Diagnostic accuracy of transabdominal ultrasound in respect to transvaginal ultrasound in diagnosing ectopic pregnancy in a tertiary care hospital of Kolkata taking histopathology as gold standard: a prospective study

Background: Ectopic pregnancy (EP) represents an important cause of acute pelvic pain in women of reproductive age. Initial evaluation consists of appropriate history and clinical examination followed by pelvic ultrasonography (US) and hormonal assays. Objective of the study was to measure diagnostic accuracy of TAS in respect to TVS in detecting ectopic pregnancy.Methods: This prospective cross sectional study was done for 1 year duration in Nilratan Sircar Medical College and Hospital, Kolkata. 50 patients with suspected ectopic pregnancy were transferred from Gynae emergency ward and trans-abdominal, transvaginal ultrasound were subsequently performed on each. The results were corroborated with histopathology reports..Results: Diagnostic parameters of TAS in respect to HPE:sensitivity 75.5, specificity-80,PPV-97.1, NPV-26.6 (all in percentages). Diagnostic parameters of TVS in respect to HPE:sensitivity 86.6, specificity-80, PPV-97.5, NPV-40 (all in percentages).Conclusions: Sonography by transvaginal route stood way ahead of trans abdominal scan in terms of all diagnostic parameters to correctly evaluate ectopic pregnancy

Impacts of vehicle exhaust black soot on germination of gram seed (Cicer arietinum L.)

An investigation was initiated to examine the effects of carbon soot collected from exhaust tube of 15 years old petrol and diesel operated vehicles on gram seed germination and biochemical changes of seedling. In view of the widespread cultivation of gram seed in India and long-term impact of black carbon is the warming of the atmosphere as per the recommendation of IPCC (2007). Black soot were separately treated with different doses and the effects of these treatment had on seed germination, seedling vigor, chlorophyll and carotenoid content, root and shoot growth, protein, sugar, phenol and proline estimation were studied. The treatment T6 significantly affected on seed germination (84%) as well as seedling vigor and chlorophyll content. But other treatment promoted both seed germination and seedling vigor along with enhancement of other biochemical constituents. On the other hand micrograph study revealed that treatments T1 and T4 both showed negative effects on stomata rather than the ultra-structure of xylem and phloem

Adaptively inferring human transcriptional subnetworks

Although the human genome has been sequenced, progress in understanding gene regulation in humans has been particularly slow. Many computational approaches developed for lower eukaryotes to identify cis-regulatory elements and their associated target genes often do not generalize to mammals, largely due to the degenerate and interactive nature of such elements. Motivated by the switch-like behavior of transcriptional responses, we present a systematic approach that allows adaptive determination of active transcriptional subnetworks (cis-motif combinations, the direct target genes and physiological processes regulated by the corresponding transcription factors) from microarray data in mammals, with accuracy similar to that achieved in lower eukaryotes. Our analysis uncovered several new subnetworks active in human liver and in cell-cycle regulation, with similar functional characteristics as the known ones. We present biochemical evidence for our predictions, and show that the recently discovered G2/M-specific E2F pathway is wider than previously thought; in particular, E2F directly activates certain mitotic genes involved in hepatocellular carcinomas. Additionally, we demonstrate that this method can predict subnetworks in a condition-specific manner, as well as regulatory crosstalk across multiple tissues. Our approach allows systematic understanding of how phenotypic complexity is regulated at the transcription level in mammals and offers marked advantage in systems where little or no prior knowledge of transcriptional regulation is available

A Primer on Regression Methods for Decoding cis-Regulatory Logic

The rapidly emerging field of systems biology is helping us to understand the molecular determinants of phenotype on a genomic scale [1]. Cis-regulatory elements are major sequence-based determinants of biological processes in cells and tissues [2]. For instance, during transcriptional regulation, transcription factors (TFs) bind to very specific regions on the promoter DNA [2,3] and recruit the basal transcriptional machinery, which ultimately initiates mRNA transcription (Figure 1A). Learning cis-Regulatory Elements from Omics Data A vast amount of work over the past decade has shown that omics data can be used to learn cis-regulatory logic on a genome-wide scale [4-6]--in particular, by integrating sequence data with mRNA expression profiles. The most popular approach has been to identify over-represented motifs in promoters of genes that are coexpressed [4,7,8]. Though widely used, such an approach can be limiting for a variety of reasons. First, the combinatorial nature of gene regulation is difficult to explicitly model in this framework. Moreover, in many applications of this approach, expression data from multiple conditions are necessary to obtain reliable predictions. This can potentially limit the use of this method to only large data sets [9]. Although these methods can be adapted to analyze mRNA expression data from a pair of biological conditions, such comparisons are often confounded by the fact that primary and secondary response genes are clustered together--whereas only the primary response genes are expected to contain the functional motifs [10]. A set of approaches based on regression has been developed to overcome the above limitations [11-32]. These approaches have their foundations in certain biophysical aspects of gene regulation [26,33-35]. That is, the models are motivated by the expected transcriptional response of genes due to the binding of TFs to their promoters. While such methods have gathered popularity in the computational domain, they remain largely obscure to the broader biology community. The purpose of this tutorial is to bridge this gap. We will focus on transcriptional regulation to introduce the concepts. However, these techniques may be applied to other regulatory processes. We will consider only eukaryotes in this tutorial

A correlation with exon expression approach to identify cis-regulatory elements for tissue-specific alternative splicing

Correlation of motif occurrences with gene expression intensity is an effective strategy for elucidating transcriptional cis-regulatory logic. Here we demonstrate that this approach can also identify cis-regulatory elements for alternative pre-mRNA splicing. Using data from a human exon microarray, we identified 56 cassette exons that exhibited higher transcript-normalized expression in muscle than in other normal adult tissues. Intron sequences flanking these exons were then analyzed to identify candidate regulatory motifs for muscle-specific alternative splicing. Correlation of motif parameters with gene-normalized exon expression levels was examined using linear regression and linear splines on RNA words and degenerate weight matrices, respectively. Our unbiased analysis uncovered multiple candidate regulatory motifs for muscle-specific splicing, many of which are phylogenetically conserved among vertebrate genomes. The most prominent downstream motifs were binding sites for Fox1- and CELF-related splicing factors, and a branchpoint-like element acuaac; pyrimidine-rich elements resembling PTB-binding sites were most significant in upstream introns. Intriguingly, our systematic study indicates a paucity of novel muscle-specific elements that are dominant in short proximal intronic regions. We propose that Fox and CELF proteins play major roles in enforcing the muscle-specific alternative splicing program, facilitating expression of unique isoforms of cytoskeletal proteins critical to muscle cell function

A systems analysis of the chemosensitivity of breast cancer cells to the polyamine analogue PG-11047

<p>Abstract</p> <p>Background</p> <p>Polyamines regulate important cellular functions and polyamine dysregulation frequently occurs in cancer. The objective of this study was to use a systems approach to study the relative effects of PG-11047, a polyamine analogue, across breast cancer cells derived from different patients and to identify genetic markers associated with differential cytotoxicity.</p> <p>Methods</p> <p>A panel of 48 breast cell lines that mirror many transcriptional and genomic features present in primary human breast tumours were used to study the antiproliferative activity of PG-11047. Sensitive cell lines were further examined for cell cycle distribution and apoptotic response. Cell line responses, quantified by the GI₅₀(dose required for 50% relative growth inhibition) were correlated with the omic profiles of the cell lines to identify markers that predict response and cellular functions associated with drug sensitivity.</p> <p>Results</p> <p>The concentrations of PG-11047 needed to inhibit growth of members of the panel of breast cell lines varied over a wide range, with basal-like cell lines being inhibited at lower concentrations than the luminal cell lines. Sensitive cell lines showed a significant decrease in S phase fraction at doses that produced little apoptosis. Correlation of the GI₅₀values with the omic profiles of the cell lines identified genomic, transcriptional and proteomic variables associated with response.</p> <p>Conclusions</p> <p>A 13-gene transcriptional marker set was developed as a predictor of response to PG-11047 that warrants clinical evaluation. Analyses of the pathways, networks and genes associated with response to PG-11047 suggest that response may be influenced by interferon signalling and differential inhibition of aspects of motility and epithelial to mesenchymal transition.</p> <p>See the related commentary by Benes and Settleman: <url>http://www.biomedcentral.com/1741-7015/7/78</url></p

Basal-Subtype and MEK-Pl3K Feedback Signaling Determine Susceptibility of Breast Cancer Cells to MEK Inhibition

Specific inhibitors of MEK have been developed that efficiently inhibit the oncogenic RAF-MEK-ERK pathway. We employed a systems-based approach to identify breast cancer subtypes particularly susceptible to MEK inhibitors and to understand molecular mechanisms conferring resistance to such compounds. Basal-type breast cancer cells were found to be particularly susceptible to growth-inhibition by small-molecule MEK inhibitors. Activation of the PI3 kinase pathway in response to MEK inhibition through a negative MEK-EGFR-PI3 kinase feedback loop was found to limit efficacy. Interruption of this feedback mechanism by targeting MEK and PI3 kinase produced synergistic effects, including induction of apoptosis and, in some cell lines, cell cycle arrest and protection from apoptosis induced by proapoptotic agents. These findings enhance our understanding of the interconnectivity of oncogenic signal transduction circuits and have implications for the design of future clinical trials of MEK inhibitors in breast cancer by guiding patient selection and suggesting rational combination therapies