ObjectiveTo explore the mechanism of Yishen Qubi Tongluo Formula （益肾祛痹通络方， YQTF） in the treatment of rheumatoid arthritis（RA）. MethodsNetwork pharmacology was employed to retrieve and screen the active components and potential targets of YQTF as well as RA-related targets using databases including TCMSP， BATMAN， ETCM and GEO. The intersection of targets related to active components and RA-related targets was identified， and a protein-protein interaction （PPI） network was constructed. Gene Ontology （GO） functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis were performed， and a drug-active component-common target network of YQTF in the treatment of RA was established. The core components of YQTF were molecularly docked with key targets. Human rheumatoid arthritis synovial fibroblast cell line MH7A was divided into blank group， model group， methotrexate group and YQTF group. The blank group was cultured with 10% fetal bovine serum， while the other three groups were stimulated with 10 μg/L of recombinant human tumor necrosis factor-α （TNF-α） for 24 h to establish the RA cell model. On this basis， the methotrexate group was treated with methotrexate suspension at a concentration of 20 μmol/L， and the YQTF group was treated with 10% YQTF-medicated serum. After 48 h of intervention， the levels of TNF-α and interleukin-17A（IL-17A）contents in cell supernatants were detected by enzyme-linked immunosorbent assay （ELISA）， and mRNA expressions of phosphatidylinositol 3-kinase（PI3K）， protein kinase B（AKT） and mammalian target of rapamycin（mTOR） were detected by real-time quantitative polymerase chain reaction （RT-qPCR）. ResultsNetwork pharmacological analysis identified 209 active components and 583 potential target genes of YQTF， as well as 818 RA-related targets. A total of 29 common targets were obtained from the intersection of drug-related targets and RA-related targets. Quercetin，β-sitosterol， kaempferol， stigmasterol and luteolin were the core active components of YQTF for the treatment of RA， while matrix metalloproteinase-9 （MMP9）， prostaglandin-endoperoxide synthase 2 （PTGS2）， Toll-like receptor 4 （TLR4）， tumor protein p53 （TP53） and transcription factor AP-1 subunit JUN were the key targets. The GO and KEGG pathway enrichment analysis showed that the involved biological processes and pathways were mainly associated with antioxidant responses， PI3K-AKT signaling pathway and Toll-like receptor （TLR） signaling pathway. Molecular docking results showed that MMP9 and PTGS2 exhibited high binding affinities with quercetin， β-sitosterol， kaempferol， stigmasterol and luteolin； TLR4 exhibited high binding activities with β-sitosterol， stigmasterol and luteolin； and TP53 showed high binding affinity with luteolin. The results of cell experiments showed that compared with the control group， the contents of TNF-α and IL-17A as well as the mRNA expressions of AKT and mTOR in the model group significantly increased （P＜0.05 or P＜0.01）. Compared with the model group， all the above indicators significantly decreased in the YQTF group， while the contents of TNF-α and the mRNA expression of AKT significantly decreased in the methotrexate group （P＜0.05 or P＜0.01）. ConclusionThe mechanism of YQTF in the treatment of RA may be associated with reducing inflammatory cytokine secretion and inhibiting the activation of the PI3K-AKT-mTOR signaling pathway.

Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

Background: Obesity is a well-known risk factor for chronic kidney disease and its progression. However, the impact of obesity on the renal function of the elderly population is uncertain. We investigated the association between obesity and renal outcomes in the elderly. Methods: We analyzed 130,504 participants from the Korean National Health Insurance Service-Senior cohort. Obesity was classified according to body mass index (BMI), sex-specific waist circumference (WC), and the presence of metabolic syndrome. The primary outcome was renal function decline, defined as a decline in the estimated glomerular filtration rate (eGFR) of at least 50% from baseline or new-onset end-stage renal disease. Results: During a follow-up period of 559,531.1 person-years (median, 4.3 years), 2,486 participants (19.0%; incidence rate of 4.44 per 1,000 person-years) showed renal function decline. A multivariate Cox proportional hazards model revealed that BMI/WC was not associated with renal function decline. However, the group with metabolic syndrome had a significantly increased risk of renal function decline compared to the group without metabolic syndrome (adjusted hazard ratio [HR], 1.24; 95% confidence interval [CI], 1.13–1.36). Compared with the non-metabolic syndrome group, the adjusted HRs (95% CI) for participants with one through five components were 0.96 (0.84–1.11), 1.10 (0.96–1.27), 1.24 (1.06–1.45), 1.37 (1.12–1.66), and 1.99 (1.42–2.79), respectively (p for trend < 0.001). Conclusion In elderly Korean adults, metabolic syndrome and the number of its components were associated with a higher risk of renal function decline, but BMI or WC was not significant.

Effective symptom management can alleviate the physical and psychological distress experienced by patients with cancer, improve quality of life, and contribute to treatment adherence and improve clinical outcomes. However, most existing guidelines are developed for healthcare professionals, and patients and the public have limited access to standardized and comprehensible guidance on symptom management. To address this gap and to facilitate effective communication and shared decision-making, this study proposes the development of a patient version of the cancer symptom management guideline. The development process will adhere to the methodological framework recommended by the Guidelines International Network and the World Health Organization. The GRADE approach will be employed to assess the certainty of evidence and to formulate recommendations. In addition, the process will be informed by the Appraisal of Guidelines for Research and Evaluation Ⅱ (AGREE Ⅱ) instrument and the Reporting Items for Practice Guidelines in Healthcare-Public or Patient Versions of Guidelines (RIGHT-PVG). This protocol outlines the establishment of the guideline working group, the identification and prioritization of key questions, evidence retrieval and appraisal, and the formulation of recommendations, with the aim of ensuring methodological rigor and transparency in the development of the patient guideline and providing methodological reference for similar guideline initiatives.

Traditional Chinese medicine contains a variety of volatile components （VOCs） such as terpenes and aliphatics, which have significant pharmacological activities, and are commonly analyzed by gas chromatography （GC） and gas chromatography-mass spectrometry （GC-MS）. Although the separation ability is strong, the samples need to be pre-treated and the analysis time is long. In recent years, the combination of GC and ion migration spectrometry （IMS） has been widely used in the academic community. The combination of high separation ability of GC and rapid reaction ability of IMS has the advantages of no sample pretreatment, fast analysis time, low detection limit and simple operation. It is increasingly used in traditional Chinese medicine research. The working principle of GC-IMS was introduced, the application in VOCs research of traditional Chinese medicine was summarized, and the future development direction was prospected in this paper.

Cremastrae Pseudobulbus Pleiones Pseudobulbus is a Chinese medicinal material used for clearing heat， detoxicifying， resolving phlegm， and dissipating nodules. It is derived from Cremastra appendiculata， Pleione bulbocodioides， or Pleione yunnanensis， as recorded in the 2025 edition of the Pharmacopoeia of the People′s Republic of China， with the former known as Maocigu and the latter two known as Bingqiuzi. Current antitumor studies mainly focus on polysaccharides， water-extracted alcohol-precipitated fractions， and purified extracts of C. appendiculata. Structurally characterized glucomannans suppress breast and liver tumor xenografts and exhibit immunomodulatory effects. The water-extracted alcohol-precipitated fractions inhibit tumor angiogenesis in hepatoma-bearing mice. A purified C. appendiculata extract standardized to five phenanthrene and bibenzyl constituents induces mitochondrial apoptosis in hepatocellular carcinoma cells. Reported pharmacological effects involve cell-cycle regulation， apoptosis， epithelial-mesenchymal transition， angiogenesis， autophagy， and the tumor immune microenvironment， with phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin （PI3K/Akt/mTOR）， Wnt/β-catenin， and Janus kinase 2/signal transducer and activator of transcription 3 （JAK2/STAT3） signaling pathways being the major mechanism links. Quality evaluation of Cremastrae Pseudobulbus Pleiones Pseudobulbus has progressed from single-marker assays to an integrated approach involving botanical authentication， chromatographic fingerprinting， multicomponent analysis， and evaluation of associations between blood-absorbed constituents and antitumor effects. Militarine and dactylorhin A can be used for botanical identification and batch evaluation， and in vivo exposure data from related orchids are concentrated on militarine. Quantitative associations between these constituents and antitumor effects remain to be established. Clinical evidence mainly focuses on formula-based applications and expert experience. Comparative antitumor data in hepatoma models are available for the commercial specifications of Maocigu and Bingqiuzi， whereas parallel evaluations of pharmacological effects， safety windows， and drug interactions among the three official botanical origins remain insufficient. The major limitations are the incomplete standardization of botanical origins and preparations and the lack of quantitative links among quality markers， systemic exposure， antitumor effects， and toxicity endpoints， which constrain reproducible pharmacological evaluation and clinical translation of Cremastrae Pseudobulbus/Pleiones Pseudobulbus.

With the rapid development of sequencing technologies, the detection of alternative polyadenylation (APA) in mammals has become more precise. APA precisely regulates gene expression by altering the length and position of the poly(A) tail, and is involved in various biological processes such as disease occurrence and embryonic development. The research on APA in mammals mainly focuses on the following aspects:(1) identifying APA based on transcriptome data and elucidating their characteristics; (2) investigating the relationship between APA and gene expression regulation to reveal its important role in life regulation;(3) exploring the intrinsic connections between APA and disease occurrence, embryonic development, differentiation, and other life processes to provide new perspectives and methods for disease diagnosis and treatment, as well as uncovering embryonic development regulatory mechanisms. In this review, the classification, mechanisms and functions of APA were elaborated in detail and the methods for APA identifying and APA data resources based on various transcriptome data were systematically summarized. Moreover, we epitomized and provided an outlook on research on APA, emphasizing the role of sequencing technologies in driving studies on APA in mammals. In the future, with the further development of sequencing technology, the regulatory mechanisms of APA in mammals will become clearer.

Objective To develop and evaluate a diagnostic model for autoimmune liver disease(AILD)using clinical indicators.Methods A total of 181 AILD patients(AILD group)diagnosed in the Department of Gastroenterology or Rheumatology and Immunology,the First Medical Center of Chinese PLA General Hospital,from June 2019 to February 2024,133 patients with hepatitis B virus cirrhosis(HBVC)(HBVC group),and 100 healthy individuals(HC group)were included in the study cohort for retrospective analysis.Clinical data,blood routine tests,and biochemical indicators were compared among the groups.Propensity score matching was used to balance the effects of factors such as gender and age.Multivariate logistic regression analysis was applied to identify characteristic indicators for AILD.Receiver operating characteristic(ROC)curves were used to evaluate the diagnostic efficacy of single and combined indicators,and the optimal diagnostic model for AILD was constructed.The Hosmer-Lemeshow test was performed to assess the model's goodness-of-fit,while ROC analysis was employed to evaluate the predictive validity.Additionally,an independent validation cohort,including 91 AILD patients(AILD validation group),82 HBVC patients(HBVC validation group),and 40 healthy individuals(HC validation group)who visited during the same period,was used to validate the diagnostic model.False-positive and false-negative rates were calculated to assess the diagnostic efficacy and clinical utility of the model.Results The age and the proportion of male patients in AILD and HBVC groups were higher than those in HC group,and the proportion of male patients in AILD group was higher than in HBVC group,the differences were statistically significant(P＜0.05).Prior to matching,compared with HC group,HBVC group and AILD group had significantly lower levels of hemoglobin(HB),red blood cell count(RBC),white blood cell count(WBC),platelet count(PLT),and albumin(ALB)(P＜0.05),but significantly higher levels of alanine aminotransferase(ALT),aspartate aminotransferase(AST),alkaline phosphatase(ALP),gamma-glutamyl transferase(GGT),total bilirubin(TBIL),and direct bilirubin(DBIL)(P＜0.05).Compared with HBVC group,AILD group had significantly higher levels of WBC,PLT,ALB,ALP,and GGT(P＜0.05 or P＜0.001)but significantly lower levels of TBIL and DBIL(P＜0.001).After maching,compared with HC group,AILD group still had significantly lower levels of HB,RBC,WBC,PLT,and ALB,but significantly higher levels of ALT,AST,ALP,GGT,TBIL,and DBIL(P＜0.05).Compared with HBVC group,AILD group had significantly higher levels of HB,RBC,WBC,PLT,ALB,ALT,ALP,and GGT,but significantly lower levels of DBIL(P＜0.05).ROC analysis results showed that AST,GGT,ALP,and DBIL had high predictive values for differentiating AILD from HC(AUC=0.843,0.804,0.802,0.773),while PLT,WBC,GGT,and ALP had high predictive values for differentiating AILD from HBVC(AUC=0.780,0.739,0.729,0.702).For distinguishing AILD from HC,the combined model of AST,ALP,and DBIL(Model e)had an AUC of 0.887,with a sensitivity of 82.2％,and a specificity of 94.7％.For distinguishing AILD from HBVC,the combined model of ALP,GGT,and PLT(Model D)had an AUC of 0.829,with a sensitivity of 78.5％and a specificity of 80.6％.Conclusions The combined diagnostic model based on AST,ALP,and DBIL can effectively differentiate healthy individuals without liver diseases from AILD patients,while the combined diagnostic model based on PLT,ALP,and GGT can effectively distinguish HBVC from AILD patients.

Objective:To investigate the clinical predictive value of Ki67 proliferation index combined with preoperative serum Ctn for postoperative biochemical cure of medullary thyroid carcinoma (MTC) .Methods:Clinical data were collected from Dec. 2008 to Dec. 2024 from 90 patients with surgically confirmed MTC at China-Japan Union Hospital of Jilin University. The optimal cut-off value for preoperative Ctn prediction of biochemical cure (171.18pg/mL) was determined by the ROC curve; the Ki67 proliferation index cut-off value was adopted from the international MTC grading system standard (5%). Patients were divided into three groups based on the above cutoff values: double-low group (Ki67 <5% and Ctn <171.18pg/mL, n=23), single-high group (Ki67 ≥5% and Ctn <171.18pg/mL or Ki67 <5% and Ctn ≥171.18pg/mL, n=49), and double-high group (Ki67 ≥5% and Ctn ≥171.18pg/mL, n=18). The Kaplan-Meier method (Log-Rank and Trend test) was used to compare the differences in biochemical cure rates between groups, and the Cox proportional risk model was used to analyze the risk factors affecting biochemical cure. Results:The correlation between preoperative Ctn and Ki67 proliferation index was not significant. The three groups differed significantly in gender, tumor distribution, tumor size, vascular invasion, N stage, TNM stage, and biochemical cure ( P<0.05), with the double-high group being significantly associated with larger tumors, later N stage and TNM stage, and lower biochemical cure ( P<0.001). Kaplan-Meier analysis showed that the biochemical cure rate in the double-high, single-high, and double-low groups showed a stepwise improvement.Cox univariate analysis showed that tumor size, N stage, TNM stage, preoperative Ctn, and Ki67 combined with Ctn were risk factors for failure to biochemically cure; multivariate analysis confirmed that the double-high group was an independent risk factor ( P<0.05). In the single-high group, the biochemical cure rate of patients in the low Ki67-high Ctn group was lower than that of the high Ki67-low Ctn group and more malignant. Ki67 had less effect on biochemical cure and disease-free survival at the low Ctn level, and Ki67 was an independent risk factor for failure to biochemically cure at the high Ctn level ( P=0.023) and was significantly associated with disease-free survival ( P=0.004) . Conclusions:Serum Ctn is more sensitive than Ki67 index in predicting biochemical cure after MTC, and the correlation between the two was weak. Ki67 proliferation index alone has limited prognostic value, but combines with preoperative Ctn significantly optimize the prognostic assessment of patients.The role of Ki67 index varied at different Ctn levels.

Objective:To explore a method that can improve the detecting accuracy for faults of magnetic resonance(MR)through diagnostic technique based on firefly algorithm for fault of MR coil of magnetic resonance imaging(MRI)equipment with superconductivity,so as to enhance the performance and reliability of MRI equipment.Methods:A diagnosis technique for fault of MR coils in MRI equipment with superconductivity was proposed.Wavelet basis function was used to decompose initial vibration signals,and they were separated into resonance components with high-frequency and that with low-frequency,so as to enhance signal purity.The signal entropy value of deconvolution became the minimum value through iteratively adjusted the filter's coefficients,and identified the optimal system function of inverse filter,thus,to effectively recover the resonance characteristic of initially high and low frequency.A multi-objective function,which integrated entropy value of low-resonance component,smoothness and the differentiation of that with high-resonance components,was constructed.An improved firefly algorithm was introduced to combine linearly decreasing inertia weight factor,and simulate the process of swarm intelligence optimization,so as to realize global search and precise identification for faults'characteristics.Finally,the optimally diagnostic result was outputted.Results:The diagnostic technique based on firefly algorithm for fault of MR coil of MRI equipment with superconductivity can effectively decompose and enhance the original signal,and significantly suppress the interference of background noise.The algorithm can approach the true solution of the fault,which only need 298 iterations through global search for the combination of faults'features and diagnostic parameters.It can realize accurate identification for the faults of MR coil.Conclusion:The diagnostic technique,which based on firefly algorithm for fault of MR coil of MRI equipment with superconductivity,appears obvious advantages on diagnostic accuracy and convergence speed.It can provide a feasible approach for rapid diagnosis for fault of MRI equipment with superconductivity.