Correlation of troponin-I level with left ventricular systolic dysfunction after first attack of non-ST segment elevation myocardial infarction

Background: Coronary Heart Disease (CHD) is the most common category of the heart disease and is found to be the single most important cause that leads to premature death in the developed world. Recognizing a patient with ACS is important because the diagnosis triggers both triage and management. cTnI is 100% tissue-specific for the myocardium and it has shown itself as a very sensitive and specific marker for AMI. Ventricular function is the best predictor of death after an ACS. It serves as a marker of myocardial damage and provides information on systolic function as well as diagnosis and prognosis. The study aimed at investigating the impact of LVEF on elevated troponin-I level in patients with first attack of NSTEMI.Methods: This cross-sectional analytical study was conducted in the department of cardiology in Mymensingh Medical College Hospital from December, 2015 to November, 2016. Total 130 first attack of NSTEMI patients were included considering inclusion and exclusion criteria. The sample population was divided into two groups: Group-I: Patients with first attack of NSTEMI with LVEF: ≥55%. Group-II: Patients with first attack of NSTEMI with LVEF: <55%. Then LVEF and troponin-I levels were correlated using Pearson’s correlation coefficient test.Results: In this study mean troponin-I of group-I and group-II were 5.53±7.43 and 16.46±15.79ng/ml respectively. It was statistically significant (p<0.05). The mean LVEF value of groups were 65.31±10.30% and 40.17±4.62% respectively. It was statistically significant (p<0.05). The echocardiography showed that patients with high troponin-I level had low LVEF and patients with low troponin-I level had preserved LVEF. Analysis showed that patients with highest level of troponin-I had severe left ventricular systolic dysfunction (LVEF <35%) and vice versa-the patients with the lowest levels of troponin-I had preserved systolic function (LVEF ≥55%). In our study, it also showed that the levels of troponin-I had negative correlation with LVEF levels with medium strength of association (r= -0.5394, p=0.001). Our study also discovered that Troponin-I level ≥6.6ng/ml is a very sensitive and specific marker for LV systolic dysfunction.Conclusions: The study has enabled the research team to conclude that the higher is the Troponin-I level the lower is the LVEF level and thus more severe is the LV systolic dysfunction in first attack of NSTEMI patients

A clinical study of arrhythmias associated with acute coronary syndrome: a hospital based study of a high risk and previously undocumented population

Background: ACS represents a global epidemic. Arrhythmia in ACS is common. Careful investigation may lead to further improvement of prognosis. Retrospectively analyzed the year- round data of our center. Study was undertaken to analyze the incidence, frequency and type of arrhythmias in ACS. This is to aid timely intervention and to modify the outcome. Identification of the type of arrhythmia is of therapeutic and prognostic importance.Methods: This cross sectional analytical study was conducted in the Department of Cardiology, Apollo Hospitals Dhaka, from January 2019 to January 2020 with ACS patients. Enrolled consecutively and data analyzed.Results: There were 500 patients enrolled considering inclusion and exclusion criteria. Sample was subdivided into 3 groups on the type of ACS. Group-I with UA, Group-II with NSTE - ACS and Group-III with STE - ACS. Different types of arrhythmia noted. Types of arrhythmia were correlated with type of ACS. 500 patients included. Mean age 55.53±12.70, 71.6% male and 28.4% female. 60.4% hypertensive, 46.2% diabetic, 20.2% positive family history of CAD, 32.2% current smoker, 56.4% dyslipidaemic and 9.6% asthmatic. 31.2% UA, 39.2% NSTE-ACS and 29.6% STE-ACS. Type of arrhythmias noted. 22% sinus tachycardia, 20.2% sinus bradycardia, 9% atrial fibrillation, 5.2% ventricular ectopic, 4.8% supra ventricular ectopic, 2.8% bundle branch block, 2.2% atrio-ventricular block, 1% broad complex tachycardia, 0.4% narrow complex tachycardia, 0.2% sinus node dysfunction and 32.2% without any arrhythmia. Significant incidences of arrhythmia detected - respectively 29.8%, 39.2% and 31%, p<0.001.Conclusions: In conclusion, arrhythmias in ACS are common. More attention should be paid to improve their treatment and prognosis

Biosynthesis and mechanism of action of enterococcal cytolysin

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a large, structurally diverse group of natural products that are united by a common biosynthetic logic. During RiPP biosynthesis, a genetically encoded precursor peptide is post-translationally modified by enzymes. The precursor peptide is typically composed of an N-terminal leader peptide and a C-terminal core peptide. The leader peptide serves as a recognition motif for the modification enzymes that subsequently catalyze transformations on the core peptide. The separation between substrate recognition on the leader peptide from catalysis on the core peptide allows RiPP modification enzymes to be inherently substrate tolerant. Changes to the core peptide are generally well tolerated, as long as the recognition motif on the leader peptide is not perturbed. Detailed understanding of the mechanism of substrate recognition in RiPP biosynthesis can enable RiPP enzymes to be utilized in a variety of biotechnological platforms. In chapter 2, the mode of substrate recognition between the class II lanthipeptide synthetase, HalM2, and the leader peptide of its cognate substrate, HalA2 is described. Critical residues on the leader peptide required for substrate recognition and processing were identified. Furthermore, the capping helices on HalM2 were determined to be involved in leader peptide binding. In chapter 3, the interactions identified were applied to strategically position cysteine residues on both the substrate and enzyme to generate covalent substrate-enzyme complexes. The complexes were found to be catalytically competent, thus providing a platform to investigate the positional requirements of the leader peptide during catalysis. Chapter 4 focuses on the structure-activity relationships of an unusual class II lanthipeptide known as enterococcal cytolysin. Cytolysin is composed of two subunits, a large subunit, CylLL” and a small subunit, CylLS”. Cytolysin is a virulence factor produced by pathogenic strains of Enterococci and has been directly linked to human disease and mortality. Amongst lanthipeptides, cytolysin displays a unique bioactivity profile with potent lytic activity against both gram-positive bacteria and mammalian erythrocytes. Alanine scanning mutagenesis of every residue in both subunits of cytolysin was performed and bioactivity was determined for every mutant. Specific residues appear to dictate cell-type specificity, suggesting that the molecular target of cytolysin may be a structurally related molecule between the two cell types. Additionally, I provide evidence that CylLL” binds to bacterial cell membranes first, potentiating the lytic activity of CylLS”. In chapter 5, I provide insights into the molecular target of cytolysin in both bacterial and mammalian systems. These insights set the stage to understanding the molecular recognition of cytolysin and target cells.LimitedAuthor requested closed access (OA after 2yrs) in Vireo ETD syste

Search for conserved patterns in RNA structures

RNA molecules play an intricate role in many cellular processes, but unlike protein and DNA, our abilities to predict and compare RNA structures are inadequate. Divergent RNA molecules with similar functions are likely to have similar structures but might have no detectable resemblance in sequence. So, a sequence homology based approach for prediction and comparison is not very reliable. Moreover, predicted Minimum Free Energy (MFE) structures do not predict pseudoknots, and a large fraction of biologically relevant stems may be missing due to restrictions of the algorithms and inaccuracies in energy parameters. However, a reasonable strategy is to analyze the ensemble of predicted suboptimal structures to find additional biologically relevant stems, especially pseudoknots. We use a graph framework (XIOS RNA graph) to represent these structures and learn biologically important motifs by comparative analysis. We convert RNA structures to XIOS RNA graphs, where a stem is a vertex and the relationships between stems are represented as different types of edges, including pseudoknots and mutually exclusive relationship between stems. Hence, ensembles of RNA structures can be represented in a single. First, we generate a comprehensive representation of RNA, which includes all biological stems, from predicted suboptimal structures. Since individual suboptimal structures do not contain pseudoknots, we incorporate likely pseudoknots by considering all unique stems in the ensemble of structures. One of our findings shows that, at the cost of overprediction, the accuracy of predicting stems and pseudoknots increases as more suboptimal structures are considered. We reduce the complexity of XIOS RNA graphs by removing similar stems while preserving those that are biologically important. We enumerate the topologies of all possible stems that can be formed with respect to another stem. Then, we identify the instances where the topological space can be reduced by merging similar stems, creating the basis for developing a set of heuristics rules to contract these graph. We also have developed methods to remove infrequent base pairs from the ensemble. We have developed a RNA structure comparison tool, XIOSMatch, by optimizing, extending and parallelizing a maximal subgraph isomorphism algorithm (gSpan), and use it to identify the largest topological match in a set of RNA graphs. We apply our tool to different RNAs and demonstrate that the conserved motifs discovered for various RNA species are likely to have functional and structural significance

RNA-seq analysis of <i>Drosophila</i> clock and non-clock neurons reveals neuron-specific cycling and novel candidate neuropeptides

<div><p>Locomotor activity rhythms are controlled by a network of ~150 circadian neurons within the adult <i>Drosophila</i> brain. They are subdivided based on their anatomical locations and properties. We profiled transcripts “around the clock” from three key groups of circadian neurons with different functions. We also profiled a non-circadian outgroup, dopaminergic (TH) neurons. They have cycling transcripts but fewer than clock neurons as well as low expression and poor cycling of clock gene transcripts. This suggests that TH neurons do not have a canonical circadian clock and that their gene expression cycling is driven by brain systemic cues. The three circadian groups are surprisingly diverse in their cycling transcripts and overall gene expression patterns, which include known and putative novel neuropeptides. Even the overall phase distributions of cycling transcripts are distinct, indicating that different regulatory principles govern transcript oscillations. This surprising cell-type diversity parallels the functional heterogeneity of the different neurons.</p></div

Conserved piRNA Expression from a Distinct Set of piRNA Cluster Loci in Eutherian Mammals

The Piwi pathway is deeply conserved amongst animals because one of its essential functions is to repress transposons. However, many Piwi-interacting RNAs (piRNAs) do not base-pair to transposons and remain mysterious in their targeting function. The sheer number of piRNA cluster (piC) loci in animal genomes and infrequent piRNA sequence conservation also present challenges in determining which piC loci are most important for development. To address this question, we determined the piRNA expression patterns of piC loci across a wide phylogenetic spectrum of animals, and reveal that most genic and intergenic piC loci evolve rapidly in their capacity to generate piRNAs, regardless of known transposon silencing function. Surprisingly, we also uncovered a distinct set of piC loci with piRNA expression conserved deeply in Eutherian mammals. We name these loci Eutherian-Conserved piRNA cluster (ECpiC) loci. Supporting the hypothesis that conservation of piRNA expression across ~100 million years of Eutherian evolution implies function, we determined that one ECpiC locus generates abundant piRNAs antisense to the STOX1 transcript, a gene clinically associated with preeclampsia. Furthermore, we confirmed reduced piRNAs in existing mouse mutations at ECpiC-Asb1 and -Cbl, which also display spermatogenic defects. The Asb1 mutant testes with strongly reduced Asb1 piRNAs also exhibit up-regulated gene expression profiles. These data indicate ECpiC loci may be specially adapted to support Eutherian reproduction.National Institutes of Health (U.S.) (R01GM081871

Transcripts enriched specifically in one group of circadian neurons.

<p>A) The percentage of transcripts specifically enriched in each of the circadian neuronal groups is represented in a bar graph. LNvs are shown in green. LNds are shown in blue. DN1s are shown in red. The absolute number of enriched genes is indicated in each bar. Results of gene ontology analysis (GO) are included. B, C, and D) Boxplots showing the expression levels of some of the most significantly enriched transcripts in the LNvs (B), LNds (C) and DN1s (D). The purple bar indicates the mean. The asterix denotes those transcripts that show high variability due to cycling transcripts levels.</p

Most cycling gene expression is specific to one group of circadian neurons.

<p>In all figures, LNvs are shown in green, LNds are shown in blue, DN1s are shown in read, and TH are shown in orange. A) <i>Timeless</i> (<i>tim</i>) cycles in all three neuronal groups with similar phase and expression level. Transcript levels are represented as reads/million total reads in a log base 2 scale. Two independent six timepoint datasets are concatenated to show cycling. B) Overlap of the high-confidence (HC) cycling transcripts found in the four neuronal groups. Only 4 HC cycling transcripts are in common in the 3 groups of circadian neurons. C) Dh31 is a HC cycling transcript in both the LNvs (green) and DN1s (red) with peak expression in the morning. The dotted line denotes the 3’end of the LNv specific Dh31 isoform. The isoform of Dh31 expressed in DN1s has an extended 3’-UTR. See also <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006613#pgen.1006613.g003" target="_blank">Fig 3</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006613#pgen.1006613.s004" target="_blank">S1 Fig</a> and <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006613#pgen.1006613.s005" target="_blank">S2 Fig</a>.</p

Common transcripts in circadian neurons.

<p>Common transcripts in circadian neurons.</p