ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

Objective To investigate the causal relationship between metabolic syndrome and breast cancer by using a bidirectional two-sample Mendelian randomization (MR) approach. Methods Genome-wide association study (GWAS) summary statistics for metabolic syndrome and breast cancer were acquired from the Integrative Epidemiology Unit GWAS database and the GWAS Catalog, with populations encompassing the United States and East Asia. A bidirectional causal design was employed: a forward analysis with metabolic syndrome as the exposure and breast cancer as the outcome, followed by a reverse analysis wherein their roles were interchanged. The inverse-variance weighting (IVW) method was primarily used for effect estimation, supplemented by MR-Egger regression, the weighted median method, the simple mode method, and the weighted mode method. Instrument variable strength was screened using the F-statistic (F>10). Robustness of the results was assessed through heterogeneity tests, horizontal pleiotropy tests, forest plots, and leave-one-out sensitivity analyses. Results The IVW analysis indicated no significant causal relationship between metabolic syndrome and breast cancer (OR=1.00, 95%CI: 0.97-1.03), P>0.05). Sensitivity analyses yielded consistent results, suggesting the good robustness of the study findings. Conclusion This study found no evidence to support a causal relationship, either positive or negative, between metabolic syndrome and breast cancer.

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.

Hypertension ranks among the most prevalent chronic non-communicable diseases worldwide, with its prevalence rising steadily and exerting substantial impacts on the demographic composition of voluntary blood donors and the safety of blood supply. The eligibility of hypertensive individuals for safe blood donation and the relevant screening and management strategies have long remained controversial in transfusion medicine. This article systematically reviews the epidemiological characteristics of hypertension, donation-related physiological alterations and underlying risk mechanisms. By synthesizing evidence from international multicenter studies and regulatory practices across major nations, it conducts a comprehensive analysis of blood donation safety and donor admission criteria for hypertensive patients. Available evidence demonstrates that for hypertensives with well-stabilized blood pressure and no severe cardiac, cerebral or renal complications or target organ damage, the overall incidence of adverse reactions following blood donation is comparable to that in healthy donors, and no definitive correlation has been identified between blood pressure levels and vasovagal responses. Current mainstream international management frameworks are gradually shifting from screening reliant on a single blood pressure cutoff value toward an integrated strategy combining stratified risk classification and individualized dynamic assessment, with core focus on long-term blood pressure control, consistency of medication regimens and complication status. Meanwhile, emerging technologies including artificial intelligence, ambulatory blood pressure monitoring and wearable devices have opened innovative avenues for blood donation risk evaluation and full-cycle donor management. In light of existing clinical evidence, future efforts should further refine the multi-dimensional risk stratification system, facilitate the implementation of intelligent screening and continuous monitoring technologies, and scale up health education and follow-up management for hypertensive populations. Such measures aim to appropriately expand the pool of eligible blood donors while safeguarding donation safety, ultimately achieving coordinated improvement in blood safety and blood supply capacity.

ObjectiveTo explore the mechanism of Shaoyaotang in the prevention and treatment of colitis-associated carcinogenesis （CAC） based on myeloid-derived suppressor cells （MDSCs）-related immunosuppressive microenvironment. MethodsA total of 140 six-week-old SPF FVB male mice were randomly divided into seven groups： Blank group， Shaoyaotang without model group （7.12 g·kg^-1）， model group， sulfasalazine group （0.52 g·kg^-1）， Shaoyaotang low-dose group （3.56 g·kg^-1）， Shaoyaotang medium-dose group （7.12 g·kg^-1） and Shaoyaotang high-dose group （14.24 g·kg^-1）， with 20 mice in each group. The blank control group and the Shaoyaotang without model group received a single intraperitoneal injection of physiological saline （10 mg·kg^-1）， while the other five groups were given a single intraperitoneal injection of azoxymethane （AOM） （10 mg·kg^-1）. After 1 week， the mice were given drinking water containing 2% dextran sulfate sodium （DSS） for 1 week， followed by normal drinking water for 2 weeks. This cycle was repeated three times over a total period of 14 weeks to establish the CAC mouse model. Each group was administered gavage once daily for 2 weeks starting on the 14^th day of the experiment， followed by three times a week until the end of the experiment. The body weight of the mice was recorded weekly. Mice were sacrificed on the 28^th and 98^th days of the experiment. After dissection， the colon length， colon weight， spleen weight， tumor size， and tumor number were measured. Hematoxylin and eosin （HE） staining was used to assess the pathological morphology of colon tumor tissue. Flow cytometry was used to detect MDSCs， regulatory T cells （Tregs）， CD4⁺ T cells， CD8⁺ T cells， and the CD4⁺/CD8⁺ T cell ratio in the spleen. Immunohistochemistry was used to detect the expression levels of programmed cell death protein-1 （PD-1）， programmed cell death ligand 1 （PD-L1）， phosphorylated AMP-activated protein kinase （p-AMPK）， phosphorylated nuclear factor-κB （p-NF-κB）， and hypoxia-inducible factor 1α （HIF-1α） in the colon tissue. ResultsOn day 14， compared with the blank group， the body weight of the model group was significantly reduced （P<0.01）， reaching its lowest point on day 28 （23.39 ± 0.95 ） g. On days 28 and 98， compared with the blank group， the colon length in the model group was significantly shortened （P<0.01）， the colon index significantly increased （P<0.01）， the spleen index significantly increased （P<0.01）， and the tumor load significantly increased （P<0.01）. HE staining showed that in the model group， tumor cells， a large number of inflammatory cell infiltrates， goblet cell disappearance， and crypt loss were observed. In each dose group of Shaoyaotang， the damage to the colonic mucosa， inflammatory cell infiltration， and crypt structure destruction were alleviated. Compared with the model group， the body weight of mice in each dose group of Shaoyaotang increased. On day 98， the colon length was significantly increased （P<0.01）， the colon index significantly decreased （P<0.01）， the spleen index significantly decreased （P<0.01）， and the tumor burden significantly decreased （P<0.01） in each Shaoyaotang dose group. On days 28 and 98， MDSCs and Tregs in the spleen of the medium- and high-dose Shaoyaotang groups were significantly reduced （P<0.01）， while CD4⁺ T cells and the CD4⁺/CD8⁺ T cell ratio were significantly increased （P<0.01）. The proportion of CD8⁺ T cells in the spleen and the expression levels of PD-1 and PD-L1 in the colon tissues of mice in each Shaoyaotang dose group were significantly increased to varying degrees （P<0.05， P<0.01）. On days 28 and 98， the expression of p-AMPK-positive cells in the colon tissue of the medium- and high-dose Shaoyaotang groups was significantly increased （P<0.01）， while the expression of p-NF-κB and HIF-1α was significantly reduced （P<0.01）. ConclusionShaoyaotang can regulate MDSC recruitment and modulate the immune function of T lymphocyte subsets to inhibit the occurrence and development of AOM/DSS-induced CAC in mice. The mechanism may be related to the activation of the AMPK/NF-κB/HIF-1α pathway.

Objective To investigate the effect of sal-like gene 2(Sall2)gene overexpression on the progression of disease in human superoxide dismutase 1(hSOD1)-G93A mutant amyotrophic lateral sclerosis(ALS)transgenic mice,with the aim of identifying potential therapeutic targets for ALS gene therapy.Methods Differential Sall2 gene were screened through bioinformatics analysis.Forty-eight ALS transgenic mice were selected for this study.AAV-PHP.eB-Sall2 adeno-associated virus with a neuron-specific promoter,human synapsin I(hSyn),was constructed and administered via tail vein injection to six-week-old mice.In parallel,the same litter of ALS mice received an injection of AAV-PHP.eB-GFP.The staining of Sall2 and neuron-specific nuclear protein(NeuN)/GFAP in the spinal cord and cerebral cortex of mice were detected through immunofluorescent double-label staining technology.The survival period,weight changes,exercise ability,and electromyographic changes of the gastrocnemius muscle were detected.The morphological changes in the spinal cord anterior horn neurons were detected through Nissl staining.The effect of Sall2 gene overexpression on the expression of the cell cycle protein E1(cyclin E1)was investigated through Western blotting.Results Bioinformatics analysis showed out that Sall2 was differentially expressed in ALS mice.Compared with ALS mice in the control group,the Sall2 protein expression of ALS mice in the overexpressing Sall2 gene group increased in both the spinal cord and cerebral cortex,and the Sall2 integral absorbance values of Sall2+/NeuN+double-positive cells were higher.The survival time of ALS mice in the Sall2 gene overexpressing group was prolonged,the rate of weight loss was slowed down,the performance in the rotarod and inverted grid tests was improved with longer times,and the positive sharp waves and fibrillation potentials in the gastrocnemius electromyography were reduced.The number of Nissl bodies labeled neurons increased in the spinal cord anterior horn of the Sall2 gene overexpressing mice,and the condition of neuronal damage was improved.Overexpression of the Sall2 gene also reduced the expression of cyclin E1 in both the spinal cord and cerebral cortex of ALS transgenic mice.Conclusion Overexpression of the Sall2 gene can delay disease progression and improve motor performance in ALS transgenic mice,affecting the expression of cyclin E1,thus exerting a therapeutic effect on these mice.

Based on ultra-high performance liquid chromatography-quadrupole-Exactive Orbitrap mass spectrometry(UPLC-Q-Exactive Orbitrap-MS) technology and network pharmacology, this study explored the pharmacodynamic substances and potential mechanisms of Huazhuo Sanjie Chubi Decoction in the treatment of gouty arthritis(GA). UPLC-Q-Exactive Orbitrap-MS technology was used to identify the components in Huazhuo Sanjie Chubi Decoction, and the qualitative analysis of its active ingredients was carried out, with a total of 184 active ingredients identified. A total of 897 active ingredient targets were screened through the PharmMapper database, and 491 GA-related disease targets were obtained from the OMIM, GeneCards, CTD databases. After Venn analysis, 60 intersecting targets were obtained. The component target-GA target network was constructed through the Cytoscape platform, and the STRING database was used to construct a protein-protein interaction network, with 16 core targets screened. The core targets were subjected to Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses, and the component-target-pathway network was constructed. It was found that the main active ingredients of the formula for the treatment of GA were phenols, flavonoids, alkaloids, and terpenoids, and the key targets were SRC, MMP3, MMP9, REN, ALB, IGF1R, PPARG, MAPK1, HPRT1, and CASP1. Through GO analysis, it was found that the treatment of GA mainly involved biological processes such as lipid response, bacterial response, and biostimulus response. KEGG analysis showed that the pathways related to the treatment of GA included lipids and atherosclerosis, neutrophil extracellular traps(NETs), IL-17, and so on. In summary, phenols, flavonoids, alkaloids, and terpenoids may be the core pharmacodynamic substances of Huazhuo Sanjie Chubi Decoction in the treatment of GA, and the pharmacodynamic mechanism may be related to SRC, MMP3, MMP9, and other targets, as well as lipids and atherosclerosis, NETs, IL-17, and other pathways.
Drugs, Chinese Herbal/therapeutic use* ; Network Pharmacology ; Arthritis, Gouty/metabolism* ; Chromatography, High Pressure Liquid/methods* ; Humans ; Mass Spectrometry/methods* ; Protein Interaction Maps/drug effects*

This study aims to explore the effects of Buzhong Yiqi Decoction(BYD) on the cyclic guanosine monophosphate-adenosine monophosphate synthase(cGAS)-stimulator of interferon genes(STING) signaling pathway in the mouse model of autoimmune thyroiditis(AIT) and the mechanism of BYD in alleviating the immune injury. Forty-eight NOD.H-2~(h4) mice were assigned into normal, model, low-, medium-, and high-dose BYD, and selenium yeast tablets groups(n=8). Mice of 8 weeks old were treated with 0.05% sodium iodide solution for 8 weeks for the modeling of AIT and then administrated with corresponding drugs by gavage for 8 weeks before sampling. High performance liquid chromatography was employed to measure the astragaloside Ⅳ content in BYD. Hematoxylin-eosin staining was employed to observe the pathological changes in the mouse thyroid tissue. Enzyme-linked immunosorbent assay was employed to measure the serum levels of thyroid peroxidase antibody(TPO-Ab), thyroglobulin antibody(TgAb), and interferon-γ(IFN-γ). Flow cytometry was employed to detect the distribution of T cell subsets in the spleen. The immunohistochemical method was used to detect the expression of cGAS, STING, TANK-binding kinase 1(TBK1), and interferon regulatory factor 3(IRF3). Real-time PCR and Western blot were employed to determine the mRNA and protein levels, respectively, of markers related to the cGAS-STING signaling pathway in the thyroid tissue. The results showed that the content of astragaloside Ⅳ in BYD was(7.06±0.08) mg·mL~(-1). Compared with the normal group, the model group showed disrupted structures of thyroid follicular epithelial cells, massive infiltration of lymphocytes, and elevated levels of TgAb and TPO-Ab. Compared with the model group, the four treatment groups showed intact epithelial cells, reduced lymphocyte infiltration, and lowered levels of TgAb and TPO-Ab. Compared with the normal group, the model group showed increases in the proportions of Th1 and Th17 cells, a decrease in the proportion of Th2 cells, and an increase in the IFN-γ level. Compared with the model group, the four treatment groups presented decreased proportions of Th1 and Th17 cells and lowered levels of IFN-γ, and the medium-dose BYD group showed an increase in the proportion of Th2 cells. Compared with the normal group, the modeling up-regulated the mRNA levels of cGAS, STING, TBK1, and IRF3 and the protein levels of cGAS, p-STING, p-TBK1, and p-IRF3. Compared with the model group, the four treatment groups showed reduced levels of cGAS, STING, TBK1, and IRF3-positive products, down-regulated mRNA levels of cGAS, STING, and TBK1, and down-regulated protein levels of cGAS and p-STING. The high-dose BYD group showed down-regulations in the mRNA level of IRF3 and the protein levels of p-TBK1 and p-IRF3. The above results indicate that BYD can repair the imbalance of T cell subsets, alleviate immune injury, and reduce thyroid lymphocyte infiltration in AIT mice by inhibiting the cGAS-STING signaling pathway.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Signal Transduction/drug effects* ; Thyroiditis, Autoimmune/metabolism* ; Mice ; Membrane Proteins/metabolism* ; Mice, Inbred NOD ; Humans ; Female ; Nucleotidyltransferases/metabolism* ; Male ; Disease Models, Animal