BACKGROUND: Preclinical studies have indicated that Angong Niuhuang Pills (ANP) reduce cerebral infarct and edema volumes. This study aimed to investigate whether ANP safely reduces cerebral infarct and edema volumes in patients with moderate to severe acute ischemic stroke. METHODS: This randomized, double-blind, placebo-controlled pilot trial included patients with acute ischemic stroke with National Institutes of Health Stroke Scale (NIHSS) scores ranging from 10 to 20 in 17 centers in China between April 2021 and July 2022. Patients were allocated within 36 h after onset via block randomization to receive ANP or placebo (3 g/day for 5 days). The primary outcomes were changes in cerebral infarct and edema volumes after 14 days of treatment. The primary safety outcome was severe adverse events (SAEs) for 90 days. RESULTS: There were 57 and 60 patients finally included in the ANP and placebo groups, respectively for modified intention-to-treat analysis. The median age was 66.0 years, and the median NIHSS score at baseline was 12.0. The changes in cerebral infarct volume at day 14 were 0.3 mL and 0.4 mL in the ANP and placebo groups, respectively (median difference: -7.1 mL; interquartile range [IQR]: -18.3 to 2.3 mL, P = 0.30). The changes in cerebral edema volume of the ANP and placebo groups on day 14 were 11.4 mL and 4.0 mL, respectively ( median difference: 3.0 mL, IQR: -1.3 to 9.9 mL, P = 0.15). The rates of SAE within 90 days were similar in the ANP (3/57, 5%) and placebo (7/60, 12%) groups ( P = 0.36). Changes in serum mercury and arsenic concentrations were comparable. In patients with large artery atherosclerosis, ANP reduced the cerebral infarct volume at 14 days (median difference: -12.3 mL; IQR: -27.7 to -0.3 mL, P = 0.03). CONCLUSIONS: ANP showed a similar safety profile to placebo and non-significant tendency to reduce cerebral infarct volume in patients with moderate-to-severe stroke. Further studies are warranted to assess the efficacy of ANP in reducing cerebral infarcts and improving clinical prognosis. TRAIL REGISTRATION Clinicaltrials.gov , No. NCT04475328.
Aged ; Female ; Humans ; Male ; Middle Aged ; Double-Blind Method ; Drugs, Chinese Herbal/adverse effects* ; Ischemic Stroke/drug therapy* ; Pilot Projects ; Stroke/drug therapy* ; Treatment Outcome

BACKGROUND: Generalized pustular psoriasis (GPP), a rare and recurrent autoinflammatory disease, imposes a substantial burden on patients and society. Awareness of GPP in China remains limited. METHODS: This cross-sectional survey, conducted between September 2021 and May 2023 across 14 hospitals in China, included GPP patients of all ages and disease phases. Data collected encompassed demographics, clinical characteristics, economic impact, disease severity, quality of life, and treatment-related complications. Risk factors for GPP recurrence were analyzed. RESULTS: Among 127 patients (female/male ratio = 1.35:1), the mean age of disease onset was 25 years (1st quartile [Q1]-3rd quartile [Q3]: 11-44 years); 29.2% had experienced GPP for more than 10 years. Recurrence occurred in 75.6% of patients, and nearly half reported no identifiable triggers. Younger age at disease onset ( P  = 0.021) and transitioning to plaque psoriasis ( P  = 0.022) were associated with higher recurrence rates. The median diagnostic delay was 8 months (Q1-Q3: 2-41 months), and 32.3% of patients reported misdiagnoses. Comorbidities were present in 53.5% of patients, whereas 51.1% experienced systemic complications during treatment. Depression and anxiety affected 84.5% and 95.6% of patients, respectively. During GPP flares, the median Dermatology Life Quality Index score was 19.0 (Q1-Q3: 13.0-23.5). This score showed significant differences between patients with and without systemic symptoms; it demonstrated correlations with both depression and anxiety scores. Treatment costs caused financial hardship in 55.9% of patients, underscoring the burden associated with GPP. CONCLUSIONS The substantial disease and economic burdens among Chinese GPP patients warrant increased attention. Patients with early onset disease and those transitioning to plaque psoriasis require targeted interventions to mitigate the high recurrence risk.
Humans ; Male ; Female ; Psoriasis/pathology* ; Adult ; Cross-Sectional Studies ; Adolescent ; Child ; Young Adult ; Quality of Life ; Middle Aged ; China/epidemiology* ; Recurrence ; Risk Factors ; Surveys and Questionnaires ; East Asian People

Endometrial cancer (EC) is one of the most common gynecological malignancies, with an increasing incidence rate worldwide. Accurate segmentation of lesion areas in computed tomography (CT) images is a critical step in assisting clinical diagnosis. In this study, we propose a novel deep learning-based segmentation model, termed spatial choice and weight union network (SCWU-Net), which incorporates two newly designed modules: the spatial selection module (SSM) and the combination weight module (CWM). The SSM enhances the model's ability to capture contextual information through deep convolutional blocks, while the CWM, based on joint attention mechanisms, is employed within the skip connections to further boost segmentation performance. By integrating the strengths of both modules into a U-shaped multi-scale architecture, the model achieves precise segmentation of EC lesion regions. Experimental results on a public dataset demonstrate that SCWU-Net achieves a Dice similarity coefficient (DSC) of 82.98%, an intersection over union (IoU) of 78.63%, a precision of 92.36%, and a recall of 84.10%. Its overall performance is significantly outperforming other state-of-the-art models. This study enhances the accuracy of lesion segmentation in EC CT images and holds potential clinical value for the auxiliary diagnosis of endometrial cancer.
Humans ; Endometrial Neoplasms/diagnostic imaging* ; Female ; Tomography, X-Ray Computed/methods* ; Deep Learning ; Algorithms ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer

Stem cell treatment may enhance erectile dysfunction (ED) in individuals with cavernous nerve injury (CNI). Nevertheless, no investigations have directly ascertained the implications of varying amounts of human umbilical cord-derived mesenchymal stem cells (HUC-MSCs) on ED. We compare the efficacy of three various doses of HUC-MSCs as a therapeutic strategy for ED. Sprague-Dawley rats (total = 175) were randomly allocated into five groups. A total of 35 rats underwent sham surgery and 140 rats endured bilateral CNI and were treated with vehicles or doses of HUC-MSCs (1 × 10 6 cells, 5 × 10 6 cells, and 1 × 10 7 cells in 0.1 ml, respectively). Penile tissues were harvested for histological analysis on 1 day, 3 days, 7 days, 14 days, 28 days, 60 days, and 90 days postsurgery. It was found that varying dosages of HUC-MSCs enhanced the erectile function of rats with bilateral CNI and ED. Moreover, there was no significant disparity in the effectiveness of various dosages of HUC-MSCs. However, the expression of endothelial markers (rat endothelial cell antigen-1 [RECA-1] and endothelial nitric oxide synthase [eNOS]), smooth muscle markers (alpha smooth muscle actin [α-SMA] and desmin), and neural markers (neurofilament [RECA-1] and neurogenic nitric oxide synthase [nNOS]) increased significantly with prolonged treatment time. Masson's staining demonstrated an increased in the smooth muscle cell (SMC)/collagen ratio. Significant changes were detected in the microstructures of various types of cells. In vivo imaging system (IVIS) analysis showed that at the 1 st day, the HUC-MSCs implanted moved to the site of damage. Additionally, the oxidative stress levels were dramatically reduced in the penises of rats administered with HUC-MSCs.
Male ; Animals ; Erectile Dysfunction/metabolism* ; Rats, Sprague-Dawley ; Mesenchymal Stem Cell Transplantation/methods* ; Rats ; Penis/pathology* ; Humans ; Disease Models, Animal ; Umbilical Cord/cytology* ; Peripheral Nerve Injuries/complications* ; Mesenchymal Stem Cells ; Nitric Oxide Synthase Type III/metabolism* ; Actins/metabolism* ; Nitric Oxide Synthase Type I/metabolism*

OBJECTIVE: To investigate the characteristics of central nervous system regulation in patients with refractory overactive bladder (rOAB) using resting-state functional magnetic resonance imaging (rs-fMRI), and to analyze the differences in brain function and connection between the patients and healthy population. METHODS: From May 1 to November 30, 2024, we performed rs-fMRI for 47 rOAB patients and another 47 matched healthy controls, documented relevant clinical data from all the participants and obtained their Overactive Bladder Symptom Scores (OABSS) and Overactive Bladder Questionnaire (OAB-Q) scores. Based on rs-fMRI, we compared the results of Independent Component Analysis (ICA), amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo) and degree centrality (DC) between the rOAB patients and healthy controls. RESULTS: The rOAB patients, in comparison with the healthy controls, showed dramatically higher daytime urination frequency (11.64 ± 3.85) vs (5.76 ± 0.91), nighttime urination frequency (3.72 ± 1.64) vs (0.31 ± 0.47), OABSS (8.22 ± 2.21) vs (0.64±0.78), OAB-Q1 score (20.85 ± 5.28) vs (6.78 ± 1.04), and OAB-Q2 score (45.04 ± 12.11) vs (14.51 ± 1.66) (all P<0.01). No statistically significant differences were observed in the results of ICA and ALFF between the right superior frontal and right middle frontal regions in the rOAB patients (P>0.05), but fALFF, ReHo and DC were significantly decreased in the patients compared with those in the healthy controls (P<0.01). CONCLUSION Compared with healthy population, the functions and connection of the frontal superior right and frontal middle right brain regions in rOAB patients are significantly down-regulated, which may serve as new therapeutic targets.
Humans ; Urinary Bladder, Overactive/physiopathology* ; Magnetic Resonance Imaging ; Brain/physiopathology* ; Female ; Male ; Adult ; Surveys and Questionnaires ; Case-Control Studies ; Middle Aged ; Rest ; Brain Mapping

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.