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7 results on '"Yaling Pang"'

1. Can digital transformation change a firm's green innovation strategy? Evidence from China's heavily polluting industries

Author

Hongfei Cheng, Yuxin Li, Yaling Pang, Jing Zhao, and Kui Fu

Subjects
Digital transformation, Green technology innovation, Strategy selection, Heavily polluting enterprises, Capability-attitude, External constraint, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

Enterprises are facing the superimposed challenges of digitalization and greening. The shift from reactive green technology innovation (RGT) to proactive green technology innovation (PGT) has special significance for sustainable economic development. Which strategies will companies choose? Can digital transformation (DT) motivate companies to transform their green innovation strategies? Enterprises' green innovation strategy choices must be explained with regard to digitalization. The purpose of this paper is to reveal how digitalization affects the choice of green innovation strategies and to provide a realistic basis for the sustainable development of heavily polluting enterprises. We formulated a “DT-capability-strategy'' theoretical framework incorporating external constraints and internal attitudes to empirically test the microdata of 505 heavily polluting enterprises. The results show that: (1) DT can shift the heavily polluting enterprises' green innovation strategies from RGT to PGT. Endogenous tests and robustness tests support this conclusion. (2) A mechanism test shows that environmental regulations cannot significantly regulate a green innovation strategy. Only a company's capabilities and attitudes can influence PGT but their effects on RGT are not statistically significant. (3) The influence of DT on green innovation strategies shows multi-dimensional heterogeneity in the digital infrastructure, scale, and innovation level of the enterprise. The conclusions provide implications for enterprises to integrate their digital and green behaviors.

Published
2024
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2. Effect of Different Types of Empathy on Prosocial Behavior: Gratitude as Mediator

Author

YaLing Pang, Chao Song, and Chao Ma

Subjects
prosocial behavior, gratitude, college students, mediator, empathy, Psychology, BF1-990
Abstract

With the development of positive psychology, prosocial behavior has received widespread attention from researchers. Some studies have shown that emotion has a significant influence on individual prosocial behavior, but little research has studied the effect of different types of empathy on college students’ prosocial behaviors. The current study examined the mediating effects of gratitude among the associations between different types of empathy (perspective-taking, fantasy, empathic concern, and personal distress) and prosocial behavior among Chinese college students. For the study, we used the Prosocial Tendency Measurement questionnaire, the Hebrew version of Interpersonal Reactivity Index-C, and The Gratitude Questionnaire that investigated 1,037 participants. The results indicated that gratitude played a mediating role between perspective-taking and prosocial behavior, fantasy and prosocial behavior, empathic concern and prosocial behavior, and personal distress and prosocial behavior, respectively. The current study contributes to a better understanding of the relationship between empathy and prosocial behavior.

Published
2022
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4. Identification of biomarkers and mechanisms of diabetic cardiomyopathy using microarray data

Author

Chunping Dong, Xiao-Yan Li, Jian Guo, Shan Gao, Guifu Wu, Hui Li, Yaling Pang, and Yang-Wei Wang

Subjects
medicine.medical_specialty, Diabetic Cardiomyopathies, Lactate dehydrogenase A, Ribosome biogenesis, Computational biology, 030204 cardiovascular system & hematology, Activating Transcription Factor 4, Basic Science and Experimental Cardiology, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, medicine, Diabetes Mellitus, Humans, Gene Regulatory Networks, education, Gene, education.field_of_study, biology, Microarray analysis techniques, Aldolase C, business.industry, Gene Expression Profiling, General Medicine, Microarray Analysis, ABCE1, Cardiology, biology.protein, MYH6, Cardiology and Cardiovascular Medicine, business, Biomarkers
Abstract

Background: The study aimed to uncover the regulation mechanisms of diabetic cardiomyopathy (DCM) and provide novel prognostic biomarkers. Methods: The dataset GSE62203 downloaded from the Gene Expression Omnibus database was utilized in the present study. After pretreatment using the Affy package, differentially expressed genes (DEGs) were identified by the limma package, followed by functional enrichment analysis and protein– protein interaction (PPI) network analysis. Furthermore, module analysis was conducted using MCODE plug-in of Cytoscape, and functional enrichment analysis was also performed for genes in the modules. Results: A set of 560 DEGs were screened, mainly enriched in the metabolic process and cell cycle related process. Hub nodes in the PPI network were LDHA (lactate dehydrogenase A), ALDOC (aldolase C, fructose-bisphosphate) and ABCE1 (ATP Binding Cassette Subfamily E Member 1), which were also highlighted in Module 1 or Module 2 and predominantly enriched in the processes of glycolysis and ribosome biogenesis. Additionally, LDHA were linked with ALDOC in the PPI network. Besides, activating transcription factor 4 (ATF4) was prominent in Module 3; while myosin heavy chain 6 (MYH6) was highlighted in Module 4 and was mainly involved in muscle cells related biological processes. Conclusions: Five potential biomarkers including LDHA, ALDOC, ABCE1, ATF4 and MYH6 were identified for DCM prognosis.

Published
2020

5. β-arrestin-2 is involved in irisin induced glucose metabolism in type 2 diabetes via p38 MAPK signaling

Author

Lingjiao Liu, Lihua Yang, Jing Li, Jianqin Xu, Yaling Pang, and Haihui Zhu

Subjects
0301 basic medicine, Male, medicine.medical_specialty, MAP Kinase Signaling System, Glucose uptake, p38 mitogen-activated protein kinases, 030209 endocrinology & metabolism, Mice, Transgenic, Type 2 diabetes, Carbohydrate metabolism, p38 Mitogen-Activated Protein Kinases, Diabetes Mellitus, Experimental, Rats, Sprague-Dawley, 03 medical and health sciences, Mice, 0302 clinical medicine, Diabetes mellitus, Internal medicine, medicine, Myocyte, Animals, Cells, Cultured, biology, Skeletal muscle, Cell Biology, medicine.disease, beta-Arrestin 2, Fibronectins, Rats, 030104 developmental biology, medicine.anatomical_structure, Endocrinology, Glucose, Diabetes Mellitus, Type 2, biology.protein, Carbohydrate Metabolism, GLUT4
Abstract

Type 2 diabetes mellitus (T2DM) is a common metabolic disease worldwide. It has been reported that irisin play regulatory role in glucose metabolism in T2DM. However, the underlying mechanism involved in that is not completely known. Herein, we determined the novel role of β-arrestin-2 in irisin-induced glucose utilization in diabetes. Effects of irisin and β-arrestin-2 on glucose utilization were investigated in a rat model of diabetes and in diabetic C2C12 cells in vitro. Results showed that irisin had positive role in glucose metabolism via regulating glucose tolerance as well as uptake in cardiac and skeletal muscle tissues, as evidenced by IPGTT, 2-deoxyglucose uptake and plasma membrane GLUT-4 assay. β-arrestin-2 also improved glucose utilization in diabetes by increasing the glucose uptake and insulin sensitivity, as shown in mice overexpressing β-arrestin-2. In diabetic C2C12 myocytes, irisin-induced GLUT4 and glucose uptake were restrained by β-arrestin-2 inhibition, but was enhanced by β-arrestin-2 overexpression. Additionally, irisin and β-arrestin-2 increased the activation of p38 MAPK in diabetic C2C12 cells, and the repression of p38 MAPK activation decreased the glucose uptake and plasma membrane GLUT-4 was enhanced by irisin and β-arrestin-2 overexpression in diabetic C2C12 cells. In conclusion, we demonstrated that β-arrestin-2 has a crucial role in irisin induced glucose metabolism in T2DM by regulating the p38 MAPK signaling. This might present a novel therapeutic target of treatment for human diabetes.

Published
2017

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