Political Uncertainty and Corporate Social Responsibility in a Transition Economy

Cheng Maoyong,Dong Yuxuan,Jin Justin Y.,Kanagaretnam Kiridaran 한국증권학회 2022 Asia-Pacific Journal of Financial Studies Vol.51 No.5

We examine the influence of political uncertainty on the corporate social responsibility (CSR) of local firms in China. Political uncertainty refers to government officials’ turnover. We find that these firms significantly increase their CSR activities when city government officials are changed or replaced. We also find that political uncertainty increases firms’ attention to employee responsibilities, supply chain responsibilities, and environmental responsibilities. In addition, the turnover of government officials increases CSR activities due to the reduction or loss of political connections. The anti-corruption campaign has also strengthened the influence of political uncertainty on CSR.

Hierarchically porous carbon derived from tobacco waste by one-step molten salt carbonization for supercapacitor

Liu Yuxuan,Cheng Xinhua,Zhang Shenghui 한국탄소학회 2022 Carbon Letters Vol.32 No.1

High-performance carbon materials were prepared via a one-step molten salt carbonization of tobacco waste used as electrode materials for supercapacitors. Carbon material prepared by carbonization for 3 h in molten CaCl2 at 850 °C exhibits hierarchically porous structure and ideal capacitive behavior. In a three-electrode configuration with 1 mol L−1 H2SO4 aqueous solution, it delivers specific capacitance of 196.5 F g−1 at 0.2 A g−1, energy density of 27.2 Wh kg−1 at 0.2 A g−1, power density of 983.5 W kg−1 at 2 A g−1, and excellent cyclic stability with 94% capacitance retention after 5000 charge–discharge cycles at 1 A g−1. Moreover, in a symmetrical two-electrode configuration with 6 mol L−1 KOH aqueous solution, it delivers specific capacitance of 111.1 F g−1 at 0.2 A g−1, energy density of 3.8 Wh kg−1 at 0.2 A g−1, and power density of 482.0 W kg−1 at 2 A g−1. The relationship between hierarchically porous structure and capacitive performance is also discussed.

Combination of High-Density Lipoprotein Cholesterol and Lipoprotein(a) as a Predictor of Collateral Circulation in Patients With Severe Unilateral Internal Carotid Artery Stenosis or Occlusion

Shuyin Ma,Meijuan Zhang,Huiyang Qu,Yuxuan Cheng,Shuang Du,Jiaxin Fan,Qingling Yao,Xiao Dong Zhang,Mengying Chen,Nan Zhang,Kaili Shi,Yizhou Huang,Shuqin Zhan 대한신경과학회 2022 Journal of Clinical Neurology Vol.18 No.1

Background and Purpose Collateral circulation is considered an important factor affecting the risk of stroke, but the factors that affect collateral circulation remain unclear. This study was performed to identify the factors associated with collateral circulation, especially blood lipids. Methods The study involved patients who had undergone digital subtraction angiography and were confirmed as having severe unilateral stenosis or occlusion of the internal carotid artery (ICA). We classified the collateral circulation status of each patient as good (Grade 3 or 4) or poor (Grade 0, 1, or 2) according to the grading system of the American Society of Interventional and Therapeutic Neuroradiology/American Society of Interventional Radiology. We collected data on patients’ characteristics and identified the factors that affect collateral circulation. Results This study included 212 patients. The multivariate logistic regression analysis showed that the high-density lipoprotein cholesterol (HDL-C) concentration and a complete anterior half of the circle of Willis were independent protective factors for good collateral circulation, whereas elevated lipoprotein(a) [Lp(a)] and serum creatinine concentrations were independent risk factors for good collateral circulation. The area under the receiver operating characteristics curve (AUC) was 0.68 (95% confidence interval [CI], 0.61–0.76) for HDL-C and 0.69 (95% CI, 0.62–0.76) for Lp(a). A binary logistic regression model analysis of the joint factor of HDL-C and Lp(a) yielded an AUC of 0.77 (95% CI, 0.71–0.84). Conclusions In patients with severe unilateral ICA stenosis or occlusion, the combination of HDL-C and Lp(a) is a useful predictor of collateral circulation.

Artificial Intelligence in the Prediction of Gastrointestinal Stromal Tumors on Endoscopic Ultrasonography Images: Development, Validation and Comparison with Endosonographers

Lu Yi,Wu Jiachuan,Hu Minhui,Zhong Qinghua,Er Limian,Shi Huihui,Cheng Weihui,Chen Ke,Liu Yuan,Qiu Bingfeng,Xu Qiancheng,Lai Guangshun,Wang Yufeng,Luo Yuxuan,Mu Jinbao,Zhang Wenjie,Zhi Min,Sun Jiachen 거트앤리버 소화기연관학회협의회 2023 Gut and Liver Vol.17 No.6

Background/Aims: The accuracy of endosonographers in diagnosing gastric subepithelial lesions (SELs) using endoscopic ultrasonography (EUS) is influenced by experience and subjectivity. Artificial intelligence (AI) has achieved remarkable development in this field. This study aimed to develop an AI-based EUS diagnostic model for the diagnosis of SELs, and evaluated its efficacy with external validation. Methods: We developed the EUS-AI model with ResNeSt50 using EUS images from two hospitals to predict the histopathology of the gastric SELs originating from muscularis propria. The diagnostic performance of the model was also validated using EUS images obtained from four other hospitals. Results: A total of 2,057 images from 367 patients (375 SELs) were chosen to build the models, and 914 images from 106 patients (108 SELs) were chosen for external validation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the model for differentiating gastrointestinal stromal tumors (GISTs) and non-GISTs in the external validation sets by images were 82.01%, 68.22%, 86.77%, 59.86%, and 78.12%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy in the external validation set by tumors were 83.75%, 71.43%, 89.33%, 60.61%, and 80.56%, respectively. The EUS-AI model showed better performance (especially specificity) than some endosonographers. The model helped improve the sensitivity, specificity, and accuracy of certain endosonographers. Conclusions: We developed an EUS-AI model to classify gastric SELs originating from muscularis propria into GISTs and non-GISTs with good accuracy. The model may help improve the diagnostic performance of endosonographers. Further work is required to develop a multi-modal EUS-AI system.

Comparative analysis of metabolites and in vitro hypoglycemic activity of Taiwanofungus camphoratus cultured using various methods

Ming YongFei,Li Yin,Chu JianZhi,Zhou XiaoShuang,Huang YuXuan,Yang ShuDe,Mu YueJun,Wang Lin,Zhang Rui,Cheng XianHao 한국응용생명화학회 2024 Applied Biological Chemistry (Appl Biol Chem) Vol.67 No.-

Taiwanofungus camphoratus has attracted much attention because it can abundantly produce various active substances that exhibit blood-sugar lowering, immunity improving, and antioxidant properties. Currently, T. camphoratus is cultured using four main methods: cutting wood culture, solid-state fermentation, submerged fermentation, and dish culture. T. camphoratus produces different metabolites under different culture methods. In this study, nontargeted metabolomics was used to compare the metabolites of T. camphoratus produced under these four culture methods. Principal component analysis and supervised partial least squares-discriminant analysis were used to analyze the differences in the metabolites. Moreover, in vitro hypoglycemic activity of T. camphoratus extracts produced under four culture methods was compared by assessing their ability to inhibit the activity of α-glucosidase, α-amylase, and sucrase. A total of 186 metabolites were identified. In total, 127 metabolites were common under the four culture methods. Under solid-state fermentation, submerged fermentation, and cutting wood culture, 12, 1, and 4 metabolites were unique, respectively. The differential metabolites produced by T. camphoratus under four culture methods were mainly triterpenoids, phenolic compounds, and fatty acid compounds. α-glucosidase, α-amylase, and sucrase activity inhibition was the best using T. camphoratus extract obtained under cutting wood culture; the inhibition rates were 55.97%, 51.96%, and 78.02%, respectively, which were comparable to those exhibited by 0.001, 3, and 12 mg/mL acarbose (positive control). The metabolites produced by T. camphoratus and α-glucosidase, α-amylase, and sucrase inhibitory activities were different under the four culture methods. Cutting wood culture exhibited the best enzyme inhibitory activity. This study provided a theoretical basis for further use and development of various culture methods for the rational production of active metabolites of T. camphoratus.