• Journal of Life Science
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• v.30 no.8
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• pp.701-707
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• 2020

Gene editing technology using the clustered regularly interspaced short palindromic repeat (CRISPR) and the CRISPR associated protein (Cas)9 has been highly anticipated in developing breeding techniques. In this study, we discuss gene scissors as a tool for silkworm molecular breeding through analysis of Bombyx mori Kynurenine 3-Monooxygenase (BmKMO) gene editing using the CRISPR/Cas9 system and analysis of generational transmission through mutagenesis and selective crossing. The nucleotide sequence of the BmKMO gene was analyzed, and three guide RNAs (gRNAs) were prepared. Each synthesized gRNA was combined with Cas9 protein and then analyzed by T7 endonuclease I after introduction into the BM-N silkworm cell line. To edit the silkworm gene, K1P gRNA and Cas9 complexes were subsequently microinjected into the silkworm embryos; the hatching rate was 18% and the incidence of mutation was 60%. The gene mutation was verified in the heterozygous G0 generation, but no phenotypic change was observed. In homozygotes generated by self-crossing, a mutant phenotype was observed. These results suggest that silkworm molecular breeding using the CRISPR/Cas9 system is possible and could be an effective way of shortening the time required.

• Journal of Distribution Science
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• v.22 no.8
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• pp.65-76
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• 2024

Purpose: The study aims to recognize the relationship between big data analytics capabilities, big data analytics process, and perceived business performance from supply chain management to total customer satisfaction. Research design, data and methodology: The study followed a quantitative approach with a descriptive design. The data was collected from leading e-commerce companies in India using a structured questionnaire, and the data was coded and decoded using MS Excel, SPSS, and R language. It was further tested using Cronbach's alpha, KMO, and Bartlett's test for reliability and internal consistency. Results: The results showed that the big data analytics process acts as a robust mediator between big data analytics capabilities and perceived business performance. The 'direct, indirect and total effect of the model' and 'PLS-SEM model' showed that the big data analytics process directly impacts business performance. Conclusions: A complete indirect relationship exists between big data analytics capabilities and perceived business performance through the big data analytics process. The research contributesto e-commerce companies' understanding of the importance of big data analytics capabilities and processes.