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 characterize longitudinal trajectories of testicular development in boys and breast development in girls, so as to provide reference data for understanding patterns of pubertal sexual maturation. Methods: Based on the Shanghai Pudong New Area Cohort Study on Growth, Development and Health in Children and Adolescents, a baseline survey was conducted in 2020 using a mult stage cluster random sampling method. A total of 2 184 children who completed all follow ups during the primary school period from 13 elementary schools in Pudong New Area,Shanghai,with annual follow ups during 2021-2025. Testicular volume and Tanner stage of breast development were assessed by professional physicians using standardized visual inspection and palpation. The age distribution of testicular volume and breast development was fitted by using cumulative link mixed models and Turnbull s nonparametric maximum likelihood estimation method. Results: Median ages for testicular volumes of 2, 3, 4 and 5 mL in boys were 7.07, 9.24, 10.29, and 11.57 years old, respectively. Median ages for Tanner breast stages Ⅱ, Ⅲ, Ⅳ, and Ⅴ in girls were 8.55 , 10.17, 11.18, and 13.78 years old, respectively. Based on overweight and obesity, stratified analysis showed that earlier pubertal onset among overweight/obesity children, and the key milestones for pubertal initiation were testicular volume reaching 4 mL in boys and breast Tanner II in girls for 10.29, 10.83; 8.18, 9.00 years. Conclusion Overweight and obesity are associated with earlier pubertal initiation,but there are certain gender and developmental stage specific patterns.

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.

Objective To explore the incidence and risk factors of sarcopenia in non-dialysis patients with stage 5 chronic kidney disease (CKD). Methods Non-dialysis stage 5 CKD patients in Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences from October 2023 to October 2024 were enrolled and divided into the non-sarcopenia group and the sarcopenia group according to lean tissue index (LTI) and handgrip strength (HGS). Demographic data of patients were collected and biochemical indicators were detected. Serum advanced glycation end products (AGEs) were detected by competitive ELISA. Multivariate logistic regression analysis was conducted to analyze the risk factors of sarcopenia in these patients. The diagnostic efficacy of the risk factors was evaluated by the receiver operating characteristic (ROC) curve. Results A total of 102 non-dialysis stage 5 CKD patients with (68.52±7.39) years, were enrolled, including 61 male (59.8%). Among them, 24 were diagnosed with sarcopenia (23.5%). Compared with patients in non-sarcopenia group, patients in sarcopenia group were older and had higher interleukin-6 (IL-6) and AGEs, lower body mass index (BMI) and lower serum albumin (sAlb; P＜0.05). Multivariate logistic regression showed that advanced age (OR＝1.153, 95%CI 1.045–1.273, P＝0.005), higher IL-6 (OR＝1.165, 95%CI 1.042–1.302, P＝0.007)、lower sAlb (OR＝0.675, 95%CI 0.542–0.840, P＝0.001), and higher serum AGEs (OR＝1.105, 95%CI 1.013–1.206, P＝0.024) were independent risk factors of sarcopenia in non-dialysis CKD 5 patients. The areas under the curve (AUC) for the age, IL-6, sAlb, and serum AGEs were 0.896, 0.643, 0.658, and 0.724, respectively. Conclusions Sarcopenia is common in non-dialysis stage 5 CKD patients, and the risk of sarcopenia is higher in non-dialysis stage 5 CKD patients with advanced age, higher IL-6, lower sAlb, and higher serum AGEs.

Objective: To determine the potential genetic causal relationship between sleep related phenotypes and female pubertal onset using the two sample Mendelian randomization approach. Methods: Genetic instrumental variables for sleep and age at menarche were sourced from FinnGen, IEU Open GWAS and GWAS Catalog three publicly available Genome Wide Association Study databases. Causal effects were estimated using the inverse variance weighted method, supplemented by sensitivity analyses and tests for heterogeneity, pleiotropy, and direction. Results: Genetically predicted sleep duration was positively associated with age at menarche ( β =0.61, 95% CI =0.30-0.91, P <0.01). Conversely, overall sleep problems ( β =-0.13, 95% CI =-0.20 to -0.07 ), two specific types of sleep disorders (sleep apnea: β =-0.10, 95% CI =-0.16 to -0.03; insomnia: β =-0.40, 95% CI = -0.69 to -0.11) were causally associated with earlier age at menarche (all P <0.01). Sensitivity analyses confirmed the robustness of these findings with consistent effect directions and no evidence of significant directional pleiotropy. Conclusions The study reveales a genetic causal relationship between sleep and pubertal onset. Adequate sleep duration appears to have a protective effect. These findings suggest that sleep may have a critical regulatory role in the initiation of pubertal development.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Objective To investigate the clinical and pathological characteristics of adrenal cortical carcinoma(ACC),compare differences between hypercortisolism and non-functional ACC,and assess the diagnostic value of indicators such as Ki-67 index.Methods The clinical data of 57 ACC patients admitted to the First Medical Center of Chinese PLA General Hospital from January 2015 to March 2025 were retrospectively analyzed.According to the results of endocrine function assessment,47 of these patients were divided into hypercortisolism group(n=19)and non-functional group(n=28).The differences in clinical and pathological characteristics between the two groups were compared,and non-parametric tests and Spearman correlation analysis were used to explore the relationship between Ki-67 index and tumor stage as well as imaging features.Results Among the 57 patients,there were 20 males and 37 females,with a male-to-female ratio of 1:1.85.The age ranged from 16 to 76 years,and the age at diagnosis was(48.7±13.3)years.The tumor diameter was(10.53±4.14)cm.The tumors were located on the right side in 12 cases(21.1%),on the left side in 34 cases(59.6%),and bilaterally in 11 cases(19.3%).Among them,16 cases(28.1%)were complicated with glucose metabolism disorders,31 cases(54.3%)had hypertension,and 20 cases(35.1%)had hypokalemia.According to ENSAT staging,there were 0 cases in stage Ⅰ,15 cases(26.3%)in stage Ⅱ,24 cases(42.1%)in stage Ⅲ,and 18 cases(31.6%)in stage Ⅳ.Endocrine function assessment was completed in 47 of the 57 patients,including 28 cases(59.6%)of non-functional ACC and 19 cases(40.4%)of hypercortisolism(including 1 case of hypercortisolism combined with increased sex hormone secretion).Compared with non-functional group,hypercortisolism group had a significantly higher prevalence of hypertension(P=0.014),later ENSAT stage(P=0.010),and a higher proportion of hypervascularization(P=0.048).The median Ki-67 index was 20%(10%-40%),showing no significant correlation with either the maximum tumor diameter or SUVmax value,but it was related to ENSAT staging,with Ki-67 index in stageⅣ patients being significantly higher than that in stage Ⅱ(P=0.032).Immunohistochemistry results showed that the positive rate of Inhibin-α was 84.8%,and the positive rate of Melan-A was 40.9%.Conclusions ACC is a rare malignant endocrine tumor.ACC patients with hypercortisolism are more likely to be complicated with hypertension,have later staging,and more common hypervascular manifestations.Clinically,their endocrine function should be prioritized for assessment,and more active treatment strategies should be adopted.Diagnosis should be combined with imaging characteristics(such as hypervascularization)and immunohistochemical indicators(Ki-67,Inhibin-α,Melan-A).The significant increase in Ki-67 is in the advanced stage can serve as an important prognostic indicator to guide individualized treatment.

In this study, the pharmacokinetic characteristics and tissue distribution of cannabidiol(CBD)/γ-polyglutamic acid-g-cholesterol(γ-PGA-g-CHOL) nanomicelles [CBD/(γ-PGA-g-CHOL)NMs] were investigated by pharmacokinetic experiments, and the effect of CBD/(γ-PGA-g-CHOL)NMs on the lipopolysaccharide(LPS)-induced inflammatory damage of cells was evaluated by cell experiments. CBD/(γ-PGA-g-CHOL)NMs were prepared by dialysis. The CBD concentrations in the plasma samples of male SD rats treated with CBD and CBD/(γ-PGA-g-CHOL)NMs were investigated, and the pharmacokinetic parameters were calculated and compared. UPLC-MS/MS was employed to determine the concentration of CBD in tissue samples. The heart, liver, spleen, lung, kidney, and muscle samples were collected at different time points to explore the tissue distribution of CBD and CBD/(γ-PGA-g-CHOL)NMs. The Caco-2 cell model of LPS-induced inflammation was established, and the cell viability, transepithelial electrical resistance(TEER), and secretion levels of inflammatory cytokines were determined to compare the anti-inflammatory activity between the two groups. The results showed that CBD/(γ-PGA-g-CHOL)NMs had the average particle size of(163.1±2.3)nm, drug loading of 8.78%±0.28%, and encapsulation rate of 84.46%±0.35%. Compared with CBD, CBD/(γ-PGA-g-CHOL)NMs showed increased peak concentration(C_(max)) and prolonged peak time(t_(max)) and mean residence time(MRT_(0-t)). Within 24 h, the tissue distribution concentration of CBD/(γ-PGA-g-CHOL)NMs was higher than that of CBD. In addition, both CBD and CBD/(γ-PGA-g-CHOL)NMs significantly enhanced Caco-2 cell viability and TEER, lowered the secretion levels of inflammatory cytokines, and alleviated inflammation. Moreover, CBD/(γ-PGA-g-CHOL)NMs demonstrated stronger anti-inflammatory effect. It can be inferred that γ-PGA-g-CHOL blank nanomicelles are good carriers of CBD, being capable of prolonging the circulation time of CBD in the blood, improving the bioavailability and tissue distribution concentration of CBD, and protecting against LPS-induced inflammatory injury. The findings can provide an experimental basis for the development and clinical application of oral CBD preparations.
Animals ; Cannabidiol/administration & dosage* ; Polyglutamic Acid/analogs & derivatives* ; Humans ; Male ; Rats ; Rats, Sprague-Dawley ; Anti-Inflammatory Agents/administration & dosage* ; Micelles ; Caco-2 Cells ; Cholesterol/pharmacokinetics* ; Tissue Distribution ; Nanoparticles/chemistry*