Ulcerative colitis（UC） is a chronic non-specific inflammatory bowel disease characterized by inflammation and ulceration of the colonic mucosa and submucosa， and its complex pathogenesis involves immune abnormality， oxidative stress and other factors. The nuclear transcription factor E₂-related factor 2（Nrf2）， encoded by the Nfe212 gene， plays a central role in antioxidant responses. It not only activates various antioxidant response elements such as heme oxygenase-1（HO-1） and quinone oxidoreductase 1（NQO1）， but also enhances the activity of glutathione-S-transferase（GST） and superoxide dismutase 1（SOD1）， effectively eliminating reactive oxygen species（ROS） accumulated in the body， and mitigating oxidative stress-induced damage to intestinal mucosa. In addition， Nrf2 can reduce the release of inflammatory factors and infiltration of immune cells by regulating immune response， cell apoptosis and autophagy pathways， thereby alleviating intestinal inflammation and promoting the repair and regeneration of damaged mucosa. Based on this， this paper reviews the research progress of Chinese materia medica in the prevention and treatment of UC by modulating the Nrf2 signaling pathway. It deeply explores the physiological role of Nrf2， the molecular mechanism of activation， the protective effect in the pathological process of UC， and how active ingredients in Chinese materia medica regulate the Nrf2 signaling pathway through multiple pathways to exert their potential mechanisms. These studies have revealed in depth that Chinese materia medica can effectively combat oxidative stress by regulating the Nrf2 signaling pathway. It can also play a role in anti-inflammatory， promoting autophagy， inhibiting apoptosis， protecting the intestinal mucosal barrier， and promoting intestinal mucosal repair， providing new ideas and methods for the multi-faceted treatment of UC.

Twelve compounds were isolated from the rice fermentation extracts of Penicillium expansum GY618 by silica column chromatography, Sephadex gel column chromatography, ODS column chromatography and semi preparative HPLC methods. They were determined as 11-hydroxyl-penicitrinone F (1), penicitrinone F (2), betulin (3), erythrodiol (4), ergosterol (5), ergost-5α,8α-epidioxy-6,22-dien-3β-ol (6), (5α,8α-epidioxy-(22E,24R)-ergosta-6,9(11),22-trien-3β-ol) (7), 5α,8α-epidioxy-(22E,24R)-23-methylergosta-6,22-dien-3β-ol (8), 5α,8α-epidioxy- 23,24(R)-dimethylcholesta-6,9(11),22-trien-3β-ol (9), dankasterone A (10), (17R)-4-hydroxy-17-methylincisterol (11) and ergosta-4,6,8(14),22-tetraen-3-one (12), through mass spectrometer, nuclear magnetic resonance (NMR) and comparison with the literature. Compound 1 was a new compound and compounds 2-4, 6-12 were isolated from Penicillium expansum fungus for the first time. The tyrosinase inhibitory activity experiment showed that compounds 1, 3 and 12 showed certain inhibitory activity against tyrosinase with IC₅₀ values of (75 ± 9), (69 ± 8) and (64 ± 2) μmol·L^-1, respectively. The IC₅₀ of other compounds were all greater than 100 μmol·L^-1, while IC₅₀ of the positive control kojic acid was (46 ± 4) μmol·L^-1.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Objective: To explore the association between mental health status and adverse childhood experiences (ACEs) among sexual minority college students, so as to provide a scientific basis for mental health education and health promotion in universities. Methods: From January to February 2024, convenience and cluster sampling methods were used to select 1 792 college students from 11 colleges in Guangxi. A self reporting method was applied to identify 476 sexual minority individuals. The Symptom Check-List 90 (SCL-90) and the Simplified Chinese Adverse Childhood Experiences International Questionnaire (SC-ACE-IQ) were employed to assess mental health and ACEs. Multivariate Logistic regression analysis was conducted to examine the associations. Results: The detection rates of all psychological issues among sexual minority college students in Guangxi were significantly higher than those of non sexual minority college students ( χ 2=56.01-91.39, all P <0.01). Except for physical neglect, bullying, and community violence, sexual minority students exhibited higher reporting rates of other ACEs types compared to nonsexual minority students ( χ 2= 4.52-13.34, all P <0.05). The total ACEs score for college students was 1.00 (1.00, 2.00), while the SCL-90 total score was 96.00 (113.00, 160.00). Spearman correlation analysis revealed a positive correlation between ACEs total scores and SCL-90 total scores ( r=0.29, P <0.05). Additionally, all ACEs subscales, including emotional neglect, physical neglect, emotional abuse, sexual abuse, parental loss, domestic violence, and community violence were positively correlated with corresponding SCL-90 subscale scores ( r =0.05-0.22, all P <0.05). Multivariate Logistic regression analysis showed that family violence increased the risk of mental health issues for sexual minority students ( OR=1.61, 95%CI =1.26-2.09); emotional neglect ( OR= 1.05 , 95%CI =1.00-1.10), physical neglect ( OR=1.20, 95%CI =1.06-1.35), sexual abuse ( OR=1.49, 95%CI =1.15-1.93) increased mental health risks for non sexual minority students (all P <0.05). The cumulative effects of ACEs were all statistically significant in the total sample and both subgroups (all P <0.05). Conclusion Mental health status among sexual minority college students in Guangxi is associated with ACEs, and their well being requires active attention

Objective: To analyze the correlation between preschool children s emotional competence and home rearing environment in Shangrao City, so as to provide support for improving children s emotional competence development as well as their home rearing environment. Methods: A total of 1 242 children aged 3-6 years old from 10 kindergartens in Shangrao City were retrospectively investigated by stratified cluster random sampling method in December 2022, and the Children s Emotional Adjustment Scale-Preschool Version (CEAS-P) and the Home Nurture Environment Scale for children aged 3-6 were surveyed on parents of preschool children. The t-test was used to test the difference, Spearman correlation analysis and multiple linear regression were used to analyze the influencing factors of preschool children s emotional competence. Results: There were significant differences in emotional competence scores of preschool children for demographic indicators including age, place of residence, health status and whether they were only children ( F/t =5.98, 6.56, 38.00, 2.23, P <0.01). The emotional competence of preschool children was positively correlated with the home rearing environment ( r=0.62, P <0.01). Multiple linear regression analysis showed that diverse activities/play participation, social adaptation/self management, and emotional warmth/self expression in home rearing environment were positive predictors of children s emotional ability ( β =0.30, 0.28, 0.16), while neglect/intervention/punishment were negative predictors ( β =-0.09)( P <0.05). Conclusions The home rearing environment is a factor related to young children s emotional competence. It is suggested specific parenting initiatives such as enriching family activities and play, strengthening children s self adaptation and management, giving warmth and let children express emotions, and preventing child neglect, interference and punishment should be conducted to improve children s emotional competence.

OBJECTIVE: To investigate the effects of Danmu Extract Syrup (DMS) on lipopolysaccharide (LPS)-induced acute lung injury (ALI) in mice and explore the mechanism. METHODS: Seventy-two male Balb/C mice were randomly divided into 6 groups according to a random number table (n=12), including control (normal saline), LPS (5 mg/kg), LPS+DMS 2.5 mL/kg, LPS+DMS 5 mL/kg, LPS+DMS 10 mL/kg, and LPS+Dexamethasone (DXM, 5 mg/kg) groups. After pretreatment with DMS and DXM, the ALI mice model was induced by LPS, and the bronchoalveolar lavage fluid (BALF) were collected to determine protein concentration, cell counts and inflammatory cytokines. The lung tissues of mice were stained with hematoxylin-eosin, and the wet/dry weight ratio (W/D) of lung tissue was calculated. The levels of tumor necrosis factor-α (TNF-α), interleukin (IL)-6 and IL-1 β in BALF of mice were detected by enzyme linked immunosorbent assay. The expression levels of Claudin-5, vascular endothelial (VE)-cadherin, vascular endothelial growth factor (VEGF), phospho-protein kinase B (p-Akt) and Akt were detected by Western blot analysis. RESULTS: DMS pre-treatment significantly ameliorated lung histopathological changes. Compared with the LPS group, the W/D ratio and protein contents in BALF were obviously reduced after DMS pretreatment (P<0.05 or P<0.01). The number of cells in BALF and myeloperoxidase (MPO) activity decreased significantly after DMS pretreatment (P<0.05 or P<0.01). DMS pre-treatment decreased the levels of TNF-α, IL-6 and IL-1 β (P<0.01). Meanwhile, DMS activated the phosphoinositide 3-kinase/protein kinase B (PI3K/Akt) pathway and reversed the expressions of Claudin-5, VE-cadherin and VEGF (P<0.01). CONCLUSIONS DMS attenuated LPS-induced ALI in mice through repairing endothelial barrier. It might be a potential therapeutic drug for LPS-induced lung injury.
Mice ; Male ; Animals ; Proto-Oncogene Proteins c-akt/metabolism* ; Lipopolysaccharides ; Phosphatidylinositol 3-Kinases/metabolism* ; Interleukin-1beta/metabolism* ; Vascular Endothelial Growth Factor A/metabolism* ; Tumor Necrosis Factor-alpha/metabolism* ; Claudin-5/metabolism* ; Acute Lung Injury/chemically induced* ; Lung/pathology* ; Interleukin-6/metabolism* ; Drugs, Chinese Herbal

This study constructed a LHCGR-CRE-luc-HEK293 transgenic cell line according to the activation of the cAMP signaling pathway after recombinant human chorionic gonadotropin binding to the receptor. The biological activity of recombinant human chorionic gonadotropin was assayed using a luciferase assay system. The relative potency of the samples was calculated using four-parameter model. And the method conditions were optimized to validate the specificity, relative accuracy, precision and linearity of the method. The results showed that there was a quantitative potency relationship of human chorinonic gonadotropin (hCG) in the method and it was in accordance with the four-parameter curve. After optimization, the conditions were determined as hCG dilution concentration of 2.5 μg·mL^-1, dilution ratio of 1∶4, cell number of 10 000-15 000 cells/well, and induction time of 6 h. The method had good specificity, relative accuracy with relative bias ranging from -8.9% to 3.4%, linear regression equation correlation coefficient of 0.996, intermediate precision geometric coefficient of variation ranging from 3.3% to 15.0%, and linearity range of 50% to 200%. This study successfully established and validated a reporter gene method to detect hCG biological activity, which can be used for hCG biological activity assay and quality control.