ObjectiveTo investigate the protective effect of Xielitang on dextran sulfate sodium （DSS）-induced ulcerative colitis （UC） mice and its possible mechanism. MethodsDSS was used to establish UC model. Sixty mice were randomly divided into a normal group， a model group， a sulfasalazine group （0.6 g·kg^-1）， and low-， medium-， and high-dose Xielitang groups （1.67， 3.34， 6.68 g·kg^-1）. After treatment for 42 d， the colon length was recorded， and the disease activity index （DAI） score was calculated. Enzyme-linked immunosorbent assay （ELISA） was used to detect the serum levels of tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， and interleukin-10 （IL-10）. Hematoxylin-eosin （HE） staining was used to observe the pathomorphological changes of colon. Western blot was used to detect the protein expression of farnesoid X receptor （FXR）， small heterodimer partner （SHP）， liver receptor homolog-1 （LRH-1）， cholesterol 7α-hydroxylase （CYP7A1）， and fibroblast growth factor receptor 4 （FGFR4） in liver and FXR， sodium-dependent bile acid transporter （ASBT）， and fibroblast growth factor 15 （FGF15） in ileum. 16S rRNA sequencing was used to analyze the intestinal flora. Moreover， ultra-high performance liquid chromatography–tandem mass spectrometry was used to detect the bile acid content. ResultsCompared with the normal group， the model group showed significantly decreased colon length， IL-10 content， α-diversity index， abundance of Firmicutes and Lactobacillus， and content of deoxycholic acid （DCA） and lithocholic acid （LCA） （P<0.01）， significantly increased DAI score， IL-6 and TNF-α content， abundance of Bacteroidetes， and the content of cholic acid （CA）， chenodeoxycholic acid （CDCA）， and taurocholic acid （TCA） （P<0.05， P<0.01）， significantly down-regulated protein expression of FXR， SHP， and FGFR4 in liver and FXR， ASBT， and FGF15 in ileum （P<0.01）， and significantly up-regulated protein expression of LRH-1 and CYP7A1 in liver （P<0.01）. In addition， the structure of colonic mucosa was destroyed， and inflammatory cells infiltrated in the model group. Compared with the model group， Xielitang could significantly increase the colon length， IL-10 content， α-diversity index， the abundance of Firmicutes and Lactobacillus， and DCA and LCA content （P<0.05， P<0.01）， decrease DAI score， abundance of Bacteroidetes， and the content of IL-6， TNF-α， CA， CDCA， and TCA （P<0.01）， up-regulate the protein expression of FXR， SHP， and FGFR4 in liver and FXR， ASBT， and FGF15 in ileum （P<0.01）， and down-regulate the protein expression of LRH-1 and CYP7A1 in liver （P<0.01）. The pathological damage of colonic mucosa was obviously alleviated. ConclusionXielitang protects against UC probably by regulating the "intestinal microbiota-bile acid" axis， regulating intestinal flora imbalance， and maintaining bile acid homeostasis.

Objective To understand the influencing factors of chronic dyslipidemia in T2DM patients who signed a contract for diabetes point system management in Qingpu District, and to provide a basis for comprehensive intervention and prevention and control of dyslipidemia in T2DM patients and to optimize the management strategy of Qingpu District diabetes point system. Methods Among the T2DM patients who signed the diabetes point system from 2017 to 2023, patients with chronic dyslipidemia and normal blood lipids were selected and included in the case group and the control group, respectively. A case-control study was conducted with 1:1 matching by age and gender to analyze the factors influencing dyslipidemia. Results Multifactorial paired logistic regression analysis showed that overweight/obesity and central obesity and smoking in T2DM patients increased the risk of dyslipidemia by 1.93, 2.27, and 2.16 times, respectively. Long-term use of lipid-lowering drugs, duration of diabetes for 5 years or more, regular physical exercise, knowledge of blood lipid status, and married status could reduce the risk of dyslipidemia in T2DM patients (OR values were 0.547, 0.452, 0.685, 0.386 and 0.354, respectively). Current complications (history of stroke, coronary heart disease, and renal insufficiency) were also associated with dyslipidemia (OR=1.802, 95% CI:1.125-2.888). Conclusion The management of diabetes point system in Qingpu District should strengthen the feedback and interpretation of blood lipid monitoring results, improve patients’ health awareness of blood lipid management, and actively take comprehensive management of lifestyle intervention and drug treatment to effectively control blood lipid and reduce the occurrence of related complications.

Objective To observe changes in genetic material in the peripheral blood of pediatric patients with vascular malformations after interventional procedures. Methods A total of 108 children with vascular malformations who underwent interventional procedures at Shandong University Affiliated Children’s Hospital between February 2021 and January 2024 were selected as the research subjects. Clinical data and peripheral venous blood samples before and after the interventional procedures were collected from the children. Two biological indicators, γ-H2AX and peripheral blood lymphocyte chromosomal aberration (CA), were used to determine the levels of genetic material damage in children with vascular malformations before and after interventional procedures. Results The median age of the children was 7 years and the median body weight was 27 kg. The median dose-area product (DAP) was 24.20 Gy·cm² and the median DAP/kg was 1.04 Gy·cm²/kg. The incidence rates of both γ-H2AX foci and CA in children with vascular malformations significantly increased after the interventional procedures (Z = 5.924, P < 0.001; Z = 8.515, P < 0.001). The incidence of postoperative CA in 7 children were significantly higher than that in others, approaching or exceeding 4%. The incidence rates of postoperative γ-H2AX foci and CA in children with DAP/kg ≥ 1 Gy·cm²/kg were significantly higher than those in children with DAP/kg < 1 Gy·cm²/kg (U = 7.586, P = 0.031; U = 6.835, P = 0.009). No significant differences were observed in the incidence rates of postoperative γ-H2AX foci and CA among subgroups based on age, body weight, or surgical site. A positive correlation was observed between the difference in the incidence rates of γ-H2AX foci before and after the procedure and DAP/kg (R = 0.493, P = 0.027). Conclusion Ionizing radiation exposure during interventional procedures can increase peripheral blood genetic material damage levels in children with vascular malformations, and the damage levels show a correlation with the radiation dose, with some children being abnormally sensitive. Further research is needed to explore the influencing factors for genetic material damage in children with vascular malformations after interventional procedures, which is of great significance for reducing long-term cancer risks and achieving personalized treatment strategies.

As a key member of the insulin-like growth factor family， insulin-like growth factor-‍Ⅰ （IGF-‍Ⅰ） is mainly synthesized in the liver and is widely distributed in the human body， and it is involved in the physiological processes such as cell proliferation， differentiation， metabolism， and apoptosis. Studies have shown that the level of IGF-‍Ⅰ is negatively correlated with the severity of liver cirrhosis， and IGF-‍Ⅰ mainly affects the progression of liver cirrhosis by inhibiting liver fibrosis， promoting DNA damage repair， and regulating lipid metabolism. Monitoring of IGF-‍Ⅰ level is expected to provide an evaluation indicator for improving the prognosis of patients with liver cirrhosis， and stimulating the action pathway of IGF-‍Ⅰ or regulating its expression level may become a new method for the treatment of liver cirrhosis. This article reviews the research advances in IGF-‍Ⅰ in liver cirrhosis， in order to provide new ideas for the diagnosis and treatment of liver cirrhosis.

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.

Aim To establish a stable hepatic stellate cell ( HSC ) -specific G protein-coupled receptor kinase 2 ( GRK2 ) knockout mice and provide the important animal model for further studying the biological function of GRK2 in HSC. Methods The loxP-labeled Grk2 gene mouse (Grk2

Objective: To explore the molecular mechanism of resveratrol (RES) in the treatment of oral squamous cell carcinoma (OSCC) through the use of biological information methods such as network pharmacology and molecular docking and to provide a theoretical reference for the clinical application of RES in the treatment of OSCC. Methods: The Swiss Target Prediction(http://www.swisstargetprediction.ch), SEA (http://sea.bkslab.org)database, and Pharm mapper database(http://lilab-ecust.cn) were used to retrieve RES-related targets, and the DISGENET (www.disgenet.org), OMIM (https://omim.org) and GeneCards (https://www.genecards.org) databases were used to screen OSCC disease targets. The intersection of drugs and disease targets was determined, and Cytoscape 3.7.2 software was used to construct a "drug-diseasetarget pathway" network. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was used to construct a target protein interaction network, and the DAVID database was used for enrichment analysis of key proteins. Finally, molecular docking validation of key proteins was performed using AutoDock and PyMOL. The enrichment analysis and molecular docking results were integrated to predict the possible molecular mechanisms of RES treatment in OSCC; western blot was used to determine the effect of resveratrol at different concentrations (50, 100) μmol/L on the expression of Src tyrosine kinase (SRC), epidermal growth factor receptor (EGFR), estrogen receptor gene 1 (ESR1), and phosphatidylinositol 3 kinase/protein kinase B (PI3K/AKT) signaling pathway proteins in OSCC HSC-3 cells. Results: A total of 243 targets of RES drugs and 6 094 targets of OSCC were identified. A total of 116 potential common targets were obtained by intersecting drugs with disease targets. These potential targets mainly participate in biological processes such as in vivo protein self-phosphorylation, peptide tyrosine phosphorylation, transmembrane receptor protein tyrosine kinase signaling pathway, and positive regulation of RNA polymerase Ⅱ promoter transcription, and they interfere with the PI3K/AKT signaling pathway to exert anti-OSCC effects. The docking results of resveratrol with OSCC molecules indicated that key targets, such as EGFR, ESR1, and SRC, have good binding activity. The results of cell-based experiments showed that resveratrol inhibited the protein expression of SRC, EGFR, ESR1, p-PI3K, and p-AKT in HSC-3 cells in a dose-dependent manner. Conclusion RES can inhibit the expression of its targets EGFR, ESR1, SRC, p-PI3K, and p-AKT in OSCC cells.