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Astrocytes contribute in critical ways to the pathophysiology of epilepsy not only through trophic support but also through the regulation of neuronal excitability by modulating glutamate, γ‐aminobutyric acid (GABA), adenosine triphosphate (ATP), and adenosine levels. Calponin‐3 is an actin‐binding protein that is enriched in the brain. We have previously reported that increased calponin‐3 expression is correlated with epileptic seizures. In the present study, we revealed that in the hippocampus of epileptic mice models, increased calponin‐3 protein expression was correlated with the expression of the astrocytic marker glial fibrillary acidic protein (GFAP). Calponin‐3 overexpression in the hippocampus significantly increased susceptibility to epileptic seizures, whereas calponin‐3 downregulation was associated with reduced spontaneous recurrent seizures in mice. Furthermore, changes in calponin‐3 levels corresponded to astrocyte activation in both mice and cultured human astrocytes and were associated with changes in the protein levels of adenosine kinase (ADK) and equilibrative nucleoside transporter 1 (ENT1), which are two key regulators of adenosine metabolism that have been shown to play critical roles in epileptogenesis. Collectively, our findings suggest that calponin‐3 may regulate astrocyte‐mediated adenosine metabolism and could represent a potential therapeutic target for epilepsy. Increased calponin‐3 expression correlates with astrocyte activation in epileptic mice, modulating adenosine metabolism regulators ADK and ENT1. Calponin‐3 overexpression increased susceptibility to epileptic seizures, while its downregulation reduces spontaneous recurrent seizures, identifying it as a potential therapeutic target for epilepsy.

Vulnerability can lead to data loss, privacy leakage and financial loss. Accurate detection and identification of vulnerabilities is essential to prevent information leakage and APT attacks. This paper explores the possibility of digging the valuable information in vulnerability reports deeply. We propose a new model, VCGERG, which products a graph using key information from vulnerability reports and embeds the graph into the vector space using a keywords-LINE graph embedding algorithm based on the attention of neighboring nodes. VCGERG model uses the OVR random forest algorithm to classify vulnerabilities. Our model can get the complicated local and global information of the graph in large-scale dataset and achieve better results. In order to verify the effectiveness of our model, it is evaluated on many experiments. Compared with other models, our method has a higher accuracy rate of 0.975.

This study aimed to construct a prediction model for the occurrence of venous thromboembolism (VTE) in patients hospitalized with coronary heart disease (CHD) using machine learning algorithms. Clinical data were from the medical records of CHD patients admitted to tertiary hospitals in eastern Liaoning Province between 2019 and 2024. Five machine learning algorithms-random forest (RF), classification and regression tree (CART), logistic regression (LR), logistic regression + least absolute shrinkage and selection operator (LR + LASSO), and extreme gradient boosting (XGBoost)-were used to construct predictive models. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy were comparison metrics between different models. A total of 3113 CHD inpatients were included in the study. In the internal validation set, XGBoost had the highest AUC (0.704), sensitivity (0.708), and accuracy (0.692), and RF had the highest specificity (0.706). In the time external validation set, LR + LASSO had the highest AUC (0.649), the highest specificity (0.683) for RF, and the highest sensitivity (0.682) and accuracy (0.656) for XGBoost. D-dimer, Age, and Neutrophil Count (NEUT) were the three most important relevant indicators. The prediction model based on machine learning algorithms for the occurrence of VTE in CHD inpatients has a specific diagnostic value. The prediction model constructed by LR + LASSO and XGBoost is more effective than the models constructed by other methods. The results of this study can provide research ideas for the clinical prevention and treatment of VTE events occurring in CHD inpatients.

This paper presents a new morphing method based on the ＂as-rigid-as-possible＂ approach. Unlike the original as-rigid-as-possible method, we avoid the need to construct a consistent tetrahedral mesh, but instead require a consistent triangle surface mesh and from it create a tetrahedron for each surface triangle. Our new approach has several significant advantages. It is much easier to create a consistent triangle mesh than to create a consistent tetrahedral mesh. Secondly, the equations arising from our approach can be solved much more efficiently than the corresponding equations for a tetrahedral mesh. Finally, by incorporating the translation vector in the energy functional controlling interpolation, our new method does not need the user to arbitrarily fix any vertex to obtain a solution, allowing artists automatic control of interpolated mesh positions.

To investigate the relationship between the ratio (GHR) of fasting blood glucose (FBG) to high-density lipoprotein cholesterol (HDL-C) and the degree of coronary artery stenosis. This retrospective cross-sectional study enrolled 1313 eligible participants who underwent coronary arteriography (CAG) or coronary computed tomography angiography (CCTA) between January 1, 2022, and May 31, 2023, from the electronic medical record system of Liaoning Province Benxi Central Hospital. Participants were divided into two groups: a Coronary Artery Disease (CAD) group (n = 1071) and a non-CAD group (n = 242). Patients in the CAD group were further categorized into three groups based on their GS: a low GS group (GS ≤ 32, n = 404), a medium GS group (32 < GS ≤ 66, n = 313), and a high GS group (GS > 66, n = 354). Logistic regression analysis was used to determine the association between GHR and CAD, as well as severe CAD. Receiver operating characteristic (ROC) curves were constructed to analyze the predictive value of GHR for CAD and severe CAD. The median GHR in the CAD group was significantly higher than that in the non-CAD group (5.980 vs 4.871, = 0.000). GHR was positively correlated with GS and the number of coronary artery lesions. Logistic regression analysis indicated that GHR was an independent predictor of CAD and severe CAD. ROC analysis showed that GHR had predictive value for CAD and severe CAD. The areas under the curve (AUC) were 0.672 and 0.591, respectively, both of which were statistically significant ( = 0.000). Combining GHD with other risk factors to construct a new diagnostic model significantly improved the AUC. GHR is associated with the degree of coronary artery stenosis and can predict CAD and its severity.

In this paper, we present a new technique based on strain fields to carry out 3D shape morphing for applications in computer graphics and related areas. Strain is an important geometric quantity used in mechanics to describe the deformation of objects. We apply it in a novel way to analyze and control deformation in morphing. Using position vector fields, the strain field relating source and target shapes can be obtained. By interpolating this strain field between zero and a final desired value we can obtain the position field for intermediate shapes. This method ensures that the 3D morphing process is smooth. Locally, volumes suffer minimal distortion, and no shape jittering or wobbling happens: other methods do not necessarily have these desirable properties. We also show how to control the method so that changes of shape (in particular, size changes) vary linearly with time.

This study aimed to assess the risk factors for acute first-ever ischaemic stroke (IS) in the elderly population aged ≥60 years in the eastern part of Liaoning Province, China. This retrospective case-control study was derived from the Benxi Clinical Biobank and the Thrombotic Chronic Non-Communicable Disease Cohort Study in Natural Populations in Eastern Liaoning (ChiCTR2300074593). We collected cases of acute IS in the elderly population and selected the corresponding controls in a 1:1 ratio for inclusion in the study. Data collection included sociodemographics, clinical characteristics, and laboratory characteristics. We used IBM SPSS Statistics V26.0 for Windows for descriptive statistical analysis and conditional logistic regression analysis to determine risk factors for IS. This study included 326 cases (163 pairs) of study subjects. The median age of the cases and controls was 65 years (62-70). Both groups were predominantly 60-69 years old in the age subgroups, 69.3% in the case group and 74.2% in the control group, with a p-value of 0.011; females in both groups accounted for 49.1% in the case group and 49.1% in the control group. Variables with P < 0.05 in the univariate analysis included current smoking, current alcohol consumption, fasting blood glucose, and hypertension. Variables statistically significant in the univariate analysis entered into the multivariate multifactorial analysis. The results showed that hypertension (OR, 1.977; 95% CI, 1.322-2.956) and current alcohol consumption (OR, 1.549; 95% CI, 1.086-2.210) were independent risk factors for acute first-ever IS in the elderly population aged ≥60 years. Hypertension and current alcohol consumption are major risk factors for IS in an elderly population in eastern Liaoning Province.

Based on the community structure characteristics, theory, and methods of frequent subgraph mining, network motifs findings are firstly introduced into social network analysis; the tendentiousness evaluation function and the importance evaluation function are proposed for effectiveness assessment. Compared with the traditional way based on nodes centrality degree, the new approach can be used to analyze the properties of social network more fully and judge the roles of the nodes effectively. In application analysis, our approach is shown to be effective.

Purpose: To investigate the relationship between the ratio (GHR) of fasting blood glucose (FBG) to high-density lipoprotein cholesterol (HDL-C) and the degree of coronary artery stenosis. Patients and Methods: This retrospective cross-sectional study enrolled 1313 eligible participants who underwent coronary arteriography (CAG) or coronary computed tomography angiography (CCTA) between January 1, 2022, and May 31, 2023, from the electronic medical record system of Liaoning Province Benxi Central Hospital. Participants were divided into two groups: a Coronary Artery Disease (CAD) group (n = 1071) and a non-CAD group (n = 242). Patients in the CAD group were further categorized into three groups based on their GS: a low GS group (GS [less than or equal to] 32, n = 404), a medium GS group (32 < GS [less than or equal to] 66, n = 313), and a high GS group (GS > 66, n = 354). Logistic regression analysis was used to determine the association between GHR and CAD, as well as severe CAD. Receiver operating characteristic (ROC) curves were constructed to analyze the predictive value of GHR for CAD and severe CAD. Results: The median GHR in the CAD group was significantly higher than that in the non-CAD group (5.980 vs 4.871, P = 0.000). GHR was positively correlated with GS and the number of coronary artery lesions. Logistic regression analysis indicated that GHR was an independent predictor of CAD and severe CAD. ROC analysis showed that GHR had predictive value for CAD and severe CAD. The areas under the curve (AUC) were 0.672 and 0.591, respectively, both of which were statistically significant (P = 0.000). Combining GHD with other risk factors to construct a new diagnostic model significantly improved the AUC. Conclusion: GHR is associated with the degree of coronary artery stenosis and can predict CAD and its severity. Keywords: coronary artery disease, atherosclerosis, high-density lipoprotein cholesterol, fasting blood glucose, coronary stenosis

This paper was aimed to compare the clinical effectiveness and safety of adult male circumcision using the Shang RingTM （SR） with the no-flip technique compared with Dorsal Slit （DS） surgical method, A single-centered, prospective study was conducted at the West China Hospital, where patients were circumcised using the no-flip SR （n = 408） or the DS （n = 94） procedure. The adverse events （AEs） and satisfaction were recorded for both groups, and ring-removal time and percentage of delayed removals were recorded for the SR group. Finally, complete follow-up data were collected for 76.1% of patients （SR： n = 306; DS： n = 76）. The average ring-removal time for the SR group was 17.62 ± 6.30 days. The operation time （P 〈 0.001）, pain scores during the procedure （P 〈 0.001） and at 24 h postoperatively （P 〈 0.001）, bleeding （P = 0.001）, infection （P = 0.034）, and satisfaction with penile appearance （P 〈 0.001） in the SR group were superior to those in the DS group. After two postoperative weeks, the percentage of patients with edema in the SR group （P = 0.029） was higher but no differences were found at 4 weeks （P = 0, 185） between the two groups. In conclusions, the no-flip SR method was found to be superior to the DS method for its short operation time （〈5 min）, involving less pain, bleeding, infection, and resulting in a satisfactory appearance. However, the time for recovery from edema took longer, and patients may wear device for 2-3 weeks after the procedure.