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.

Objective To identify determinants of subtherapeutic voriconazole(VRCZ)concentrations in allogeneic hematopoietic stem cell transplantation(allo-HSCT)recipients and to develop/validate a nomogram-based risk prediction model.Methods This study retrospectively analyzed 310 VRCZ therapeutic drug monitoring(TDM)measurements from allo-HSCT recipients at 310 patients who under went allo-HSCT surgery at Hebei Yanda Ludaopei Hospital from October 2022 to October 2024 and received VRCZ for the prevention and treatment of invasive fungal infections before transplantion were selected as the study subjects.Cases were stratified into target-concentration group(0.5～5.0μg/ml)and subtherapeutic group(<0.5μg/ml).Through single factor and multiple factor Logistic regression analysis,indeipendent predictive factors forvecz plasma concentration non-compliance were screened,and a column chart prediction model(NPM)was constructed.The performance of the model was evaluateding area under the receiver operating characteristic curve(AUC),Hosmer-Lemeshow(H-L)goodness-of-fit test,and decision curve analysis(DCA).Results Among 310 VRCZ-TDM measurements,71.61%(222/310)achieved target concentrations.Multivariate analysis showed that CYP2C19 intermediate metabolite,daily dose of cyclosporine A(CSA),daily dose of VRCZ,creatinine(Cr)>97 μmol/L,albumin(Alb)and C-reactive protein(CRP)were independent influencing factors for VRCZ blood drug concentration non-compliance(Wald χ2=4.046～13.221,all P＜0.05).The nomogram demonstrated excellent discrimination,calibration(H-L goodness of fit test χ2=2.663,P=0.954),and clinical utility with net benefit across 0.05～0.96 risk thresholds.Conclusion The nomogram incorporating CYP2C19 gene phenotype,daily CSA dosing,daily VRCZ dosing,Cr levels,Alb and CRP provides a validated tool for optimizing VRCZ therapy in allo-HSCT recipients,enabling precision dosing strategies.

Objective This study aims to systematically evaluate the evidence-based medicine of traditional Chinese medicine(TCM)in the treatment of dry eye,analyze its efficacy and differences compared with modern Western medicine treatments,and provide a scientific basis for clinical application.Methods By searching Chinese and English databases(including CNKI,Wanfang Data,PubMed,Cochrane Library,etc.),we included meta-analyses and systematic reviews of TCM treatments for dry eye.Literature was screened according to strict inclusion and exclusion criteria,and relevant data were extracted and integrated for analysis.The Mantel-Haenszel fixed-effects model was used to calculate the relative risk(RR)and mean difference(WMD),with the effect size expressed as a 95％confidence interval,to analyze the efficacy in-dicators of TCM treatment for dry eye.Results A total of 21 articles were finally included,involving various TCM inter-ventions for dry eye(such as Chinese herbal medicine,acupuncture,and TCM external therapies).The results showed that TCM treatment was superior to Western medicine alone in improving the overall clinical efficacy[RR=1.63,95％CI(1.46,1.81),P＜0.05],prolonging tear film break-up time[MD=2.23,95％CI(1.85,2.60),P＜0.05],and increasing tear secretion[MD=1.49,95％CI(1.04,1.94),P＜0.05].In addition,acupuncture,the combination of Chinese herbal medicine and Western medicine,and TCM external therapies all demonstrated unique advantages in improving dry eye symptoms and tear function.Conclusion TCM treatment for dry eye shows significant efficacy in key indicators such as overall clinical efficacy,tear film break-up time,and tear secretion,with a high level of safety.

AIM:To observe the changes of atrial fibrillation susceptibility,and the remodeling of atrial myo-cyte action potential,ultrarapid activation delayed rectifier potassium current(IKur)and transient outward potassium cur-rent(Ito)in elderly mice,and to explore the mechanism of atrial fibrillation from the single cell electrophysiological level.METHODS:The C57BL/6J mice were divided into old group(20 months old)and young group(4 months old).Atrial fi-brillation was induced by esophageal atrial pacing.The atrial myocytes were isolated,and action potential and ion currents were recorded with patch-clamp technique.The associated proteins were detected by Western blot technique.RE-SULTS:(1)Compared with young mice,the total incidence of atrial fibrillation was significantly increased in old mice(20.0%at 4 months old vs 60.0%at 20 months old,P<0.01).(2)The action potential duration of atrial myocytes in aged mice was shortened,and more significantly after stimulation.(3)The density of Ito and IKur in atrial myocytes of aged mice increased significantly,from(12.6±1.4)pA/pF to(21.7±1.1)pA/pF,and from(7.5±1.5)pA/pF to(13.3±2.1)pA/pF,respectively(P<0.01).After stimulation,the current increased more significantly,especially in older atrial cells.Compared with the young mice,the steady-state activation curve of Ito in the atrial myocytes of the aged mice shifted towards the depolarization,suggesting that activation of Ito channels in the aged mice increased at the same voltage stimula-tion.(4)Compared with young group,the expression of KV4.2(generating Ito)and KV1.5(generating IKur)proteins in the atrial tissue of the mice in old group was significantly increased,and the expression of caveolin-3 and end-binding protein 1(EB1)was up-regulated,suggesting that the increases in KV4.2 and KV1.5 total channel proteins and effective proteins in the cell membrane might contribute to the increase in the remodeling of potassium currents in the elderly atrial myo-cytes.CONCLUSION:The incidence of atrial fibrillation in elderly mice is significantly augmented,which may be related to the increases in Ito and IKur in atrial myocytes.The remodeling of potassium currents in elderly atrial myocytes is one of the electrophysiological bases leading to the shortening of action potential duration and the occurrence of atrial fibrillation.

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.

Pancreatic cancer has emerged as one of the most challenging malignancies worldwide,with its high resistance to chemotherapy being the primary cause of treatment failure.Therefore,enhancing the chemosensitivity of pancreatic cancer has become a major focus of current research.In this study,we in-vestigated how Bufotaline,a bufadienolide extracted from the traditional Chinese medicine toad venom,exhibits its antitumor activity.Specifically,we explored the potential of Bufotaline to enhance the chemo-sensitivity of pancreatic cancer cells to Adriamycin and elucidated its underlying molecular mechanisms.Using CCK-8 and colony formation assays,we demonstrated that Bufotaline enhances the inhibitory effect of Adriamycin on the survival of pancreatic cancer cell lines Patu-8988T,Aspc-1,and Patu-8988S.No-tably,Bufotaline treatment reduced the IC50 of Adriamycin in drug-resistant pancreatic cancer cells to lev-els comparable to those in non-resistant cells.Results from Western blot,immunofluorescence,comet as-say,and TUNEL assays revealed that Bufotaline promotes Adriamycin-induced DNA damage in pancreatic cancer cells.RNA-seq analysis of Patu-8988T cells treated with Adriamycin alone or in combination with Bufotaline showed significant changes in gene expression,and qRT-PCR analysis further confirmed that Bu-fotaline downregulates the expression of DNA damage repair proteins NBS1 and RAD50.Moreover,Western blot analysis revealed that Bufotaline reduces the levels of DNA damage response repair proteins,and Im-munofluorescence experiments indicated that Bufotaline inhibits the activation of the ATM/CHK2 signaling pathway.Finally,in a subcutaneous xenograft mouse model,the combination of Adriamycin and Bufotaline treatment significantly suppressed pancreatic cancer cell growth.In conclusion,Bufotaline enhances Adria-mycin-induced chemosensitivity in pancreatic cancer cells;the combination of Adriamycin and Bufotaline downregulates the expression of DNA damage response repair proteins NBS1 and RAD50,and inhibits the ATM/CHK2-mediated DDR signaling pathway,thereby delaying DNA damage repair.