Angiotensin converting enzyme (ACE) is a functional enzyme in renin-angiotensin system (RAS) during heart regulation. It is a 21-kb long gene which encodes an enzyme, on long arm of chromosome 17. ACE gene comprises of 26 exons with 25 introns. Genomic studies found that on ACE intron 16, an insertion or a deletion of a 287-bp noncoding Alu repeat sequence effects enzyme activity. This insertion/deletion polymorphism have a significant role in cardiovascular diseases, diabetes chronic obstructive pulmonary disease and skin disorders, furthermore, it was reported that D allele has shown an association with elevated levels of plasma ACE. Congenital heart diseases (CHDs) are the structural, functional and multifactorial defects, present at birth. Chromosomal aberration, alteration of gene (InDel, SNP) and environmental factors are some of the known causative agents of CHDs. However, to date there is limited information on the association of InDel polymorphism of ACE gene in Pakistani population. Total 207 patients and 150 healthy controls were recruited in the study to test the hypothesis. The aim of the current research is to find the association of D allele of ACE insertion/deletion polymorphism with congenital heart disease. The allelic frequencies of patients are D allele 56.7% and I allele 43.2% in patients and D allele 76.6% and I allele 23.3% in controls, reveals that presence of D allele can be a factor for the disturbed levels of enzyme in patients. It is needs to be further exploring its consequences.

The Cell Image Library (CIL) is a public and easily accessible resource database of images, videos, and animations of cells, capturing a wide diversity of organisms, cell types, and cellular processes. The purpose of this database is to advance research on cellular activity, with the ultimate goal of improving human health. This comprehensive and easily accessible Library is designed as a public resource first and foremost for research, and secondarily as a tool for education. The long-term goal is the construction of a library of images that will serve as primary data for research. A discussion of the development of the open source library and a demonstration of the features focusing on large data sets will be presented. Lastly, there will be a discussion of new tools that have been incorporated to interact with the data in the CIL to aid in original research will be presented.

Introduction: Baculovirus (BV), which is an enveloped insect virus with a circular double-stranded DNA genome, possesses unique characteristics to induce strong innate immune responses in various mammalian cells and in mice. Aim: Here we show that the innate immune responses induced by BV not only eliminate Plasmodium liver-stage parasites but also elicit sterile protection against Plasmodium sporozoite infection through type I IFN signaling pathway. Methodology: Mice had infected with liver-stage parasites before 24h completely prevented blood-stage parasites following a single dose of BV intramuscular (i.m.) administration, which was much superior to primaquine, the only drug approved to eradicate liver-stage parasites. Findings: This BV-mediated liver-stage parasite elimination was also observed in TLR-9-/-and iNOS-/- mice. In addition to the therapeutic effect, BV i.m. administration sterilely protects mice for at least 7 days from subsequence sporozoite infection, indicating the prophylactic effect. In vivo passive transfer with sera from mice i.m. administered with BV effectively eliminated liver-stage parasites and this effect was canceled by neutralization of IFN-a but not IFN-g in the sera, indicating a killing mechanism downstream of type I IFN signaling pathway. In fact, 6h after BV i.m. administration, both type I and II IFNs were robustly produced in sera and RNA transcripts of interferon-stimulated genes were drastically upregulated in the liver. Conclusion & Significance: Our results provide a great potential of BV for development of BV-based vaccine and anti-hypnozoite drug as a new stand-alone therapeutic and prophylactic immunostimulatory agent, which is applicable not only for malaria but also for other serious infectious diseases such as viral hepatitis.

Protein phosphatase-1 (PP1) is a prominent member of the Phosphoprotein Phosphatases family, and it catalyzes the majority of Ser/Thr dephosphorylation reactions. This broad range of functions is tightly regulated by its ability to form hundreds of holoenzymes by swapping a variety of regulatory subunits known as PP1-interacting proteins (PIPs). PIPs are seemingly unrelated in sequence and structure, but share a number of PP1-binding motifs (PP1-BMs). This common trait allows PIPs to combine multiple motifs and bind distinctive sites on PP1 surface to assemble unique holoenzymes. Although the majority of known PP1-BMs are unstructured short linear motifs (SLIMs), some are highly structured. Previous PP1 interactome mapping derives from high-throughput techniques combined with bioinformatics approaches that exploit SLIM PP1-BMs in proteome-wide screens based on sequence homology. Even though the number of known structured PP1-BMs is scarce when compared with the number of established SLIMs, it seems reasonable to expect that structural homology of proteins subunits (domains) could also be applied to expand the PP1 interactome. The present study explores structure-based PrePPI predictions to identify new PP1 interactors. PrePPI combines structural information with different sources of non-structural evidence to predict high-confidence interaction models. PrePPI predicts 17 models that recapitulate known holoenzymes and 127 novel interactions between PP1 and 70 putative PIPs. The analysis suggests that several proteins interact with PP1 via their ankyrin repeat domains, a known structured PP1-BM. Similarly, various proteins were proposed to interact with PP1through their PDZ domains in a manner previously unexplored. Most of the predicted PIPs contain established SLIM PP1-BMs, providing support for their physiological relevance, and additional novel PP1-BMs are proposed based on the analysis of the interaction models. This structural approach facilitates the mapping of a more complete PP1 interactome and provides the basis for novel therapeutic approaches to selectively modulate particular signaling cascades.

Pathogenesis of bacterial infections is important source of significant human diseases and excellent opportunities to accomplishment at biotechnology and biomedicine. Advances in Bacteria Genus prediction will provide further progress of biological production. Recent research has assisted to clarify the predictions of bacterial taxonomy genus until 2030 involved in pathogenesis and biomedical applications. The analysis of the data gathered through the National Center for Biotechnology Information Taxonomy database since from 1992/01/01 to 2018/12/31 demonstrated there’s a correct relationship between years with bacterial genus exploration analysis by regression and Durbin-Watson with analysis of variance and coefficients for dependent variable of the bacterial genus and predictors by years.