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.

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.

Objective To analyze the nonlinear relationship between hypothermic machine perfusion (HMP) parameters and delayed graft function (DGF) and optimize the construction of a predictive model for DGF. Methods The data of 923 recipients who underwent kidney transplantation from deceased donors were retrospectively analyzed. According to the occurrence of DGF, the recipients were divided into DGF group (n=823) and non-DGF group (n=100). Donor data, HMP parameters and recipient data were analyzed for both groups. The nonlinear relationship between HMP parameters and the occurrence of DGF was explored based on restricted cubic splines (RCS). Over-sampling, under-sampling and balanced sampling were used to address the imbalance in the proportion of DGF to construct logistic regression predictive models. The area under the curve (AUC) of each model was compared in the validation set, and a nomogram model was constructed. Results Donor BMI, cold ischemia time of the donor kidney, and HMP parameters (initial and final pressures, resistance, and perfusion time) were significantly different between the DGF and non-DGF groups (all P<0.05). The RCS analysis revealed a threshold-like nonlinear relationship between HMP parameters and the risk of DGF. Among the models constructed using different sampling methods, the balanced sampling model had the highest AUC. Using this model, a nomogram was constructed to stratify recipients based on risk scores. Recipients in the high-risk group had higher serum creatinine levels at 1, 6, and 12 months after kidney transplantation compared to those in the low-risk group (all P<0.05). Conclusions There is a nonlinear relationship between HMP parameters and the risk of DGF, and the threshold is helpful for organ quality assessment and monitoring of graft function after transplantation. The predictive model for DGF constructed on the base of balanced sampling algorithms helps perioperative decision-making and postoperative graft function monitoring of kidney transplantation.

It is proposed that cold qi-induced accumulation encapsulates the core pathogenesis of the inflammation-cancer transformation in inflammatory bowel disease （IBD）. Cold pathogens may serve as the initiating factor. When first invading the intestines， cold pathogens obstruct the flow of qi； over time， the lingering cold impairs the middle jiao （焦）， eventually leading to the accumulation of cold-phlegm and blood stasis. Based on the progressive nature of this transformation， the process can be divided into three stages， active stage， remission stage， and carcinogenic stage. In the active stage， the main pathogenesis involves stagnation of cold qi and accumulation of damp-heat in the intestines； in the remission stage， cold qi impairs the spleen， disrupting its transport and transformation functions； and in the carcinogenic stage， the mechanisms include cold-induced accumulation， phlegm accumulation from cold， and stagnation of cold and blood stasis. Accordingly， the treatment strategies are proposed.In the active stage， regulating qi， relieving stagnation， and harmonizing cold and heat； in the remission stage， warming yang， dispersing cold， tonifying qi， and strengthening the spleen； and in the carcinogenic stage， promoting qi circulation， dispersing cold， resolving phlegm， activating yang， and eliminating stasis to remove accumulation. These approaches aim to interrupt the transformation of IBD into colorectal cancer.

OBJECTIVES: To investigate the impact of high expression of transmembrane and coiled helix structural domain 1 (TMCO1) on prognosis of gastric cancer and the possible mechanisms. METHODS: TMCO1 expression in gastric cancer and its effect on gastric cancer progression and prognosis were analyzed using publicly available databases and clinical data of patients undergoing radical surgery in our hospital, and its possible biological functions were explored using KEGG and GO analyses. In gastric cancer HGC-27 cells, the effects of lentivirus-mediated TMCO1 overexpression and TMCO1 silencing on cell apoptosis, proliferation, invasion and migration were examined. RESULTS: TMCO1 expression was significantly elevated in gastric cancer tissues (P<0.05), and its high expression was positively correlated with cancer progression (P<0.001) and a lowered postoperative 5-year survival rate of the patients (P<0.05). Bioinformatic analyses suggested that TMCO1 may affect gastric cancer cell apoptosis via Wnt signaling. In HGC-27 cells, TMCO1 overexpression significantly promoted tumor cell proliferation, inhibited cell apoptosis, and enhanced cell migration and invasion, whereas TMCO1 silencing produced the opposite effects. Western blotting showed that β-catenin levels were significantly upregulated in TMCO1-overexpressing cells and downregulated in cells with TMCO1 silencing. CONCLUSIONS TMCO1 is overexpressed in gastric cancer tissues, and its high expression promotes gastric cancer progression and affects long-term prognosis of the patients possibly by activating the Wnt/ β-catenin signaling pathway to inhibit apoptosis of gastric cancer cells.
Humans ; Stomach Neoplasms/metabolism* ; Apoptosis ; Prognosis ; Cell Line, Tumor ; Cell Proliferation ; Cell Movement ; Wnt Signaling Pathway ; beta Catenin/metabolism* ; Gene Expression Regulation, Neoplastic

In order to investigate whether the effect of Yuxuebi Tablets on the peripheral and central inflammation resolution of mice with inflammatory pain is related to their regulation of G protein-coupled receptor 37(GPR37), an inflammatory pain model was established by injecting complete Freund's adjuvant(CFA) into the paws of mice, with a sham-operated group receiving a similar volume of normal saline. The mice were assigned randomly to the sham-operated group, model group, ibuprofen group(91 mg·kg~(-1)), and low-, medium-, and high-dose groups of Yuxuebi Tablets(60, 120, and 240 mg·kg~(-1)). The drug was administered orally from days 1 to 19 after modeling. Von Frey method and the hot plate test were used to detect mechanical pain thresholds and heat hyperalgesia. The levels of interleukin-10(IL-10) and transforming growth factor-beta(TGF-β) in the spinal cord were quantified using enzyme-linked immunosorbent assay(ELISA), and the mRNA and protein expression of GPR37 in the spinal cord was measured by real-time quantitative reverse transcription PCR(qRT-PCR) and Western blot. Additionally, immunofluorescence was used to detect the expression of macrosialin antigen(CD68), mannose receptor(MRC1 or CD206), and GPR37 in dorsal root ganglia, as well as the expression of calcium-binding adapter molecule 1(IBA1), CD206, and GPR37 in the dorsal horn of the spinal cord. The results showed that compared with those of the sham-operated group, the mechanical pain thresholds and hot withdrawal latency of the model group significantly declined, and the expression of CD68 in the dorsal root ganglia and the expression of IBA1 in the dorsal horn of the spinal cord significantly increased. The expression of CD206 and GPR37 significantly decreased in the dorsal root ganglion and dorsal horn of the spinal cord, and IL-10 and TGF-β levels in the spinal cord were significantly decreased. Compared with those of the model group, the mechanical pain thresholds and hot withdrawal latency of the high-dose group of Yuxuebi Tablets significantly increased, and the expression of CD68 in the dorsal root ganglion and IBA1 in the dorsal horn of the spinal cord significantly decreased. The expression of CD206 and GPR37 in the dorsal root ganglion and dorsal horn of the spinal cord significantly increased, as well as IL-10 and TGF-β levels in the spinal cord. These findings indicated that Yuxuebi Tablets may reduce macrophage(microglial) infiltration and foster M2 macrophage polarization by enhancing GPR37 expression in the dorsal root ganglia and dorsal horn of the spinal cord of CFA-induced mice, so as to improve IL-10 and TGF-β levels, promote resolution of both peripheral and central inflammation, and play analgesic effects.
Inflammation/genetics* ; Pain/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Animals ; Mice ; Freund's Adjuvant/pharmacology* ; Ibuprofen ; Pain Threshold/drug effects* ; Hyperalgesia/genetics* ; Ganglia, Spinal ; Interleukin-10/genetics* ; Transforming Growth Factor beta/genetics* ; Reverse Transcriptase Polymerase Chain Reaction ; Tablets ; Receptors, G-Protein-Coupled

The inheritance, innovation, and development of traditional Chinese medicine(TCM) need to be based on Chinese medicinal materials. The TCM seed industry is the source of TCM production, which is related to the stable supply and quality safety of TCM. This paper summarizes the basic situation of the TCM seed industry and introduces relevant policies and regulations to TCM seeds in the seed industry and the TCM field. At present, the Management Measures of TCM Seeds and Seedlings has not yet promulgated, and TCM seeds are classified as non-major crops in the category of crops for management. This paper also describes the current situation of TCM seed and seedling system construction, which is in the development stage, from six aspects, including the construction of TCM seed industry technical support system; the establishment of TCM seed standard; the construction of germplasm resource preservation system; TCM seed testing, variety registration, and variety protection; production and management of TCM seeds; TCM seed supervision. According to the development status of the TCM seed industry, four problems are put forward, including imperfect systems and standards relevant to TCM seeds, insufficient supervision and law enforcement regarding TCM seeds, insufficient policy measures and capital investment to promote the development of the industry, and the industry's falling into a low-level cycle.Accordingly, four suggestions are provided, including improving laws, regulations, and policies, perfecting standards and norms,strengthening supervision and law enforcement, and promoting support system construction, in order to boost the high-quality development of the TCM seed industry.
Seeds/chemistry* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/standards* ; Plants, Medicinal/chemistry*

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