Global Value Chain Embeddedness, Digital Economy and Green Innovation- Evidence From Provincial-Level Regions of China

With globalization and digitalization, participating in Global Value Chain (GVC) and developing digital economy have had a profound impact, which transforms China’s economy into a green and innovative one. This paper studies the intrinsic influential mechanism of GVC embeddedness and digital economy on green innovation and proposes some research hypotheses. Based on panel data of 30 Chinese provinces from 2002 to 2016, we constructed some core indicators such as GVC embeddedness, digital economy and green innovation. The ordinary panel model and spatial panel model are used to empirically test the impact of GVC embeddedness and digital economy on China’s green innovation at the provincial level. The research findings are: First, GVC embeddedness and digital economy have significant promotion effects on green innovation. Second, the development of digital economy will not only directly promote green innovation, but also indirectly promote green innovation by effectively promoting the integration of provincial economy into GVC. The results of mediating effect test show that GVC embeddedness has a partial mediating effect in the influential mechanism of digital economy to promote green innovation. Third, GVC embeddedness and green innovation have significant spatial spillover effects. It indicates that Chinese provinces (cities¹) have significantly promoted green innovation in neighboring provinces through many possible channels and mechanisms in the process of participating in GVC, and the robustness test shows the stability of the spatial spillover mechanism. The findings provide useful policy implications for China’s deeply participating in GVC, vigorously developing digital economy and promoting green innovation

Pan-cancer and single-cell analysis reveals FAM83D expression as a cancer prognostic biomarker

Background: The family with sequence similarity 83 member D (FAM83D) protein is known to play a significant role in many human diseases. However, its role in cancer remains ambiguous. This study aimed to investigate the function of FAM83D in a pan-cancer analysis, with a special focus on breast cancer.Methods: Samples were collected from The Cancer Genome Atlas (TCGA) and used for bioinformatic analysis. Datasets from the Gene Expression Omnibus (GEO) and Genotype-Tissue Expression (GTEx) databases were also analyzed for verification. The potential value of FAM83D as a prognostic and diagnostic biomarker was visualized through R software. The “survival” and “GSVA” package were used for univariate, multivariate and pathway enrichment analyseis. We further analyzed the CancerSEA databases and TISIDB websites for single-cell and immune-related profiling. Lastly, we validated those data in vitro using quantitative reverse transcriptase-polymerase chain reaction (RT‒qPCR), cell counting kit-8 (CCK-8), transwell, flow cytometry, and tumorigenicity assays in a murine cell line model.Results: The expression of FAM83D in tumor samples was significantly higher than in normal tissues for most cancer types in the datasets. We confirmed this finding using RT‒qPCR in a breast cancer cell line. Analysis of multiple datasets suggests that overall survival (OS) was extremely poor for breast cancer patients with high FAM83D expression. The CCK-8 assay demonstrated that MCF-7 cell proliferation was inhibited after genetic silencing of FAM83D. Transwell assay showed that knockdown of FAM83D significantly inhibited the invasion and migration ability of MCF-7 cells compared to the control. The results of flow cytometry showed that silencing FAM83D could block the G1 phase of MCF-7 cells compared with negative groups. The tumorigenicity assay in nude mice indicated that the tumorigenic ability to silence FAM83D decreased compared.Conclusion: Results suggest that FAM83D expression can serve as a valuable biomarker and core gene across cancer types. Furthermore, FAM83D expression is significantly associated with MCF-7 cell proliferation and thus may be a prospective prognostic biomarker especially for breast cancer

Baicalin Ameliorates Experimental Liver Cholestasis in Mice by Modulation of Oxidative Stress, Inflammation, and NRF2 Transcription Factor

Experimental cholestatic liver fibrosis was performed by bile duct ligation (BDL) in mice, and significant liver injury was observed in 15 days. Administration of baicalin in mice significantly ameliorates liver fibrosis. Experimental cholestatic liver fibrosis was associated with induced gene expression of fibrotic markers such as collagen I, fibronectin, alpha smooth muscle actin (SMA), and connective tissue growth factor (CTGF); increased inflammatory cytokines (TNFα, MIP1α, IL1β, and MIP2); increased oxidative stress and reactive oxygen species- (ROS-) inducing enzymes (NOX2 and iNOS); dysfunctional mitochondrial electron chain complexes; and apoptotic/necrotic cell death markers (DNA fragmentation, caspase 3 activity, and PARP activity). Baicalin administration on alternate day reduced fibrosis along with profibrotic gene expression, proinflammatory cytokines, oxidative stress, and cell death whereas improving the function of mitochondrial electron transport chain. We observed baicalin enhanced NRF2 activation by nuclear translocation and induced its target genes HO-1 and GCLM, thus enhancing antioxidant defense. Interplay of oxidative stress/inflammation and NRF2 were key players for baicalin-mediated protection. Stellate cell activation is crucial for initiation of fibrosis. Baicalin alleviated stellate cell activation and modulated TIMP1, SMA, collagen 1, and fibronectin in vitro. This study indicates that baicalin might be beneficial for reducing inflammation and fibrosis in liver injury models