ObjectiveTo investigate the potential mechanism of Yiqi Yangyin Huoxue Formula （益气养阴活血方， YYHF） in the treatment of membranous nephropathy （MN） based on the NOX4-mediated stromal cell-derived factor-1α（SDF-1α）/CXC chemokine receptor 4 （CXCR4） signaling pathway. MethodsA total of 42 male SD rats were randomly divided into blank group （n=6） and modeling group （n=36）. The modeling rats were given a single injection of sheep antirat Fx1A （6 ml/kg） serum into the tail vein to establish MN model. Thirty-six rats with successful modeling were further divided into model group （normal saline， 10 ml/kg）， benazepril group （10 mg·kg^-1·d^-1）， the medium-dose YYHF group （11.0 g·kg^-1·d^-1） and high-dose YYHF group （22.0 g·kg^-1·d^-1）， with 9 rats in each group. All groups received daily intragastric administration for 6 consecutive weeks. During the experimental period， the general condition of rats in each group was observed. After gavage administration finished， a fully automated biochemical analyzer was used to measure the 24-hour urine total protein （24 h-UTP） and serum biochemical parameters， including albumin （ALB）， aspartate aminotransferase （AST）， blood urea nitrogen （BUN）， serum creatinine （SCr）， total cholesterol （TC）， and triglyceride （TG）. Hematoxylin-eosin （HE） staining and periodic acid-silver metheramine （PASM） staining were used to observe the histopathological changes of renal tissues in each group of rats. The levels of superoxide dismutase （SOD） and malondialdehyde （MDA） in renal tissues were detected by ELISA. The protein expression levels of NOX4， SDF-1α， CXCR4， Nrf2， nuclear factor kappa B subunit p65 （NF-κB p65） and podocyte slit diaphragm protein nephrin in rat renal tissues were detected by Western Blotting. The mRNA expressions of NOX4， SDF-1α， CXCR4， Nrf2， NF-κB p65 and Nephrin in renal tissues were detected by real-time fluorescence quantitative polymerase chain reaction （RT-PCR）. ResultsCompared to the blank group， rats in the model group exhibited typical features of MN， including lethargy， reduced activity， dull and coarse fur， marked edema， and massive proteinuria. Compared to the model group， these abnormal conditions were improved to varying degrees in all treatment groups. The high-dose YYHF group showed a level of improvement comparable to that of the benazepril group， with overall recovery superior to that of the medium-dose YYHF group. Compared to the blank group， the model group showed increased levels of 24 h-UTP， BUN， SCr， TC and TG， decreased level of ALB， increased levels of MDA and protein and mRNA expressions of NOX4， SDF-1α， CXCR4 and NF-κB p65 in renal tissue， along with decreased levels of SOD and protein and mRNA expressions of Nrf2， Nephrin （P＜0.01）， accompanied by severe renal pathological damage. Compared to the model group， the benazepril and the medium- and high-dose YYHF groups showed significant improvements in the above indicators （P＜0.01）， along with alleviation of renal pathological injury. The 24 h-UTP level in the high-dose YYHF group was lower than that in the medium-dose group （P＜0.01）， while no statistically significant difference was observed among the other treatment groups （P＞0.01）. ConclusionYYHF may alleviate oxidative stress and inflammatory responses by down-regulating the expression of NOX4 and inhibiting the SDF-1α/CXCR4-Nrf2 signaling pathway， thereby improving podocyte damage and protecting renal function.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveThis paper aims to observe the syndrome improvement and negative antigen conversion rate of Qingxuan Daozhi formula in the treatment of influenza in children （heat accumulation in the lung and stomach syndrome）. MethodsThrough a multi-center randomized controlled methodology design，confirmed influenza cases were collected from October 2022 to April 2023 in the pediatrics department of eight hospitals，such as Dongfang Hospital of Beijing University of Chinese Medicine. A total of 180 children with influenza and heat accumulation in the lung and stomach syndrome conforming to the standard were recruited through the clinic. The sick children meeting the inclusion criteria were randomly divided into groups by a block-randomized method. The children in the experimental group were treated with Qingxuan Daozhi formula for five days，and those in the control group were treated with Oseltamivir Phosphate Granules for five days. The primary efficacy indicator was the negative conversion rate of influenza antigen detection. Secondary efficacy indicators were the Canadian acute respiratory illness and flu scale （CARIFS） and the incidence of complications，severe cases， and critical cases. Follow-up observation was conducted on the day of enrollment，48 hours after medication，72 hours after medication， and （6+1） d after medication. ResultsOne hundred and eighty participants were randomly assigned to the experimental group （90 cases） or the control group （90 cases）. All participants were followed up during the study. Comparison of influenza antigen detection results in the primary efficacy indicators showed that the average time of negative influenza antigen conversion in the experimental group was （5.29±1.25） d，and that in the control group was （5.40±1.68） d，without a statistically significant difference. After five days of intervention，52 cases in the experimental group and 51 cases in the control group converted to negative，without a statistically significant difference. CARIFS score results in the secondary efficacy indicators showed that during 72 hours after intervention，there were statistically significant differences between the experimental group and the control group in three dimensions， including headache，muscle soreness， and the need for extra care （P<0.05）. On the （6+1） days after the intervention，the differences in both the experimental group and the control group were statistically significant in 10 dimensions， including sore throat，bad sleep，uncomfortable feeling，poor spirit and fatigue，crying more than usual，the need for extra care，symptom，function，influence on parents，and total score （P<0.05）. The comparison results within the group in the dimensional scores of symptom， function， and influence on parents，as well as the CARIFS total score showed that with the delay of follow-up time，scores of both groups decreased significantly，with a statistically significant difference （P<0.01）. Inter-group comparison results showed that the mean score of the experimental group was higher than that of the control group at the time of enrollment. With the progress of intervention，the score of the experimental group was significantly decreased compared with that of the control group. At the end of follow-up，the mean score of the experimental group was lower than that of the control group，with no statistically significant difference. In terms of the incidence of complications，severe cases， and critical cases， there were no complications，severe cases， and critical cases in the two groups，without a statistically significant difference. ConclusionThe symptom improvement effect and negative antigen conversion rate of Qingxuan Daozhi formula in the treatment of influenza in children （heat accumulation in the lung and stomach syndrome） are not inferior to Oseltamivir Phosphate granules， and children's acceptance is better. It can be more widely used in clinical treatment of influenza in children （heat accumulation in the lung and stomach syndrome）.

Objective To systematically review the studies on predictive models for delayed graft function (DGF) after kidney transplantation. Methods Databases including China Biology Medicine Database, China National Knowledge Infrastructure, Wanfang Database, VIP Database, PubMed, Web of Science and CINAHL were searched to collect studies on predictive models for DGF after kidney transplantation published from the establishment of each database to June 29, 2025. Two researchers screened the literatures according to the inclusion and exclusion criteria, evaluated the quality of the literatures using the prediction model risk of bias assessment tool (PROBAST), and conducted a meta-analysis of the common predictors of the models using R software. Results A total of 12 literatures were included, involving 14 predictive models with sample sizes ranging from 103 to 24 653 cases. Donor serum creatinine level, cold ischemia time, donor age and donor body mass index were the top four common predictors. All the predictive models were at high risk of bias and low in applicability. The results of meta-analysis showed that abnormal donor body mass index, advanced donor age, prolonged cold ischemia time and elevated donor serum creatinine level were all associated with an increased risk of DGF after transplantation (all P<0.01), but there was high heterogeneity among the studies. Fixed-effect model and random-effect model were used to re-pool the effect sizes separately. The results indicated that the fixed-effect model and random-effect model had good consistency in terms of donor body mass index, donor age and cold ischemia time, while there was a significant difference in the effect sizes of the two models for donor serum creatinine level. Conclusions The predictive models for DGF risk after kidney transplantation have good predictive performance, but the overall risk of bias is high. In the future, large-sample, multicenter and high-quality prospective clinical studies should be carried out to optimize the predictive models, so as to improve their predictive ability and clinical application value.

Objective: To investigate the mechanism of shed syndecan-4 (sSDC4) in temporomandibular joint osteoarthritis (TMJOA) in rats, aiming to provide experimental evidence for its prevention and treatment. Methods: This study was approved by the Institutional Animal Ethics Committee. Twelve 6-week-old female Sprague Dawley (SD) rats were randomly divided into two groups. They received a single intra-articular injection into the bilateral superior cavity of temporomandibular joint, which consisted of either 50 μL of 4 mg/mL monosodium iodoacetate (TMJOA model group) or 50 μL of phosphate-buffered saline (PBS, control group). After 4 weeks, the mandibular condylar cartilage was harvested for hematoxylin & eosin (H&E) staining, Safranin O-fast green (SO) staining, and type II collagen (Col-Ⅱ) immunohistochemical staining to assess the degree of cartilage degeneration. The synovium of the temporomandibular joint was collected for immunohistochemical staining to detect the expression levels of interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) to evaluate the degree of synovial inflammation. Synovial fluid from the temporomandibular joint cavity was collected to measure sSDC4 levels by enzyme-linked immunosorbent assay (ELISA). In addition, 12 6-week-old female SD rats were randomly divided into a His-SDC4 group and a control group, receiving injections into the bilateral superior cavity of temporomandibular joint of either 100 ng/mL (50 μL) of His-SDC4 protein or 50 μL of PBS once every 3 days for a total of 28 days. The same experimental procedures were performed for H&E staining, SO staining, and immunohistochemical staining (Col-Ⅱ IL-6, TNF-α) to observe condylar cartilage degeneration and detect synovial inflammation. Rat synovial fibroblasts and condylar chondrocytes were cultured in vitro and randomly divided into a His-SDC4-stimulated (10 ng/mL) group and control group. Perform CCK-8 cytotoxicity assays and observe cellular morphology under optical microscopy, the mRNA expression levels of IL-6 and TNF-α were detected by real-time quantitative polymerase chain reaction (RT-qPCR), and the levels of IL-6 and TNF-α in cell culture supernatants were measured by ELISA. Results: Compared with the control group, the TMJOA group showed decreased condylar cartilage thickness, percentage of SO-positive area, and percentage of Col-Ⅱ-positive area (all P<0.001); an increased synovitis score (P<0.001) and increased percentages of IL-6- and TNF-α-positive cells in the synovium (all P<0.001); and a significant increase in sSDC4 levels in the synovial fluid (P=0.011). Following intra-articular injection of His-SDC4, condylar cartilage thickness, percentage of SO-positive area, and percentage of Col-Ⅱ-positive area all decreased (all P<0.001); the synovitis score increased (P=0.006), and the percentages of IL-6- and TNF-α-positive cells in the synovium increased (all P<0.001). In vitro experiments showed that His-SDC4 stimulation significantly upregulated the expression levels of IL-6 and TNF-α in both synovial fibroblasts and condylar chondrocytes (all P<0.01), and the levels of these two cytokines in the culture supernatants also significantly increased (all P<0.01). Conclusion During TMJOA progression, the level of sSDC4 in the synovial fluid is significantly elevated, which can directly stimulate synovial fibroblasts and condylar chondrocytes to secrete more pro-inflammatory cytokines, forming a vicious cycle that accelerates TMJOA progression.

Objective To analyze the genetic characteristics and variations of influenza A (H3N2) viruses in Ma'anshan from 2022 to 2024, and to provide a scientific basis for local influenza prevention and control. Methods From April 2022 to March 2024, influenza-like illness (ILI) specimens were collected from three national influenza surveillance sentinel hospitals in Ma’anshan. Samples positive for influenza by real-time PCR were subjected to virus culture and identification. A total of 40 representative A/H3N2 strains with hemagglutination titers ≥8 were selected for whole-genome sequencing. Genetic evolution, homology, amino acid variations, and glycosylation sites were analyzed. Results All H3N2 representative strains from the 2022–2023 influenza season belonged to clade 3C.2a1b.2a.1a.1, while those from the 2023–2024 season fell into clade 3C.2a1b.2a.2a.3a.1. The nucleotide and amino acid sequence similarities of HA and NA between the 40 representative strains and the vaccine strain A/Darwin/6/2021 were all above 97.35%. Compared with the vaccine strain, amino acid mutations were identified in antigenic sites A, B, C, and E, as well as in receptor-binding sites of the HA protein. An I222V substitution was detected in the NA protein. The HA protein contained four additional glycosylation sites compared to the vaccine strain, while the glycosylation pattern of the NA protein remained consistent. Conclusion No antigenic drift was observed in the influenza A/H3N2 viruses in Ma'anshan City from 2022 to 2024, but genetic changes such as branching variations, key amino acid substitutions, and an increase in HA glycosylation sites were observed. These findings underscore the importance of sustained molecular surveillance of local influenza viruses.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Hepatocellular carcinoma (HCC) imposes a major health and economic burden worldwide, with disproportionate effects in low- and middle-income countries (LMICs). Surveillance in high-risk populations, typically using semiannual ultrasound and alpha-fetoprotein testing, has been shown to be cost-effective by enabling earlier detection and improving survival. Yet, its overall value is reduced by poor adherence and the limited sensitivity of ultrasound, particularly in patients with metabolic-associated steatotic liver disease. Emerging approaches—including abbreviated magnetic resonance imaging, multi-biomarker models (e.g., gender, age, AFP, AFP-L3, and DCP), and liquid biopsy assays such as methylated DNA markers—demonstrate greater diagnostic accuracy and potential economic advantages compared with conventional methods. Integration of artificial intelligence into imaging may further enhance efficiency and reduce downstream costs. Moving toward precision surveillance, guided by individualized risk stratification that incorporates etiology, fibrosis stage, and molecular profiles, can optimize allocation of resources and maximize cost-effectiveness at the population level. Interventions to improve adherence, including mailed outreach and behavioral economic incentives, have shown both clinical benefit and cost savings, underscoring the role of implementation science. Because socioeconomic disparities influence both access and outcomes, economic models must explicitly address equity to achieve sustainable impact. Future research should prioritize prospective trials that evaluate not only clinical performance but also the real-world cost-effectiveness of novel technologies and stratified surveillance strategies. For LMICs, adapting proven models into affordable, context-appropriate programs is essential. By combining prevention, precision risk assessment, innovative technologies, and equitable implementation, HCC surveillance can deliver both clinical and economic value, reducing the global burden of disease.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.