Platelet count as a prognostic indicator in pregnancy induced hypertension

Background: Hypertensive disorders are most common medical complications of pregnancy, and are one of the major causes of maternal and fetal morbidity and mortality. Thrombocytopenia complicating hypertensive disorders of pregnancy are responsible for approximately 20% of all cases of thrombocytopenia during pregnancy.Our study was done to assess the utility of platelet count as a prognostic indicator in pregnancy induced hypertension to recognize and manage early the complications arising and to have a better pregnancy outcome.Methods: This study includes 76 cases of pregnancy induced hypertension over a period of 18 months. Platelet estimation was done for all cases and patients with documented platelet count of less than 1,50,000/cumm was documented as thrombocytopenia.Results: Of the 76 cases of pregnancy induced hypertension, 32 (42.1%) were diagnosed with thrombocytopenia, and an increased incidence of maternal and fetal morbidity & mortality was observed.Conclusions: Our study and the results show that the assay of platelets can be considered as one of the prognostic tool in management of hypertensive disorders of pregnancy

Long Non Coding RNA in Triple Negative Breast Cancer: A Promising Biomarker in Tumorigenesis

Globally, Triple-negative breast cancer (TNBC) is an unsurpassed variant of breast cancer (BC) with a very high fatality rate, and disease burden. Nevertheless, the deficit of diagnostic markers and focused treatment are major hurdles for potent therapeutics. They are also the reason for bad outcomes and causes of a worse prognosis and a high rate of flare up in patients with TNBC diagnosis. Long non-coding RNAs (lncRNA) are a new class of molecules that have recently gained interest in healthcare management due to their potential as biomarkers for human diseases especially cancers. The growing interest in lncRNA in clinical practice has created an unmet need for developing assays to test lncRNA quickly and accurately for early diagnostics. These lncRNA modulate multiple stages of tumor development, including growth, proliferation, invasion, angiogenesis, and metastases, by controlling several genes and changing metabolic networks. Highly invasive phenotype and chemo resistance are prominent characteristics of TNBC subtypes that require accurate diagnostic and prognostic instruments involving lncRNA. This review focusses on the evolving purpose and coalition of lncRNAs in TNBC and accentuates their capable effects in diagnosis and treatment of cancer. Moreover, the extensive literature analysis of our review creates an opportunity in the translational application concerning the TNBC lncRNAs described until now. The depiction of lncRNAs enrolled in TNBC is comprehensive, and sufficient substantiation studies are the need of the hour to authenticate the current outcomes and create imminent upcoming of elemental research setting into clinical practice

Effectiveness of symptom screening and incidence of tuberculosis among adults and children living with HIV infection in India.

BACKGROUND WHO recommends the use of a simplified symptom-based algorithm for screening for tuberculosis (TB) among people living with HIV (PLHIV). We assessed the feasibility and effectiveness of this algorithm and determined the prevalence and incidence of TB among PLHIV attending antiretroviral treatment (ART) centres in India. METHODS We did a prospective multicentric implementation research study in four states of India. To rule out TB, we administered the WHO symptom-screen algorithm to all PLHIV every month for 6 months. If they were found to be symptomatic any time during this period, they were referred for investigations for TB. A case of TB diagnosed during the first month of screening was taken as a prevalent case while those detected TB in the subsequent 5 months were considered cases of incident TB. We calculated the incidence rate using the person-years method. Results . Between May 2012 and October 2013, a total of 6099 adults and 1662 children living with HIV were screened for TB at the ART centres of four states. Of the 6099 adult PLHIV, 1815 (30%) had at least one symptom suggestive of TB, of whom only 634 (35%) were referred for investigations of TB. Of those referred, 97 (15%) PLHIV were diagnosed with TB. Overall, the prevalence of undiagnosed TB was 0.84 person-years and in the subsequent period, the incidence of TB was 2.4/100 person-years (95% CI 1.90-3.10). Among 1662 children, 434 (26%) had at least one symptom suggestive of TB. But only 57 (13%) children were referred for investigations of TB and 13 (23%) of them were diagnosed with TB. The prevalence of TB among children was 0.5% and its incidence among them was 2.7/100 person-years (95% CI 1.60-4.30). CONCLUSION Prevalence and incidence of TB is high among PLHIV attending ART centres. This emphasizes the need to strengthen regular screening for symptoms of TB and further referral of those symptomatic for diagnosis of TB

Tension and Robustness in Multitasking Cellular Networks

Cellular networks multitask by exhibiting distinct, context-dependent dynamics. However, network states (parameters) that generate a particular dynamic are often sub-optimal for others, defining a source of “tension” between them. Though multitasking is pervasive, it is not clear where tension arises, what consequences it has, and how it is resolved. We developed a generic computational framework to examine the source and consequences of tension between pairs of dynamics exhibited by the well-studied RB-E2F switch regulating cell cycle entry. We found that tension arose from task-dependent shifts in parameters associated with network modules. Although parameter sets common to distinct dynamics did exist, tension reduced both their accessibility and resilience to perturbation, indicating a trade-off between “one-size-fits-all” solutions and robustness. With high tension, robustness can be preserved by dynamic shifting of modules, enabling the network to toggle between tasks, and by increasing network complexity, in this case by gene duplication. We propose that tension is a general constraint on the architecture and operation of multitasking biological networks. To this end, our work provides a framework to quantify the extent of tension between any network dynamics and how it affects network robustness. Such analysis would suggest new ways to interfere with network elements to elucidate the design principles of cellular networks

High Confidence Prediction of Essential Genes in Burkholderia Cenocepacia

BACKGROUND: Essential genes are absolutely required for the survival of an organism. The identification of essential genes, besides being one of the most fundamental questions in biology, is also of interest for the emerging science of synthetic biology and for the development of novel antimicrobials. New antimicrobial therapies are desperately needed to treat multidrug-resistant pathogens, such as members of the Burkholderia cepacia complex. METHODOLOGY/PRINCIPAL FINDINGS: We hypothesize that essential genes may be highly conserved within a group of evolutionary closely related organisms. Using a bioinformatics approach we determined that the core genome of the order Burkholderiales consists of 649 genes. All but two of these identified genes were located on chromosome 1 of Burkholderia cenocepacia. Although many of the 649 core genes of Burkholderiales have been shown to be essential in other bacteria, we were also able to identify a number of novel essential genes present mainly, or exclusively, within this order. The essentiality of some of the core genes, including the known essential genes infB, gyrB, ubiB, and valS, as well as the so far uncharacterized genes BCAL1882, BCAL2769, BCAL3142 and BCAL3369 has been confirmed experimentally in B. cenocepacia. CONCLUSIONS/SIGNIFICANCE: We report on the identification of essential genes using a novel bioinformatics strategy and provide bioinformatics and experimental evidence that the large majority of the identified genes are indeed essential. The essential genes identified here may represent valuable targets for the development of novel antimicrobials and their detailed study may shed new light on the functions required to support life

Lithium chloride therapy fails to improve motor function in a transgenic mouse model of Machado-Joseph disease

The accumulation of misfolded proteins in neurons, leading to the formation of cytoplasmic and nuclear aggregates, is a common theme in age-related neurodegenerative diseases, possibly due to disturbances of the proteostasis and insufficient activity of cellular protein clearance pathways. Lithium is a well-known autophagy inducer that exerts neuroprotective effects in different conditions and has been proposed as a promising therapeutic agent for several neurodegenerative diseases. We tested the efficacy of chronic lithium 10.4 mg/kg) treatment in a transgenic mouse model of Machado-Joseph disease, an inherited neurodegenerative disease, caused by an expansion of a polyglutamine tract within the protein ataxin-3. A battery of behavioral tests was used to assess disease progression. In spite of activating autophagy, as suggested by the increased levels of Beclin-1, Atg7, and LC3II, and a reduction in the p62 protein levels, lithium administration showed no overall beneficial effects in this model concerning motor performance, showing a positive impact only in the reduction of tremors at 24 weeks of age. Our results do not support lithiumchronic treatment as a promising strategy for the treatment of Machado-Joseph disease (MJD).FCT -Fundação para a Ciência e a Tecnologia(SFRH/BD/51059/2010

Mapping the Environmental Fitness Landscape of a Synthetic Gene Circuit

Gene expression actualizes the organismal phenotypes encoded within the genome in an environment-dependent manner. Among all encoded phenotypes, cell population growth rate (fitness) is perhaps the most important, since it determines how well-adapted a genotype is in various environments. Traditional biological measurement techniques have revealed the connection between the environment and fitness based on the gene expression mean. Yet, recently it became clear that cells with identical genomes exposed to the same environment can differ dramatically from the population average in their gene expression and division rate (individual fitness). For cell populations with bimodal gene expression, this difference is particularly pronounced, and may involve stochastic transitions between two cellular states that form distinct sub-populations. Currently it remains unclear how a cell population's growth rate and its subpopulation fractions emerge from the molecular-level kinetics of gene networks and the division rates of single cells. To address this question we developed and quantitatively characterized an inducible, bistable synthetic gene circuit controlling the expression of a bifunctional antibiotic resistance gene in Saccharomyces cerevisiae. Following fitness and fluorescence measurements in two distinct environments (inducer alone and antibiotic alone), we applied a computational approach to predict cell population fitness and subpopulation fractions in the combination of these environments based on stochastic cellular movement in gene expression space and fitness space. We found that knowing the fitness and nongenetic (cellular) memory associated with specific gene expression states were necessary for predicting the overall fitness of cell populations in combined environments. We validated these predictions experimentally and identified environmental conditions that defined a “sweet spot” of drug resistance. These findings may provide a roadmap for connecting the molecular-level kinetics of gene networks to cell population fitness in well-defined environments, and may have important implications for phenotypic variability of drug resistance in natural settings

MicroRNAs hsa-miR-99b, hsa-miR-330, hsa-miR-126 and hsa-miR-30c: Potential Diagnostic Biomarkers in Natural Killer (NK) Cells of Patients with Chronic Fatigue Syndrome (CFS)/ Myalgic Encephalomyelitis (ME)

Chronic Fatigue Syndrome (CFS/ME) is a complex multisystem disease of unknown aetiology which causes debilitating symptoms in up to 1% of the global population. Although a large cohort of genes have been shown to exhibit altered expression in CFS/ME patients, it is currently unknown whether microRNA (miRNA) molecules which regulate gene translation contribute to disease pathogenesis. We hypothesized that changes in microRNA expression in patient leukocytes contribute to CFS/ME pathology, and may therefore represent useful diagnostic biomarkers that can be detected in the peripheral blood of CFS/ME patients.miRNA expression in peripheral blood mononuclear cells (PBMC) from CFS/ME patients and healthy controls was analysed using the Ambion Bioarray V1. miRNA demonstrating differential expression were validated by qRT-PCR and then replicated in fractionated blood leukocyte subsets from an independent patient cohort. The CFS/ME associated miRNA identified by these experiments were then transfected into primary NK cells and gene expression analyses conducted to identify their gene targets.Microarray analysis identified differential expression of 34 miRNA, all of which were up-regulated. Four of the 34 miRNA had confirmed expression changes by qRT-PCR. Fractionating PBMC samples by cell type from an independent patient cohort identified changes in miRNA expression in NK-cells, B-cells and monocytes with the most significant abnormalities occurring in NK cells. Transfecting primary NK cells with hsa-miR-99b or hsa-miR-330-3p, resulted in gene expression changes consistent with NK cell activation but diminished cytotoxicity, suggesting that defective NK cell function contributes to CFS/ME pathology.This study demonstrates altered microRNA expression in the peripheral blood mononuclear cells of CFS/ME patients, which are potential diagnostic biomarkers. The greatest degree of miRNA deregulation was identified in NK cells with targets consistent with cellular activation and altered effector function

Rational Diversification of a Promoter Providing Fine-Tuned Expression and Orthogonal Regulation for Synthetic Biology

Yeast is an ideal organism for the development and application of synthetic biology, yet there remain relatively few well-characterised biological parts suitable for precise engineering of this chassis. In order to address this current need, we present here a strategy that takes a single biological part, a promoter, and re-engineers it to produce a fine-graded output range promoter library and new regulated promoters desirable for orthogonal synthetic biology applications. A highly constitutive Saccharomyces cerevisiae promoter, PFY1p, was identified by bioinformatic approaches, characterised in vivo and diversified at its core sequence to create a 36-member promoter library. TetR regulation was introduced into PFY1p to create a synthetic inducible promoter (iPFY1p) that functions in an inverter device. Orthogonal and scalable regulation of synthetic promoters was then demonstrated for the first time using customisable Transcription Activator-Like Effectors (TALEs) modified and designed to act as orthogonal repressors for specific PFY1-based promoters. The ability to diversify a promoter at its core sequences and then independently target Transcription Activator-Like Orthogonal Repressors (TALORs) to virtually any of these sequences shows great promise toward the design and construction of future synthetic gene networks that encode complex “multi-wire” logic functions