Measurement of serum cholesterol levels as a predictor of preterm delivery

AIM & OBJECTIVES: 1. To evaluate the association of elevated cholesterol levels at 14 to 24 weeks gestation in uncomplicated pregnancy and preterm delivery. 2. To associate the elevated levels of cholesterol as predictor of preterm delivery. 3. To determine the association between elevated Serum Cholesterol in Pregnancy & Pre-term Births. METHODOLOGY: Study Centre : Department of Obstetrics and Gynecology, MMC Chennai. Study Design: Prospective cohort study. Period of Study: ONE YEAR (Aug 2016 – July 2017). Sample Size: 300 patients. Inclusion Criteria: All cases of singleton gestation (confirmed by early second trimester ultrasound), gestational age between 14-20 weeks (by LMP and confirmed by ultrasound), intact amnioticmembranes, history of Pre-term labor/pre-term delivery in prior pregnancy. Exclusion Criteria: Multiple gestation, H/O Diabetes or Hyper Tension, Pre-eclampsia, GDM, Heart Diseases, previous abnormal pregnancy history, Cervical incompetence, Renal disorders, Congenital malformations, Smoking, Alcohol consumption. MATERIALS & METHODS: All generally, healthy pregnant women attending the antenatal clinic are to be enrolled and the serum cholesterol levels to be measured at GA of 14 to 20 weeks’ pregnancy and followed up to delivery and then they will be allocated to preterm and non-preterm groups based on the GA at delivery. SAMPLE COLLECTION: Venous blood samples were obtained from fasting patient in the morning to measure total serum cholesterol concentrations between 14 and 20 weeks' gestation. RESULT: 47% of this study population were in the age group of 22 – 24 years. (mean – 22.3). 46.7% were primis, 53.3% were second gravidas. In this study, we have not seen much influence of age and parity to the outcome of delivery. 93.7% mothers had normal cholesterol values, 6.3% had elevated cholesterol values. The study group with normal cholesterol values had good outcome were as 63.2% study group with elevated cholesterol values had preterm delivery is statistically significant (p = 0.0001). The mean fetal weight delivered at term are significantly higher than those of preterm. Among the preterm deliveries, 78.3% babies were admitted in NICU, which is statistically significant (p < 0.0001). In the current study cholesterol levels was found to be simple marker for preterm delivery. CONCLUSION: Serum cholesterol levels increase during pregnancy & is necessary for uteroplacental vascularisation, placental transport functions. Hyperlipidaemia is also regarded as an instigator of inflammation and stress, which is a significant factor in preterm birth. The findings of the present study showed that serum cholesterol levels were found to be elevated in patients who have gone in for preterm labour than those gone for term pregnancy. Hence, Serum cholesterol levels has been found to be useful simple marker for preterm delivery. This observation helps us to describe a generic framework for combining this screening information for designing a prophylactic intervention in future

Adenosine deaminase from Plasmodium falciparum as a Potential Drug Target in Anti- Malarial Drug Designing: A Bioinformatic Approach

Parasites are responsible for a wide variety of infectious diseases causing an enormous health and economical blight. Malaria is one such prominent disease that causes widespread infections in humans and results in innumerable deaths annually. The development of resistance of the malarial parasites to the conventional drugs has signaled for an urgent need to design new drugs in an effective way and also to identify and study new drug targets to combat this disease. The rational design of a drug is usually based on the biochemical and physiological differences between the pathogen and the host. So in this current study we focus on the striking differences in the purine metabolism of the malarial parasite Plasmodium falciparum and that of the host. Based on this, we submit a hypothesis on targeting a protein Adenosine deaminase that plays an important role in the purine metabolism of the parasite. In this study a synthetic and a natural drug were used and their efficacy was compared and analyzed

Phytochemical Screening and Antimicrobial Activity of the Plant Extracts of Mimosa pudica L. Against Selected Microbes

Mimosa pudica L. is a creeping annual or perennial herb. It has been identified as Lajjalu in Ayurveda and has been found to have antiasthmatic, aphrodisiac, analgesic and antidepressant. In the present study the active phytocomponents of Mimosa pudica were revealed using phytochemical analysis. The antimicrobial activity of Mimosa was studied using well diffusion method. The activity was tested against Aspergillus fumigatus, Citrobacter divergens and Klebsiella pneumonia at different concentrations of 50, 100 and 200μg/disc and the results have been illustrated

The Cellular Composition of the Uveal Immune Environment

The uveal tract consists of the iris, the ciliary body and the choroid; these three distinct tissues form a continuous layer within the eye. Uveitis refers to inflammation of any region of the uveal tract. Despite being grouped together anatomically, the iris, ciliary body and choroid are distinct functionally, and inflammatory diseases may affect only one part and not the others. Cellular structure of tissues direct their function, and understanding the cellular basis of the immune environment of a tissue in health, the "steady state" on which the perturbations of disease are superimposed, is vital to understanding the pathogenesis of those diseases. A contemporary understanding of the immune system accepts that haematopoietic and yolk sac derived leukocytes, though vital, are not the only players of importance. An array of stromal cells, connective tissue cells such as fibroblasts and endothelial cells, may also have a role in the inflammatory reaction seen in several immune-mediated diseases. In this review we summarise what is known about the cellular composition of the uveal tract and the roles these disparate cell types have to play in immune homeostasis. We also discuss some unanswered questions surrounding the constituents of the resident leukocyte population of the different uveal tissues, and we look ahead to the new understanding that modern investigative techniques such as single cell transcriptomics, multi-omic data integration and highly-multiplexed imaging techniques may bring to the study of the uvea and uveitis, as they already have to other immune mediated inflammatory diseases

Gene expression signature-based chemical genomic prediction identifies a novel class of HSP90 pathway modulators

SummaryAlthough androgen receptor (AR)-mediated signaling is central to prostate cancer, the ability to modulate AR signaling states is limited. Here we establish a chemical genomic approach for discovery and target prediction of modulators of cancer phenotypes, as exemplified by AR signaling. We first identify AR activation inhibitors, including a group of structurally related compounds comprising celastrol, gedunin, and derivatives. To develop an in silico approach for target pathway identification, we apply a gene expression-based analysis that classifies HSP90 inhibitors as having similar activity to celastrol and gedunin. Validating this prediction, we demonstrate that celastrol and gedunin inhibit HSP90 activity and HSP90 clients, including AR. Broadly, this work identifies new modes of HSP90 modulation through a gene expression-based strategy

Modern Solutions for Ancient Pathogens: Direct Pathogen Sequencing for Diagnosis of Lepromatous Leprosy and Cerebral Coenurosis.

Microbes unculturable in vitro remain diagnostically challenging, dependent historically on clinical findings, histology, or targeted molecular detection. We applied whole-genome sequencing directly from tissue to diagnose infections with mycobacteria (leprosy) and parasites (coenurosis). Direct pathogen DNA sequencing provides flexible solutions to diagnosis of difficult pathogens in diverse contexts

Height, selected genetic markers and prostate cancer risk:Results from the PRACTICAL consortium

Background: Evidence on height and prostate cancer risk is mixed, however, recent studies with large data sets support a possible role for its association with the risk of aggressive prostate cancer. Methods: We analysed data from the PRACTICAL consortium consisting of 6207 prostate cancer cases and 6016 controls and a subset of high grade cases (2480 cases). We explored height, polymorphisms in genes related to growth processes as main effects and their possible interactions. Results: The results suggest that height is associated with high-grade prostate cancer risk. Men with height 4180cm are at a 22% increased risk as compared to men with height o173cm (OR 1.22, 95% CI 1.01–1.48). Genetic variants in the growth pathway gene showed an association with prostate cancer risk. The aggregate scores of the selected variants identified a significantly increased risk of overall prostate cancer and high-grade prostate cancer by 13% and 15%, respectively, in the highest score group as compared to lowest score group. Conclusions: There was no evidence of gene-environment interaction between height and the selected candidate SNPs. Our findings suggest a role of height in high-grade prostate cancer. The effect of genetic variants in the genes related to growth is seen in all cases and high-grade prostate cancer. There is no interaction between these two exposures.</p

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Peer reviewe

Germline variation at 8q24 and prostate cancer risk in men of European ancestry

Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10−15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification