Objective: To define the mechanism by which swine TRIM25 restricts vesicular stomatitis virus replication. Methods: Porcine 3D4/21 cells with TRIM25 overexpression or knockdown were infected with vesicular stomatitis virus. Viral replication was quantified by immunoblotting, quantitative reverse transcription polymerase chain reaction, and 50% tissue culture infectious dose assays. Type I interferon signaling was assessed by transcript quantification, interferon-beta and interferon-stimulated response element reporter assays, and co-immunoprecipitation.Viral RNA binding was tested by RNA immunoprecipitation. Results: TRIM25 overexpression reduced viral RNA and infectious titers, whereas TRIM25 knockdown increased replication (p < 0.01). TRIM25 increased interferon-beta and interferon-stimulated gene expression and enhanced interferon-beta and interferonstimulated response element promoter activity (p < 0.01). Mechanistically, TRIM25 promoted Lys63-linked ubiquitination of RIG-I and increased phosphorylation of TANK-binding kinase 1 and interferon regulatory factor 3. TRIM25 also bound vesicular stomatitis virus genomic RNA, and binding required the C-terminal region. Conclusions and Relevance: Porcine TRIM25 restricts vesicular stomatitis virus replication by amplifying type I interferon signaling and directly binding viral RNA.

Chinese patent medicines are the core preparations for disease prevention and treatment in clinical traditional Chinese medicine （TCM）. Their quality is the key to ensuring safe and effective medication and promoting the high-quality development of the TCM industry. At present， the quality evaluation of Chinese patent medicines faces prominent problems， such as inadequate control of quality consistency， over-reliance on single indicators， one-sided evaluation dimensions， unstable statistical methods， and poor implementability of research findings. These defects lead to insufficient scientificity of evaluation results， making it difficult to support the implementation of policies including centralized procurement， high quality， and favorable prices for Chinese patent medicines. According to the core requirements of quality evaluation for Chinese patent medicines， this study established a four-dimensional comprehensive evaluation system encompassing consistency index（CI）， content index（MI）， effect index（EI）， and preparation index（PI）. All evaluation indicators were normalized to achieve horizontal comparability. Meanwhile， an improved radar chart was introduced to realize the visualization of evaluation results. This method can systematically integrate four types of core quality attributes： Quality consistency， component content， biological activity， and preparation characteristics. It can effectively distinguish quality differences among products of the same specification from different manufacturers. The evaluation results are unique， stable， and not affected by the addition or reduction of samples， which takes scientificity， objectivity， and operability into account. This method can provide scientific and technical support for screening high-quality Chinese patent medicines and implementing policies of centralized procurement， high quality， and favorable prices. Moreover， it has important practical significance for improving the quality evaluation system of Chinese patent medicines and advancing the standard and modern development of TCM.

This study aims to explore the mechanism of Huanglian Jiedu Decoction(HJD) in treating acute liver injury(ALI) in the mouse model of sepsis induced by lipopolysaccharide(LPS). Fifty-four male C57BL/6 mice were randomized into six groups: blank group, model group, low-, medium-, and high-dose group HJD, and dexamethasone group. The mouse model of sepsis was established by intraperitoneal injection of LPS after 7 days of gavage with HJD, and dexamethasone(0.2 mL) was injected intraperitoneally 1.5 h after modeling. The murine sepsis score(MSS) was recorded 12 h after modeling. The levels of alanine aminotransferase(ALT) and aspartate aminotransferase(AST) in the liver tissue and tumor necrosis factor-α(TNF-α) and interleukin-6(IL-6) in the serum were measured by ELISA. Hematoxylin-eosin(HE) staining was used to observe the pathological changes of the mouse liver. The content of light chain 3 of microtubule-associated protein 1(LC3) was detected by immunofluorescence, and that of sirtuin 1(SIRT1) was detected by immunohistochemistry. The mRNA levels of adenosine 5'-monophosphate-activated protein kinase(AMPK), LC3, and P62 were detected by RT-PCR. Western blot was employed to determine the protein levels of AMPK, p-AMPK, and SIRT1 in the liver tissue. The results showed that compared with model group, drug interventions decreased the MSS and liver injury indicators, lowered the levels of inflammatory cytokines, improved the liver tissue structure, upregulated the protein levels of of p-AMPK/AMPK and SIRT1 and the mRNA levels of AMPK and LC3, and downregulated the mRNA level of P62. To sum up, HJD can regulate the autophagy level and reduce inflammation to ameliorate acute liver injury in septic mice by activating the AMPK/SIRT1 autophagy pathway.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Sirtuin 1/genetics* ; Male ; Mice ; Sepsis/metabolism* ; Mice, Inbred C57BL ; Autophagy/drug effects* ; AMP-Activated Protein Kinases/genetics* ; Liver/metabolism* ; Humans ; Signal Transduction/drug effects* ; Disease Models, Animal ; Tumor Necrosis Factor-alpha/genetics*

OBJECTIVE: To explore the therapeutic effect of polygonum cuspidatum glycoside on steroid-induced osteonecrosis of the femoral head(SONFH) in rats and its potential mechanism of protecting bone tissue by regulating the Janus kinase 2/signal transducer and activator of transcription 3 signaling pathway(JAK2/STAT3). METHODS: Fifty male SD rats were randomly divided into control group, model group, low-dose polygonum cuspidatum glycoside group (polygonum cuspidatum glycoside-L), high-dose polygonum cuspidatum glycoside group (polygonum cuspidatum glycoside-H), and polygonum cuspidatum glycoside-H+Colivelin (JAK2/STAT3 pathway activator) group. SONFH model was induced by lipopolysaccharide and dexamethasone. The treatment groups were given polygonum cuspidatum glycoside orally(polygonum cuspidatum glycoside-L 10 mg·kg^-1, polygonum cuspidatum glycoside-H 20 mg·kg^-1, and the polygonum cuspidatum glycoside-H+Colivelin group was injected with Colivelin (1 mg·kg^-1) intraperitoneally once a day, while the control and model groups were given an equal volume of saline for 6 weeks. The observed indicators included serum calcium(Ca), serum phosphorus (P), alkaline phosphatase, and transforming growth factor β1(TGF-β1) levels, micro-CT scanning, hematoxylin-eosin staining, and Western blot detection of JAK2/STAT3 signaling pathway and osteogenic differentiation marker genes, including Runt-related transcription factor 2 (Runx2), bone morphogenetic protein 2 (BMP2), and osteopontin (OPN) protein expression. RESULTS: Compared with the model group, the trabecular bone area percentage in the polygonum cuspidatum glycoside-L and polygonum cuspidatum glycoside-H groups was significantly increased, and the empty lacunar rate was significantly decreased (P<0.05). Micro-CT analysis showed that the bone volume fraction, trabecular number, and thickness increased, and the trabecular separation decreased in the polygonum cuspidatum glycoside-treated groups(P<0.05). Serum biochemical tests found that the serum Ca and P concentrations in the polygonum cuspidatum glycoside-L and polygonum cuspidatum glycoside-H groups were restored, the alkaline phosphatase levels decreased, and the transforming growth factor β1 levels increased (P<0.05). Western blot analysis showed that polygonum cuspidatum glycoside significantly inhibited the activation of the JAK2/STAT3 signaling pathway in the model group and promoted the expression of osteogenic differentiation marker genes such as Runx2, BMP2, and OPN (P<0.05). Compared with the polygonum cuspidatum glycoside-H group, the improvements in the polygonum cuspidatum glycoside-H+Colivelin group were somewhat weakened, indicating the importance of the JAK2/STAT3 signaling pathway in the action of polygonum cuspidatum glycoside. CONCLUSION polygonum cuspidatum glycoside promotes osteogenic differentiation, improves bone microstructure, and has significant therapeutic effects on rat SONFH by regulating the JAK2/STAT3 signaling pathway.
Animals ; Male ; Janus Kinase 2/physiology* ; Rats, Sprague-Dawley ; Rats ; Signal Transduction/drug effects* ; Glucosides/pharmacology* ; STAT3 Transcription Factor/genetics* ; Femur Head Necrosis/chemically induced* ; Stilbenes/pharmacology*

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Objective:To analyze the results of next generation sequencing (NGS) gene testing in liquid-based cytological specimens of lung adenocarcinoma cavity and evaluate the clinical efficacy of epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) treatment.Methods:Liquid based cytological specimens of 222 cases of lung adenocarcinoma with cavity effusion and 201 cases of metastatic lymph node biopsy were collected. Specimens were obtained from the Cytology Laboratory of the Cancer Hospital of the Chinese Academy of Medical Sciences. The collection period was from January 2018 to December 2022. The results of NGS gene detection were compared. The clinical efficacy of 91 patients treated with EGFR-TKI was evaluated, and the survival curve was analyzed by Kaplan-Meier and other statistical methods.Results:The mutation rates of cancer-related genes detected by NGS were 82.0% (182/222) vs 79.1% (159/201), ( P=0.455) in liquid-based cytological specimens and histological specimens of metastatic lymph node biopsy, respectively. However, the mutation rate of EGFR T790M was significantly higher in cavity effusion than in lymph node biopsy specimens [12.2%(27/222)＞3.5%(7/201), P=0.001]. The results of gene mutation were identical in 10 of the 13 cases with cavity effusion and metastatic lymph node biopsy, and the agreement rate of EGFR was 84.6%(11/13). In 3 inconsistent cases, EGFR mutations were detected in 2 cavity effusion cases that were not detected by lymph node biopsy. Results of genetic analysis of fluid-based cytological samples of 91 patients with cavity effusion were evaluated after drug treatment with EGFR-TKI. The mean progression-free survival (PFS) of the patients was 11.4 months (95% CI: 9.9-12.9). The mean PFS of patients harboring EGFR mutation was 12.3 months (95% CI: 10.8-13.9), and the mean PFS of EGFR wild type was 4.1 months (95% CI: 2.1-6.2). Conclusions:The results of NGS gene detection in liquid-based cytological specimens of lung adenocarcinoma patients with cavity effusion show that the PFS time is similar to that of histological specimens after clinical treatment with EGFR-TKI, which proves the reliability of NGS gene detection results in liquid cytological specimens. NGS gene testing appears higher sensitivity in cavity liquid-based samples than in metastatic lymph node samples.

ObjectiveThis study proposes a novel single-cell protein localization method based on a class perception graph convolutional network (CP-GCN) to overcome several critical challenges in protein microscopic image analysis, including the scarcity of cell-level annotations, inadequate feature extraction, and the difficulty in achieving precise protein localization within individual cells. The methodology involves multiple innovative components designed to enhance both feature extraction and localization accuracy. MethodsFirst, a class perception module (CPM) is developed to effectively capture and distinguish semantic features across different subcellular categories, enabling more discriminative feature representation. Building upon this, the CP-GCN network is designed to explore global features of subcellular proteins in multicellular environments. This network incorporates a category feature-aware module to extract protein semantic features aligned with label dimensions and establishes a subcellular relationship mining module to model correlations between different subcellular structures. By doing so, it generates co-occurrence embedding features that encode spatial and contextual relationships among subcellular locations, thereby improving feature representation. To further refine localization, a multi-scale feature analysis approach is employed using the K-means clustering algorithm, which classifies multi-scale features within each subcellular category and generates multi-cell class activation maps (CAMs). These CAMs highlight discriminative regions associated with specific subcellular locations, facilitating more accurate protein localization. Additionally, a pseudo-label generation strategy is introduced to address the lack of annotated single-cell data. This strategy segments multicellular images into single-cell images and assigns reliable pseudo-labels based on the CAM-predicted regions, ensuring high-quality training data for single-cell analysis. Under a transfer learning framework, the model is trained to achieve precise single-cell-level protein localization, leveraging both the extracted features and pseudo-labels for robust performance. ResultsExperimental validation on multiple single-cell test datasets demonstrates that the proposed method significantly outperforms existing approaches in terms of robustness and localization accuracy. Specifically, on the Kaggle 2021 dataset, the method achieves superior mean average precision (mAP) metrics across 18 subcellular categories, highlighting its effectiveness in diverse protein localization tasks. Visualization of the generated CAM results further confirms the model’s capability to accurately localize subcellular proteins within individual cells, even in complex multicellular environments. ConclusionThe integration of the CP-GCN network with a pseudo-labeling strategy enables the proposed method to effectively capture heterogeneous cellular features in protein images and achieve precise single-cell protein localization. This advancement not only addresses key limitations in current protein image analysis but also provides a scalable and accurate solution for subcellular protein studies, with potential applications in biomedical research and diagnostic imaging. The success of this method underscores the importance of combining advanced deep learning architectures with innovative training strategies to overcome data scarcity and improve localization performance in biological image analysis. Future work could explore the extension of this framework to other types of microscopic imaging and its application in large-scale protein interaction studies.

Poly(lactic-co-glycolide)(PLGA)is a key excipient in long-acting sustained-release preparations,and its degradation properties directly affect the drug release behavior.In this study,PLGA microspheres were prepared by microfluidic techniques,and the morphology changes of the microspheres were observed by scanning electron microscopy(SEM).In alkaline environment,due to the accelerated hydrolysis of ester bonds,the surface of the microspheres was rapidly dissolved and eroded,and the degradation rate was significantly higher than that in acidic environment.High temperature accelerated the degradation of PLGA microspheres.Under neutral and alkaline conditions,the microspheres showed aggregation and adhesion.Under acidic conditions,the microspheres gradually decomposed into irregular fragments.The high ionic strength further promoted the surface corrosion of the microspheres,especially under extreme pH conditions.Simultaneously,PLGA microspheres encapsulating coumarin were prepared to simulate the microsphere formulation.The release rate of coumarin after degradation of the microspheres under different conditions was observed by measuring the absorbance with ultraviolet-visible spectrophotometry.The results were consistent with those of the blank microspheres.This study revealed that the degradation of PLGA microspheres was significantly pH-dependent,temperature sensitive and ion strength responsive.These findings not only helped to understand and optimize the long-term stability and controlled release performance of drug-carrying microspheres,but also provided a theoretical basis for further improvement of PLGA-based drug carrier design.

In this study,a sensitive lateral flow immunoassay(LFIA)platform based on carbon dots-mesoporous silica nanocomposite(CD-MSNs)fluorescent probes was constructed for high-performance detection of inflammatory marker interleukin-6(IL-6).Green fluorescent carbon dots(CDs)were prepared by hydrothermal method with 3,9-perylenic acid and 3-aminopropyltriethoxysilane(APTES)as raw materials,and highly fluorescent CD-MSNs composites were then constructed by encapsulating the prepared CDs in mesoporous silica nanoparticles(MSNs).Fluorescent probes were prepared by covalent coupling of CD-MSNs with IL-6 antibody.Fluorescent immunochromatographic test strips were constructed by spraying IL-6 capture antibody and goat anti-mouse IgG on nitrocellulose membrane as detection line(T-line)and quality control line(C-line),respectively.The fluorescence immunoassay analyzer was used to quantitatively detect the fluorescence intensity of T-line,and the experimental results showed that the LFIA platform based on this probe had a good linear relationship in IL-6 concentration range of 102-106 pg/mL,and the detection limit was 64 pg/mL,which was two orders of magnitude more sensitive than that of the traditional colloidal gold test strips.This method effectively solved the issue of insufficient sensitivity of traditional LFIA technique,and provided a rapid and highly sensitive detection method for early diagnosis of inflammatory diseases.

Objective To investigate the metabolic characteristics of patients with early-onset type 2 diabetes mellitus(T2DM)and to develop a risk prediction model for microvascular complications.Methods A retrospective study was conducted on 980 T2DM patients admitted for treatment between April 2020 and April 2024.Based on age at diagnosis,the patients were divided into two groups,an early-onset T2DM group(age at diagnosis<40 years,n=265)and a late-onset T2DM group(age at diagnosis≥40 years,n=715).Differences in metabolic indicators between the two groups were compared.Patients in the early-onset group were further divided into a complication subgroup(n=142)and a non-complication subgroup(n=123)based on the presence or absence of microvascular complications.Data on baseline characteristics,metabolic parameters,and laboratory indicators were collected and compared between the two groups.Multivariate logistic regression analysis was used to identify independent risk factors for microvascular complications,and a nomogram prediction model was constructed.The model's discriminative performance was assessed using receiver operating characteristic(ROC)curves,and its calibration was evaluated using calibration curves and the Hosmer-Lemeshow test.Decision curve analysis(DCA)was also performed to assess the model's clinical utility.Results Compared with the late-onset group,patients in the early-onset group exhibited more pronounced metabolic abnormalities,including higher body mass index(BMI),proportion of family history of diabetes mellitus,glycated hemoglobin(HbA1c)levels,total cholesterol(TC),triglycerides(TG),low-density lipoprotein cholesterol(LDL-C),triglyceride-glucose index(TyG),and lactate dehydrogenase(LDH)levels(all P<0.05),along with a shorter disease duration and lower levels of high-density lipoprotein cholesterol(HDL-C)(P<0.05).According to a multivariate analysis,systolic blood pressure(SBP),total bilirubin(TBIL),HDL-C,LDL-C,TyG,and LDH were identified as independent risk factors for microvascular complications in patients with early-onset T2DM.A predictive model based on these factors was established as the follows,Log(P)=-19.915+0.017×SBP-0.136×TBIL-1.241×HDL-C+0.684×LDL-C+0.769×TyG+0.050×LDH.The area under the ROC curve(AUC)was 0.864(95%CI,0.820-0.907),and the Hosmer-Lemeshow test indicated good model fit(χ2=10.286,P=0.246).The slope of the DCA curve was also close to 1.Conclusion The nomogram prediction model based on SBP,TBIL,HDL-C,LDL-C,TyG,and LDH demonstrates good predictive performance for microvascular complications and can provide a reference for clinical risk stratification and individualized intervention.