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 analyze the impact of premature death due to four major chronic diseases on life expectancy in Yangpu District, Shanghai Municipality from 2010 to 2021, so as to provide the evidence for formulating chronic disease prevention and control strategies. Methods : Mortality data of registered residents in Yangpu District from 2010 to 2021 were collected through the Death Information Registration and Management System of the Shanghai Municipal Disease Control and Prevention Information Management Platform. The premature death probability of malignant tumors, diabetes, cardiovascular and cerebrovascular diseases, and chronic respiratory diseases, and life expectancy of residents were calculated using the abridged life table method. Trends in premature death probability for four types of chronic diseases were analyzed using the average annual percent change (AAPC). The impact of premature death probability due to four chronic diseases on life expectancy was assessed by Arriaga's decomposition method. Results : The premature death probability due to four major chronic diseases in Yangpu District decreased from 9.88% in 2010 to 9.22% in 2021, showing an overall declining trend (AAPC=-0.540%, P<0.05). Among females, the premature death probability declined from 6.71% to 4.90% (AAPC=-2.715%, P<0.05), whereas no statistically significant trend was observed in males (P>0.05). Life expectancy increased from 82.52 years in 2010 to 84.50 years in 2021, with an overall upward trend (AAPC=0.244%, P<0.05). Life expectancy rose by 1.71 years for males and 2.34 years for females (AAPC=0.197% and 0.303%,both P<0.05). Declines in premature death probability from malignant tumors (AAPC=-0.967%, P< 0.05) and chronic respiratory diseases (AAPC=-3.071%, P<0.05) contributed to gains in life expectancy of 0.30 years and 0.03 years, with contribution rates of 12.18% and 1.29%, respectively. Changes in premature death probability due to diabetes as well as cardiovascular and cerebrovascular diseases were not statistically significant (both P>0.05), resulting in reductions in life expectancy of 0.05 years and 0.10 years, with contribution rates of -2.40% and -5.05%, respectively. Notably, an increase in premature death probability due to cardiovascular and cerebrovascular diseases among males (AAPC=1.673%) contributed to a decrease of 0.22 years in male life expectancy, whereas a decrease among females (AAPC=-3.824%) contributed to an increase of 0.03 years in female life expectancy, with contribution rates of -13.03% and 1.14%, respectively. Conclusions From 2010 to 2021, Yangpu District experienced an overall decline in premature death probability due to four major chronic diseases and an increase in life expectancy. Greater attention should be paid to the negative impacts of premature death probability from diabetes as well as cardiovascular and cerebrovascular diseases among males on life expectancy.

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by the selective loss of dopaminergic neurons in the substantia nigra pars compacta and the pathological accumulation ofα‑synuclein. Although extensive progress has been made in elucidating its pathogenesis, current therapeutic approaches remain largely symptomatic, and effective disease-modifying treatments are still unavailable. Increasing evidence indicates that PD is driven by the interaction of multiple pathological processes, including neuroinflammation, iron homeostasis dysregulation and ferroptosis, endoplasmic reticulum (ER) stress, mitochondrial dysfunction, oxidative stress, and impaired protein homeostasis, which together contribute to neuronal vulnerability and degeneration. Fibroblast growth factors (FGFs) comprise a family of 22 ligands that play important roles in neural development, stress responses, metabolic regulation, and the maintenance of nervous system homeostasis. Recent studies have shown that several FGF family members, such as FGF1, FGF2, FGF9, and FGF21, exert neuroprotective effects in cellular and animal models of PD. These effects include the regulation of inflammatory responses, oxidative stress, iron homeostasis, cellular stress adaptation, and neuronal survival. Compared with therapeutic strategies targeting a single pathogenic pathway, FGFs appear to influence multiple disease-related processes, suggesting their potential relevance to the complex pathophysiology of PD. Experimental evidence indicates that altered FGF signaling may contribute to dopaminergic neuron dysfunction through the coordinated regulation of several interconnected mechanisms. FGFs have been reported to modulate neuroinflammation by affecting the activation of microglia and astrocytes, thereby influencing the inflammatory environment in the central nervous system. In addition, FGFs are involved in the regulation of iron homeostasis and ferroptosis, partly through antioxidant signaling pathways associated with NRF2, SLC7A11, and GPX4. Moreover, FGFs can alleviate ER stress and mitochondrial dysfunction by activating intracellular signaling pathways such as PI3K/AKT, AMPK-PGC-1α, as well as SIRT1-dependent programs, which support cellular energy metabolism and redox balance. Recent advances in single-cell and spatial transcriptomic studies further suggest that FGF signaling is not limited to neuron-intrinsic mechanisms but also involves interactions among different glial cell types. Altered FGF ligand-receptor communication between astrocytes and oligodendrocytes has been observed in PD models and is associated with increased susceptibility of dopaminergic neurons to oxidative stress and ferroptosis. These findings indicate that the biological effects of FGFs are influenced by cell type and disease stage and may vary under different pathological conditions. In this review, we summarize recent progress in understanding the roles of FGF family members in PD, with a focus on their involvement in iron homeostasis dysregulation and ferroptosis, neuroinflammation, cellular stress responses, and neuronal protection and regeneration. By integrating current evidence, this review aims to provide a clearer understanding of how FGFs participate in PD pathogenesis and to offer a theoretical basis for future studies exploring their potential value in disease-modifying therapeutic strategies.

BACKGROUND:BCR/ABL gene is a specific gene of Ph chromosome-positive acute lymphoblastic leukemia,and its expression level has become a sensitive indicator for monitoring minimal residual disease before and after allogeneic hematopoietic stem cell transplantation.However,whether the expression level of BCR/ABL gene before transplantation affects the efficacy of transplantation and how to guide the early intervention of relapse with tyrosine kinase inhibitors after transplantation is still inconclusive.OBJECTIVE:To explore the relationship between BCR/ABL gene expression and recurrence in patients with Ph chromosome positive acute lymphoblastic leukemia before and after related and allogeneic hematopoietic stem cell transplantation.METHODS:Twenty-four patients with Ph chromosome positive acute lymphoblastic leukemia who achieved complete hematological remission and underwent allogeneic hematopoietic stem cell transplantation were selected at the Affiliated Hospital of North China University of Science and Technology between January 2015 and December 2022.Real time fluorescence quantitative polymerase chain reaction was used to dynamically detect the expression levels of BCR/ABL genes during treatment,representing minimal residual disease.Based on BCR/ABL gene expression,tyrosine kinase inhibitors combined with chemotherapy was administered before transplantation to select the timing of allogeneic hematopoietic stem cell transplantation.After transplantation,the disease status was evaluated to guide the use of tyrosine kinase inhibitors,and an early intervention plan for recurrence was developed.RESULTS AND CONCLUSION:Follow-up was until December 2023,with a median follow-up time of 49(12-82)months.There were 8 cases of hematological recurrence,with a median recurrence time of 14(8-39)months and a cumulative recurrence rate of 33％(8/24).Univariate analysis showed that recurrence after allogeneic hematopoietic stem cell transplantation was not significantly correlated with gender,age,extramedullary complications,time from diagnosis to transplantation,HLA typing,acute graft-versus-host disease,and chronic graft-versus-host disease(P＞0.05).There was a significant correlation between the relief treatment course and minimal residual disease levels before transplantation.The second hematology completely resolution and positive minimal residual disease before transplantation had a higher hematological recurrence rate(P＜0.05).The 3-year cumulative recurrence rate,disease-free survival rate,and overall survival rate were 27％,63％,and 74％;the 5-year cumulative recurrence rate,disease-free survival rate,and overall survival rate were 38％,57％,and 74％,respectively.It is concluded that Ph chromosome positive acute lymphoblastic leukemia patients with BCR/ABL gene positive before transplantation have a higher recurrence rate.BCR/ABL gene expression after transplantation can guide the application of tyrosine kinase inhibitors and serve as a basis for early intervention in recurrence.

BACKGROUND:BCR/ABL gene is a specific gene of Ph chromosome-positive acute lymphoblastic leukemia,and its expression level has become a sensitive indicator for monitoring minimal residual disease before and after allogeneic hematopoietic stem cell transplantation.However,whether the expression level of BCR/ABL gene before transplantation affects the efficacy of transplantation and how to guide the early intervention of relapse with tyrosine kinase inhibitors after transplantation is still inconclusive.OBJECTIVE:To explore the relationship between BCR/ABL gene expression and recurrence in patients with Ph chromosome positive acute lymphoblastic leukemia before and after related and allogeneic hematopoietic stem cell transplantation.METHODS:Twenty-four patients with Ph chromosome positive acute lymphoblastic leukemia who achieved complete hematological remission and underwent allogeneic hematopoietic stem cell transplantation were selected at the Affiliated Hospital of North China University of Science and Technology between January 2015 and December 2022.Real time fluorescence quantitative polymerase chain reaction was used to dynamically detect the expression levels of BCR/ABL genes during treatment,representing minimal residual disease.Based on BCR/ABL gene expression,tyrosine kinase inhibitors combined with chemotherapy was administered before transplantation to select the timing of allogeneic hematopoietic stem cell transplantation.After transplantation,the disease status was evaluated to guide the use of tyrosine kinase inhibitors,and an early intervention plan for recurrence was developed.RESULTS AND CONCLUSION:Follow-up was until December 2023,with a median follow-up time of 49(12-82)months.There were 8 cases of hematological recurrence,with a median recurrence time of 14(8-39)months and a cumulative recurrence rate of 33％(8/24).Univariate analysis showed that recurrence after allogeneic hematopoietic stem cell transplantation was not significantly correlated with gender,age,extramedullary complications,time from diagnosis to transplantation,HLA typing,acute graft-versus-host disease,and chronic graft-versus-host disease(P＞0.05).There was a significant correlation between the relief treatment course and minimal residual disease levels before transplantation.The second hematology completely resolution and positive minimal residual disease before transplantation had a higher hematological recurrence rate(P＜0.05).The 3-year cumulative recurrence rate,disease-free survival rate,and overall survival rate were 27％,63％,and 74％;the 5-year cumulative recurrence rate,disease-free survival rate,and overall survival rate were 38％,57％,and 74％,respectively.It is concluded that Ph chromosome positive acute lymphoblastic leukemia patients with BCR/ABL gene positive before transplantation have a higher recurrence rate.BCR/ABL gene expression after transplantation can guide the application of tyrosine kinase inhibitors and serve as a basis for early intervention in recurrence.

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.

Integrated metabolomic and lipidomic profiling,utilizing liquid chromatography coupled with high-resolution mass spectrometry(LC-HRMS),has emerged as a pivotal strategy for biomarker discovery.However,the inherent polarity disparity between metabolites and lipids complicates simultaneous analysis.To address this,a dual-stationary phase polarity-extended liquid chromatography(PELC)system was developed,which surpassed conventional one-dimensional LC(1D-LC)by enabling comprehensive coverage of both polar and non-polar compounds within a single injection.This system enhanced chromatographic resolution,peak capacity,and throughput while minimizing analytical variability.Extracellular vesicles(EVs),lipid bilayer-enclosed nanoparticles ubiquitously present in biofluids,had gained prominence as reservoirs of cancer biomarkers due to their cargo stability and pathophysiological relevance.Herein,the application of PELC-HRMS for concurrent metabolome-lipidome profiling in EVs was pioneered.A total of 193 metabolites were identified using this technique coupled with MS-DIAL software and Human Metabolome Database.Subsequently,this technique was employed to explore potential biomarkers for prostate cancer(PCa).Multivariate analysis identified 17 differentially abundant metabolites in PCa,implicating dysregulated pathways including purine metabolism,starch and sucrose metabolism,galactose metabolism,cysteine and methionine metabolism,and biosynthesis of unsaturated fatty acids.Notably,creatine(AUC=0.92)and DG 42:5(AUC=0.80)demonstrated robust diagnostic efficacy,attributable to their broad polarity ranges and EV-specific enrichment.This study established PELC as a high-fidelity platform for multi-omics integration in complex biospecimens,advancing mechanistic insights into metabolic rewiring and disease pathophysiology.

Objective To investigate the correlation of monocyte count(MONO)to high density lipopro-tein-cholesterol(HDL-C)ratio(MHR)and systemic immune-inflammation index(SII)with diabetic retinop-athy(DR).Methods Patients with type 2 diabetes mellitus(T2DM)admitted to the hospital from June 2020 to May 2023 were selected as the research objects.According to the presence or absence of DR,the patients were divided into non-retinopathy group(NDR group)and DR Group.The differences in basic information,blood routine,and biochemical indexes between the two groups were analyzed,and the MHR and SII were cal-culated.Multivariate Logistic regression was used to analyze the risk factors for DR.Spearman correlation a-nalysis was used to analyze the correlation between risk factors and DR.The receiver operating characteristic(ROC)curve was used to evaluate the value of MHR and SII in predicting DR in T2DM patients.Results A total of 291 T2DM patients were enrolled,including 135 patients in the NDR group and 156 patients in the DR group.Compared with the NDR group,duration of diabetes was significantly prolonged(P<0.05),glycosy-lated hemoglobin(HbA1c),creatinine,fasting plasma glucose(FPG),total cholesterol(TC),platelet count(PLT),MHR and SII were increased(P<0.05),and high density lipoprotein-cholesterol(HDL-C)was de-creased(P<0.05)in the DR Group.Spearman correlation analysis showed that DR was positively correlated with duration of diabetes,FPG,HbA1c,PLT,MHR and SII(P<0.05),and negatively correlated with HDL-C(P<0.05).Multivariate Logistic regression analysis showed that gender(OR=0.151,95%CI 0.052-0.432,P<0.001),history of heavy drinking(OR=7.199,95%CI 2.845-18.216,P<0.001),duration of di-abetes(OR=1.570,95%CI 1.354-1.821,P<0.001),HbA1c(OR=1.218,95%CI 1.013-1.464,P=0.036),MHR(OR=1.054,95%CI 1.028-1.080,P<0.001)and SII(OR=1.002,95%CI 1.001-1.003,P=0.002)were independent influencing factors for DR patients.ROC curve analysis showed that the area un-der the curve(AUC)of MHR and SII in predicting the development of T2DM to DR was 0.696 and 0.567,re-spectively.The AUC of MHR and SII combined in predicting DR was 0.702.Conclusion MHR and SII are closely related to the incidence of DR,and both have certain predictive value for DR,and the predictive value of the combined of MHR and SII is higher.

Objective:To prepare decellularized extracellular matrix (dECM)-gelatin methacryloyl (GelMA) composite hydrogels and to study their effects on hepatocyte proliferation.Methods:Hepatic dECM was prepared by elution, and GelMA hydrogel and 10%, 30% and 50% dECM-GelMA composite hydrogels were prepared by pepsin solubilization. The morphology of normal liver and dECM liver was observed by eyes and scanning electron microscopy using hematoxylin-eosin, Sirius red and periodate-Schiff staining, respectively. The internal structure of the dECM-GelMA composite hydrogels was observed by scanning electron microscopy, and the pore diameter was measured. Liver HL-7702 cells were co-cultured with GelMA hydrogel and 10%, 30% and 50% dECM-GelMA composite hydrogels, and the cell proliferation viability was determined by cell counting kit-8. The expression of proliferating cell nuclear antigen (PCNA), Wnt family protein 5a (Wnt5a), β-catenin, extracellular-regulated protein kinase 1/2 (ERK1/2) and phosphorylated ERK1/2 (p-ERK1/2) were detected by Western blotting. Comparisons were made using independent sample t-test or one-factor analysis of variance. Results:After decellularization, the hepatocyte morphology showed rounded depressions, and the extracellular matrix structure was intact. The GelMA hydrogel and 10%, 30% and 50% dECM-GelMA composite hydrogels showed inernally porous structures. The pore diameter increased from (3.06±1.35) μm in the GelMA hydrogel to (16.01±4.02) μm in the 50% dECM-GelMA composite hydrogel. On the 3rd, 5th and 7th day, the relative cell proliferation was higher in the 50% dECM-GelMA composite hydrogel group than that in the GelMA hydrogel group (1.89±0.04 vs 1.53±0.01, 9.36±0.04 vs 3.89±0.09, 7.15±0.27 vs 4.89±0.15, all P<0.05). The relative expression levels of PCNA, Wnt5a, β-catenin, and p-ERK1/2/ERK1/2 proteins in the 50% dECM-GelMA composite hydrogel group were higher than those in the GelMA hydrogel group (2.14±0.04 vs 1.00±0.03, 2.36±0.09 vs 1.00±0.08, 1.45±0.03 vs 1.00±0.04, 1.43±0.04 vs 1.00±0.01, all P<0.05). Conclusions:A dECM-GelMA composite hydrogel can be prepared, which may promote hepatocyte proliferation by upregulating the phosphorylation of ERK1/2 and activating Wnt/β-catenin signaling pathway.