No abstract

To date, there is no representative in vitro model for liver sinusoidal endothelial cells (LSECs), as primary LSECs dedifferentiate very fast in culture and no combination of cytokines or growth factors can induce an LSEC fate in (pluripotent stem cell (PSC)-derived) endothelial cells (ECs). Furthermore, the transcriptional programmes driving an LSEC fate have not yet been described. Here, we first present a computational workflow (CenTFinder) that can identify transcription factors (TFs) that are crucial for modulating pathways involved in cell lineage specification. Using CenTFinder, we identified several novel LSEC-specific protein markers, such as FCN2 and FCN3, which were validated by analysis of previously published single-cell RNAseq data. We also identified PU.1 (encoded by the SPI1 gene) as a major regulator of LSEC-specific immune functions. We show that SPI1 overexpression (combined with the general EC TF ETV2) in human PSCs induces ECs with an LSEC-like phenotype. The ETV2-SPI1-ECs display increased expression of LSEC markers, such as CD32B and MRC1, as well as several of the proposed novel markers. More importantly, ETV2-SPI1-ECs acquire LSEC functions, including uptake of FSA-FITC, as well as labelled IgG. In conclusion, we present the CenTFinder computational tool to identify key regulatory TFs within specific pathways, in this work pathways of lineage specification, and we demonstrate its use by the identification and validation of PU.1 as a master regulator for LSEC fating.

Imputation is a computational method based on the principle of haplotype sharing allowing enrichment of genome-wide association study datasets. It depends on the haplotype structure of the population and density of the genotype data. The 1000 Genomes Project led to the generation of imputation reference panels which have been used globally. However, recent studies have shown that population-specific panels provide better enrichment of genome-wide variants. We compared the imputation accuracy using 1000 Genomes phase 3 reference panel and a panel generated from genome-wide data on 407 individuals from Western India (WIP). The concordance of imputed variants was cross-checked with next-generation re-sequencing data on a subset of genomic regions. Further, using the genome-wide data from 1880 individuals, we demonstrate that WIP works better than the 1000 Genomes phase 3 panel and when merged with it, significantly improves the imputation accuracy throughout the minor allele frequency range. We also show that imputation using only South Asian component of the 1000 Genomes phase 3 panel works as good as the merged panel, making it computationally less intensive job. Thus, our study stresses that imputation accuracy using 1000 Genomes phase 3 panel can be further improved by including population-specific reference panels from South Asia.

No abstract

Traditional toxicity risk assessment approaches have until recently focussed mainly on histochemical readouts for cell death. Modern toxicology methods attempt to deduce a mechanistic understanding of pathways involved in the development of toxicity, by using transcriptomics and other big data-driven methods such as high-content screening. Here, we used a recently described optimised method to differentiate human induced pluripotent stem cells (hiPSCs) to hepatocyte-like cells (HLCs), to assess their potential to classify hepatotoxic and non-hepatotoxic chemicals and their use in mechanistic toxicity studies. The iPSC-HLCs could accurately classify chemicals causing acute hepatocellular injury, and the transcriptomics data on treated HLCs obtained by TempO-Seq technology linked the cytotoxicity to cellular stress pathways, including oxidative stress and unfolded protein response (UPR). Induction of these stress pathways in response to amiodarone, diclofenac, and ibuprofen, was demonstrated to be concentration and time dependent. The transcriptomics data on diclofenac-treated HLCs were found to be more sensitive in detecting differentially expressed genes in response to treatment, as compared to existing datasets of other diclofenac-treated in vitro hepatocyte models. Hence iPSC-HLCs generated by transcription factor overexpression and in metabolically optimised medium appear suitable for chemical toxicity detection as well as mechanistic toxicity studies.

One major source of business financing is through Initial Public Offerings (IPOs). Historically, IPOs received high initial first day gains compared to the market performance. These gains reflect external factors and not the company's true value, thereby suggesting the under-priced IPO. The recent researches on IPOs in different markets for different industries in various countries, have focused on under-pricing and show that the under-pricing is evident in case of book-building route as well as fixed price-band offers. This study attempts to identify causal variables behind high initial gains for Indian IPOs using earlier researches and testing them over a sample of Indian IPOs to examine the influence of non-fundamental factors and signalling effects on under-pricing

All of us, with no exception, wish to succeed in life and find peace, fulfillment and contentment. We spend nearly a-third of our lives at the workplace. Our joys and sorrows our agonies and ecstasies are colored by the experiences we have at the workplace. However, only a handful amongst us consciously prepare ourselves for survival and for attaining success. Apart from acquiring skills of various kinds, it is necessary for us to understand the environment in which we operate. To deal with the situations we confront during our career with maturity, poise and grace, we have to prepare ourselves and have to understand the human psyche and to imbibe a philosophy of life which will allow us to not only survive but succeed as well.

Amorphous-SiC films have been deposited by pulsed laser ablation on silicon substrates. Photoluminescence (PL) studies showed two broad bands with peaks at 1.34 and 1.72 eV for these unhydrogenated films. On NH3 passivation the intensity of the 1.34 eV peak increased by a large factor of 40–50 with full width at half-maximum (FWHM) decreasing to 13.5 meV at 12 K. The activation energy of this level was found to be 24 meV. These results are in contrast with those from unhydrogenated a-Si. A possible mechanism responsible for PL enhancement is discussed.