Testing Big Data Applications

Today big data has become the basis of discussion for the organizations. The big task associated with big data stream is coping with its various challenges and performing the appropriate testing for the optimal analysis of the data which may benefit the processing of various activities, especially from a business perspective. Big data term follows the massive volume of data, (might be in units of petabytes or exabytes) exceeding the processing and analytical capacity of the conventional systems and thereby raising the need for analyzing and testing the big data before applications can be put into use. Testing such huge data coming from the various number of sources like the internet, smartphones, audios, videos, media, etc. is a challenge itself. The most favourable solution to test big data follows the automated/programmed approach. This paper outlines the big data characteristics, and various challenges associated with it followed by the approach, strategy, and proposed framework for testing big data applications

Single-cell transcriptome profiling reveals β cell maturation in stem cell-derived islets after transplantation

Human pluripotent stem cells differentiated to insulin-secreting β cells (SC-β cells) in islet organoids could provide an unlimited cell source for diabetes cell replacement therapy. However, current SC-β cells generated in vitro are transcriptionally and functionally immature compared to native adult β cells. Here, we use single-cell transcriptomic profiling to catalog changes that occur in transplanted SC-β cells. We find that transplanted SC-β cells exhibit drastic transcriptional changes and mature to more closely resemble adult β cells. Insulin and IAPP protein secretions increase upon transplantation, along with expression of maturation genes lacking with differentiation in vitro, including INS, MAFA, CHGB, and G6PC2. Other differentiated cell types, such as SC-α and SC-enterochromaffin (SC-EC) cells, also exhibit large transcriptional changes. This study provides a comprehensive resource for understanding human islet cell maturation and provides important insights into maturation of SC-β cells and other SC-islet cell types to enable future differentiation strategy improvements

SIX2 regulates human β cell differentiation from stem cells and functional maturation in vitro

Generation of insulin-secreting β cells in vitro is a promising approach for diabetes cell therapy. Human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSCs) are differentiated to β cells (SC-β cells) and mature to undergo glucose-stimulated insulin secretion, but molecular regulation of this defining β cell phenotype is unknown. Here, we show that maturation of SC-β cells is regulated by the transcription factor SIX2. Knockdown (KD) or knockout (KO) of SIX2 in SC-β cells drastically limits glucose-stimulated insulin secretion in both static and dynamic assays, along with the upstream processes of cytoplasmic calcium flux and mitochondrial respiration. Furthermore, SIX2 regulates the expression of genes associated with these key β cell processes, and its expression is restricted to endocrine cells. Our results demonstrate that expression of SIX2 influences the generation of human SC-β cells in vitro