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.

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 protective effect and mechanism of heat acclimation(HA)on electromagnetic field(EMF)induced hippocampus neuron injury in mice.Methods Forty healthy BALB/c male mice(18～22 g,7 weeks old)were randomly divided into 4 groups(n=10):Control group(Con),HA group(34℃,30 d),EMF group(2 450 MHz,20 min/d,4 weeks)and HA+EMF group(HA preconditioning+EMF).Sucrose preference test was performed to evaluate sucrose preference levels of mice in each group.Tail suspension test and forced swimming test were utilized to observe the immobility time.Morris water maze test was conducted to determine the learning and memory capabilities.Pathological changes in the hippocampus were observed with HE staining.Immunohistochemical assay for Iba1(marker of microglia),CD68(marker of pro-inflammatory phenotype)and CD206(marker of anti-inflammatory phenotype)were used to detect the number and activation phenotype of microglia in the hippocampus.ELISA was applied to measure the levels of TNF-α,IL-1β,TGF-β and IL-10 in the hippocampus of each group.Western blotting was performed to determine the protein levels of HSP70 in the hippocampus.Results As compared with the Con group,the EMF group showed a decreased preference for sucrose(P<0.05),prolonged immobile time in the tail suspension test(P<0.01)as well as in the forced swimming test(P<0.01),extented escape latency on the 7th day(P<0.01),and a decreased time of crossing the platform(P<0.05).EMF exposure resulted in that the hippocampal neurons were in disordered arrangement,loose structure and irregular morphology,with swollen cytoplasm and condensed nuclei,swollen and more microglial cells in the hippocampus(P<0.01),and enhanced relative fluorescence intensity of CD68(P<0.01),but not in CD206 fluorescence intensity(P=0.885).All these findings suggested that activated microglia predominantly exhibited a pro-inflammatory M1 phenotype during this phase.In the hippocampus,the levels of TNF-α and IL-1β were significantly increased,while the levels of IL-10 and TGF-β were significantly decreased(P<0.01).HA treatment reversed the conditions induced by EMF exposure,including better preference for sucrose(P<0.01),shorten immobile time in tail suspension test(P<0.05)and forced swimming test(P<0.01),less escape latency on the 7th day(P<0.01),and improved hippocampal cell injuries.Compared with the Con group,there were more microglial cells in the hippocampus in the HA+EMF group,with increased relative fluorescence intensity of M2 phenotype marker CD206(P<0.01)and decreased CD68 fluorescence intensity(P<0.01).HA treatment also significantly decreased the expression of TNF-α and IL-1β levels(P<0.01),increased the expression of IL-10 and TGF-β(P<0.01),and elevated the protein level of HSP70(P<0.01)when compared with the EMF group.Conclusion HA may ameliorate EMF-induced hippocampus neurons injury in mice by altering the phenotype of activated microglia and inhibiting inflammatory responses.

Objective To explore the pharmacokinetic characteristics of sufentanil in individuals with normal body mass index(BMI),overweight BMI,and different CYP3A4/5 enzyme genotypes.Methods The patients receiving laparoscopic surgery under general anesthesia in the First Affiliated Hospital of Army Medical University from November 2020 to September 2021 were prospectively recruited in this study.Before the operation,the oral swabs were collected from all the patients for genotyping using the human CYP3A4/5 gene kit.Based on the potential impact of combination of their polymorphisms on sufentanil metabolism and the proportion of different genotype combinations of CYP3A4/5 enzymes,the patients were divided into groups I(3A4 homozygous mutation or 3A4 heterozygous mutation+3A5 homozygous mutation),II(3A4 heterozygous mutation+3A5 heterozygous mutation),and III(3A4 wild type or 3A4 heterozygous mutation+3A5 wild type).According to their BMI,they were also assigned into a normal body weight group(18.5～24.0 kg/m2)and an overweight group(24～<28 kg/m2),and the differences in drug metabolism parameters were statistically analyze between the 2 groups.After routine general anesthesia induction(sufentanil 0.5 μg/kg),venous blood samples were collected to detect the changes in its concentration using high performance liquid chromatography-mass spectrometry(HPLC-MS).The pharmacokinetic data of sufentanil were calculated between the normal BMI group and overweight group in all participants and between the 2 body weight groups among those with different genotype combinations.Results Among the 90 participants completing the blood drug concentration test,8 patients had their blood samples contaminated(including 1 case with an anesthesia duration of<2 h),and 3 were excluded due to low weight or overweight.Eventually,79 participants were included in the pharmacokinetic analysis on the normal body weight group and the overweight group.Compared with the normal body weight group,the central compartment volume of distribution in the overweight group was significantly reduced(P<0.05),while no obvious differences were observed between the 2 groups in terms of peripheral compartment volume of distribution,total clearance rate,peripheral compartment clearance rate,distribution half-life,clearance half-life,and area under the blood concentration-time curve.In group Ⅰ(n=26),the overweight patients(n=13)had significantly reduced central compartment volume of distribution,peripheral compartment volume of distribution,and peripheral compartment clearance rate when compared with the normal body weight patients(n=13)(P<0.05),while no differences were observed in other pharmacokinetic parameters.In groups Ⅱ(n=25)and Ⅲ(n=28),the overweight patients and normal body weight patients had no statistical differences in all pharmacokinetic parameters.Conclusion Among the patients with the same genotype combination of CYP3A4/5 mutations,there was no difference in the metabolism of sufentanil between the overweight and normal weight patients.Additionally,in the population of 3A4 homozygous mutation or 3A4 heterozygous mutation+3A5 homozygous mutation,the overweight patients have smaller peripheral distribution range of sufentanil,and weakened metabolic process.

Arsenic is a semi-metal,and lipid-soluble arsenic compounds are one of the widespread forms in the environment and food chain,but there is a lack of standards for lipid-soluble arsenic compounds,which is one of the bottlenecks in the current analytical detection and toxicological studies of organic arsenic.In this study,four saturated arsenic-containing hydrocarbons,AsHC 318,AsHC 332,AsHC 346,and AsHC 374(The number is relative molecular mass),were successfully synthesized in three steps by using dimethylarsinic acid,potassium iodide,sodium hydroxide,and four brominated alkanes(1-Bromotetradecane,1-bromopentadecane,1-bromohexadecane,and 1-bromooctadecane)as raw materials.The structures of these four saturated arsenic-containing hydrocarbons were characterized by proton nuclear magnetic resonance(1H NMR)spectroscopy,13C nuclear magnetic resonance(13C NMR)spectroscopy,and high-resolution mass spectrometry(HR-MS).The yields of the method were 8%-10%,and the synthesized compounds could be used in subsequent toxicity evaluation experiments to assess the toxic effects and mechanisms of action of arsenic-containing hydrocarbons.This study provided an effective method for synthesis of arsenic-containing hydrocarbons,enriching the synthesis methods of arsenic-containing hydrocarbons,and provided raw materials for the subsequent toxicological studies of arsenic-containing hydrocarbons.

Ribonucleic acid(RNA)molecules with repeat expansion sequences can liquid-liquid phase separate into droplet-like condensates,which usually have good fluidity and can dynamically exchange matter and energy with the outside world,so as to play physiological functions.However,when the conditions are changed,the droplets will undergo a phase transition,forming gel-like or solid-like condensates.The change in the morphology of the condensates is closely related to many diseases.In this work,the effects of the RNA repeat length,concentration,cation and pH value on the liquid-liquid phase separation(LLPS)of RNA with CAG repeats were systematically studied,and the molecular structure of the condensates formed by LLPS was analyzed by Raman spectroscopy.This study revealed the molecular basis of the formation of different condensates from the perspective of structural biology,and provided new insights for in-depth understanding of the molecular assembly of RNA phase separation and phase transition.

A centrifugation-free,single-reaction colorimetric method for detection of glucose,utilizing a dual nanozyme cascade system based on gold nanoparticles(AuNPs)and iron-doped carbon dots(FeCDs),was developed in this work.The AuNPs exhibited glucose oxidase-like activity to catalyze glucose oxidation for generation of H2O2,while the FeCDs demonstrated peroxidase-like activity to subsequently catalyze the H2O2-mediated oxidation of 3,3',5,5'-tetramethylbenzidine(TMB).To prevent interference from the blue signal generated by self-aggregation of AuNPs in subsequent quantitative detection,the reaction system was terminated with HCl,converting oxTMB into a stable yellow product.Based on changes in the absorbance at 450 nm of this yellow solution,a quantitative relationship was established between glucose concentration and absorbance at 450 nm(A450).Experimental results demonstrated that this sensor achieved a linear detection range of 44 μmol/L to 11.11 mmol/L(R2=0.993)with a detection limit of 30.68 μmol/L and spiked recoveries of 97.9%-104.7%.By integrating smartphone-based color recognition capabilities,a rapid visual detection platform was established for quantification of glucose through RGB analysis.The validation experimental results using commercial glucose injection samples further confirmed the practical application potential of this methodology.