ObjectiveA middle cerebral artery occlusion (MCAO) mouse model is established by electrocoagulation of the middle cerebral artery. The study examines the mechanism by which exosomes (EXO) derived from human amniotic mesenchymal stem cells (hAMSCs) improve ischemic stroke and regulate neural ferroptosis-related injury. MethodsThirty-two SPF-grade male C57BL/6J mice aged 6 - 8 weeks were randomly divided into four groups (n=8 per group): sham group (Sham), model group (MCAO), MCAO plus normal saline group (MCAO+NaCl), and MCAO plus exosome group (MCAO+EXO). The mouse MCAO model was established by electrocoagulation of the middle cerebral artery. Mice in the Sham group underwent exposure of the middle cerebral artery without electrocoagulation. Twenty-four hours before MCAO induction, mice in the MCAO+EXO group received a tail vein injection of 100 μL of exosomes derived from the culture supernatant of hAMSCs at a concentration of 9.5×10¹¹ particles/mL. Mice in the MCAO+NaCl group were injected with an equal volume of normal saline via the tail vein. Twenty-four hours after model establishment, neurological deficits were evaluated using the Longa neurological deficit scoring system. Cerebral infarct volume was assessed by 2,3,5-triphenyltetrazolium chloride (TTC) staining. Hematoxylin and eosin (HE) staining was performed to evaluate morphological changes of neurons in the ischemic brain regions. The contents of ferrous iron (Fe²⁺), malondialdehyde (MDA), total glutathione (total GSH), oxidized glutathione (GSSG), and reduced glutathione (GSH) in the infarct core and peri-infarct regions were determined using microcolorimetric assays to evaluate differences among groups. The mRNA expression levels of ferroptosis-related factors, including nuclear factor erythroid 2-related factor 2 (NRF2), solute carrier family 7 member 11 (SLC7A11), and glutathione peroxidase 4 (GPX4) in the infarct core and peri-infarct regions were measured by real-time quantitative PCR. Protein expression levels of NRF2, SLC7A11, and GPX4 in the infarct and peri-infarct regions of each group were analyzed by Western blotting. ResultsCompared with the MCAO group, the Longa neurological deficit score was significantly reduced in the MCAO+EXO group (P<0.01). Prominent cerebral infarction was observed in the MCAO group, whereas the infarct volume ratio was markedly decreased in the MCAO+EXO group compared with the MCAO group (P<0.001). Histopathological analysis revealed that mice in the MCAO group exhibited obvious neuronal damage, including cytoplasmic vacuolar degeneration, nuclear pyknosis and fragmentation, unclear nuclear structure, and disorganized neuronal arrangement, compared with the Sham group. In contrast, neurons in the MCAO+EXO group showed relatively preserved morphology, with intact cellular structures and large, regular nuclei located centrally within the cells. Biochemical analysis demonstrated that Fe²⁺ and MDA levels in the infarct core and peri-infarct regions were significantly increased in the MCAO group compared with the Sham group (P<0.001). These levels were significantly reduced in the MCAO+EXO group compared with the MCAO group (P<0.01). In addition, total glutathione (total GSH), oxidized glutathione (GSSG), and reduced glutathione (GSH) levels were markedly decreased in the MCAO group relative to the Sham group (P<0.01). Compared with the MCAO group, the MCAO+EXO group exhibited significantly increased levels of total GSH and GSH (P<0.001), while no significant change was observed in GSSG levels (P>0.05). Furthermore, both mRNA and protein expression levels of nuclear factor erythroid 2-related factor 2 (NRF2), solute carrier family 7 member 11 (SLC7A11), and glutathione peroxidase 4 (GPX4) were significantly downregulated in the MCAO group compared with the Sham group (P<0.01, P<0.001). In contrast, both mRNA and protein expression levels of NRF2, SLC7A11, and GPX4 were significantly upregulated in the MCAO+EXO group compared with the MCAO group (P<0.05). ConclusionIn the mouse MCAO model, tail vein injection of exosomes derived from hAMSCs can improve motor function, reduce infarct area, protect neuronal cell morphology, and reduce the degree of nerve injury. Exosomes may exert a protective effect by activating the NRF2/SLC7A11/GPX4 pathway and reducing ferroptosis in neuronal cells of MCAO model mice.

OBJECTIVE To form an expert consensus on the clinical application of parenteral direct thrombin inhibitors （DTIs） in patients during the perioperative period. METHODS Led by Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital （the Affiliated Hospital of UESTC）， a multidisciplinary working group was established. Through literature review and the Delphi method， clinical questions related to the rational perioperative use of parenteral DTIs were identified. A structured design was adopted using the “Population-Intervention-Comparison-Outcome” framework； systematic searches were conducted in CNKI， Medline， Embase and other databases. Relevant evidence from randomized controlled trials and cohort studies was included and synthesized. Evidence quality was assessed using the Grades of Recommendations Assessment，Development and Evaluation （GRADE） approach， and recommendations were formulated through multiple rounds of Delphi surveys and expert consensus meetings. RESULTS &CONCLUSIONS Seven recommendations （each with an expert consensus rate exceeding 90%） on the use of parenteral DTIs in perioperative patients were developed. These recommendations specify drug selection， dosing ranges， key monitoring points， and safety management strategies for parenteral DTIs in various scenarios， including the perioperative period of ventricular assist device implantation， the perioperative period of cardiac surgery， perioperative patients with lower-extremity atherosclerotic disease， the perioperative period of percutaneous coronary intervention in patients with acute coronary syndrome， the perioperative period of carotid artery stenting in patients with carotid stenosis， the perioperative period of patients with right heart thrombosis， and patients who develop related thrombosis and dysfunction after a central venous catheter insertion. In addition， warning and management pathways for perioperative bleeding and thrombotic events were proposed. This expert consensus， which is formulated based on the best available evidence， provides evidence-based guidance for standardized and individualized use of parenteral DTIs in perioperative period.

Objective To analyze the case data of farmers' foodborne disease surveillance reports in Guizhou Province from 2022 to 2024, and to provide reference for the precise prevention and control of foodborne diseases among farmers in Guizhou Province. Methods Case data of foodborne disease surveillance reports of farmers were systematically collected from 2022 to 2024 in Guizhou Province. Descriptive epidemiological methods were used to analyze the temporal, geographical, and demographic distribution of foodborne diseases among farmers, along with their primary clinical symptoms and pathogen detection results. Results From 2022 to 2024, a total of 22,882 cases of foodborne diseases were reported among farmers in Guizhou Province. The majority of clinical symptoms (97.81%) were related to the digestive system, with summer being the peak season. While females outnumbered males, the gender difference was statistically insignificant (P >0.05). The 36-55 age group accounted for the highest proportion (38.83%), with Zunyi City (34.89%) and Qiandongnan Prefecture (23.21%) reporting the most cases. Fungal products were the most frequently reported suspected food items (26.96%), and home-made preparation was the primary processing method (58.63%). A total of 1 210 fecal samples were collected through active monitoring with an overall detection rate of 13.22%. Norovirus showed the highest detection rate (9.92%, 120/1 210). Statistically significant differences were observed among different seasons, age groups, regions, types and processing methods of suspected food exposure, and pathogen detection rates (P <0.001). Conclusion Foodborne disease prevention and control among farmers in Guizhou Province should focus on the risks of wild mushroom poisoning in summer and homemade foods, and continuously improve farmers' awareness of the dangers of foodborne diseases and food safety.

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.

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）.

The Solomon four-group design， a critical method for improving internal validity in clinical research， can reduce bias and control the interference of Hawthorne effects and pretest sensitization on research results， which offers unique advantages in evaluating complex intervention outcomes. This paper systematically outlined the core framework and key points of statistical analysis of the Solomon four-group design， summarized its applications in clinical research at home and abroad， explored its advantages and limitations， and discussed the potential value in traditional Chinese medicine （TCM） clinical trials. It is believed that the Solomon four-group design can help distinguish between testing effects and intervention effects in TCM clinical studies， and reduce the bias in the evaluation of subjective indicators. Meanwhile， given the complexity of the Solomon four-group design and the particularity of TCM clinical research， it is proposed that future TCM clinical studies should focus on using psychological scales， know-ledge， attitude， and behavior measurements， and other similat evaluations as endpoints. It also advocates strengthening interdisciplinary collaboration to provide new methodological paths for TCM clinical research.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

OBJECTIVE: To explore the efficacy differences among different acupuncture frequencies for pain of temporomandibular disorders (TMD). METHODS: A total of 42 patients with TMD pain were randomly divided into a low-frequency group, a medium-frequency group, and a high-frequency group, with 14 patients in each group. All groups received acupuncture treatment at bilateral Hegu (LI4) and Yanglingquan (GB34), as well as ipsilateral Tinggong (SI19), Jiache (ST6), and Xiaguan (ST7), with each session lasting 30 minutes. The low-frequency group received acupuncture once per week, the medium-frequency group received acupuncture twice per week, and the high-frequency group received acupuncture three times per week, for a total duration of four weeks. The graded chronic pain scale (GCPS) score, visual analogue scale (VAS) score, jaw functional limitation scale-20 (JFLS-20) score, and pressure pain threshold (PPT) were assessed in the three groups before and after treatment, as well as at the four-week follow-up after treatment completion. RESULTS: Compared before treatment, GCPS and JFLS-20 scores were significantly decreased in all the groups after treatment (P<0.05), and VAS scores were significantly decreased in the high-frequency and medium-frequency groups (P<0.05), PPT values at different measurement sites were increased significantly in the high-frequency group (P<0.05). After treatment, GCPS, JFLS-20, and VAS scores in the high-frequency group were lower than those in the medium-frequency and low-frequency groups (P<0.05), while some PPT values were higher than the other two groups (P<0.05). At follow-up, GCPS, JFLS-20, and VAS scores remained significantly lower in all the groups compared to baseline (P<0.05), PPT values were increased significantly in the high-frequency and medium-frequency groups (P<0.05), with the high-frequency group showing lower GCPS, JFLS-20, and VAS scores and higher PPT values compared to the other two groups (P<0.05). CONCLUSION Acupuncture three times per week is more effective in reducing TMD pain intensity compared to once or twice per week, and can also alleviate some mandibular functional impairments. The therapeutic effects persist for at least four weeks after treatment completion.
Humans ; Male ; Female ; Adult ; Acupuncture Therapy/methods* ; Temporomandibular Joint Disorders/physiopathology* ; Middle Aged ; Young Adult ; Treatment Outcome ; Acupuncture Points ; Pain Management ; Adolescent ; Pain Measurement

Aim To investigate the mechanism of ac-tion of Qingre Zhixue granules in the treatment of IgA vasculitic nephritis(IgAVN)based on network phar-macology and animal experiments.Methods The ac-tive ingredients and targets of Qingre Zhixue granules were screened out by TCMSP database.The disease targets of IgAVN were retrieved by Disgenet,Gene-cards OMIM and TTD databases.The intersection tar-gets were obtained by WeChat online database,and the information was imported into Cytoscope 3.7.1 soft-ware and STRING analysis platform to construct a drug-active component-therapeutic target network.Based on the core targets,GO and KEGG pathway enrichment a-nalysis was performed through the Metascape database to select key targets and core active components.The results of network pharmacology were verified by ani-mal experiments.The animal model of IgAVN was con-structed by the combination of disease and syndrome.The urine red blood cells and 24-hour urine protein of IgAVN model rats after intervention of Qingre Zhixue granules were detected.HE staining and IgA immuno-fluorescence deposition of renal tissue were observed.Western blot and qRT-PCR were used to detect the ex-pression of core targets in renal tissue.Results Net-work pharmacology showed that 109 active ingredients,402 drug targets,1 285 disease targets and 113 inter-section targets were obtained.The core targets screened by protein interaction and network topology a-nalysis were IL6,TNF,VEGFA,etc.The core drug ingredients were quercetin,paeoniflorin,luteolin,kaempferol and baicalein.A total of 2 545 gene func-tions were enriched by GO,and 164 gene pathways were enriched by KEGG.Qingre Zhixue granules could treat IgAVN by regulating TNF signaling pathway,MAPK signaling pathway,IL-17 signaling pathway,HIF-1 signaling pathway,Toll receptor signaling path-way,NF-κB signaling pathway and apoptosis.Animal experiments showed that compared with the blank group,the urine red blood cells and 24-hour urine pro-tein quantification in the model group increased(P＜0.05);the expression of serum IL-6,TNF-α and VEGF-α increased(P＜0.05).HE staining showed glomerular mesangial proliferation,capillary lumen ste-nosis,accompanied by a small amount of inflammatory cell infiltration,glomerular IgA immunofluorescence deposition;the expression of TNF-α,p-p65,p-p38 protein and TNF-α mRNA in renal tissue increased(P＜0.05).After the intervention of Qingre Zhixue gran-ules,urine red blood cells and 24-hour urine protein decreased(P＜0.05).The changes of renal HE stai-ning were improved and glomerular IgA deposition was reduced.TNF-α,p-p65,p-p38 protein and TNF-αmRNA in renal tissue decreased(P＜0.05).Conclu-sions The active ingredients such as quercetin,peony glycoside and luteolin Qingre Zhixue granules regulate TNF signaling pathway,MAPK signaling pathway,IL-17 signaling pathway and reduce IL-6,TNF-α and VEGF-α in the treatment of IgAVN.