors of asymptomatic infection and disappearance of clinical symptoms. A total of 66,448 COVID-19 patients in China who have been diagnosed by nucleic acid test or rapid antigen test were surveyed online (December 24, 2022 to January 16, 2023). Our cross-sectional study used descriptive analyses and binary Logistics regression model to assess the correlation between the clinical characteristics and relative factors, including age, gender, pre-existing conditions, reinfection, vaccination and treatment. A total of 64,515 valid questionnaires were collected. Among included participants, 5969 of which were asymptomatic. The symptoms were mainly upper respiratory symptoms, including dry and itchy throat (64.16%), sore throat (59.95%), hoarseness (57.90%), nasal congestion (53.39%). In binary Logistics regression model, we found that male, no pre-existing conditions, reinfection and vaccination have positive correlations with the appearance of asymptomatic COVID-19 patients. In Cox proportional-hazards regression model, considering all clinical symptoms disappeared in 14 days as outcome, we found that ≤ 60 years old, male, no pre-existing conditions, vaccination and adopted treatment have positive correlations with rapid amelioration of clinical symptoms in COVID-19 patients. The clinical symptoms of the participants were mainly upper respiratory symptoms which were according with the infection of Omicron variant. Factors including age, gender, pre-existing conditions and reinfection could influence the clinical characteristics and prognosis of COVID-19 patients. Importantly, vaccination has positive significance for the prevention and treatment of COVID-19. Lastly, the use of Chinese medicine maybe beneficial to COVID-19 patients, however, reasonable guidance is necessary.