Clinicoradiological correlation in birth asphyxia

Background: Hypoxic Ischemic Encephalopathy (HIE) is the most dreaded neurological disease of the new-born. Assessment of severity of HIE would help proper parent counseling and early institution of stimulation therapy for better development of the infant.Methods: This study was conducted between December 2012 and May 2014. 37 term neonates with perinatal asphyxia were the subjects. The cranial ultrasound, EEG and MRI findings of these babies are analysed and correlated with each other and with clinical staging and the neurological condition of the babies at discharge.Results: Among the 37 neonates, 21 were of HIE stage 2 and 16 were of stage 3. Sensitivity of EEG in detecting abnormality in the neurological condition according to our study is 76.9%, specificity 87.5%, positive predictive value 76.9%, negative predictive value 87.5%. Sensitivity of severe pattern of injury in MRI brain in detecting abnormality in neurological condition according to our study is 76.9%, specificity 91.6%, positive predictive value 83.3%, negative predictive value 88%. Involvement of both basal ganglia and cortex in MRI brain had statistically significant correlation with abnormal neurological condition at discharge in our study (P = 0.04).Conclusion: An abnormal EEG and MRI brain in a term new-born with Hypoxic Ischemic Encephalopathy (HIE) is associated with poor neurological outcome. Involvement of basal ganglia/thalamus and cortex together in the MRI are predictors of abnormal outcome.

Acceptable Risk

Perhaps the topic of acceptable risk never had a sexier and more succinct introduction than the one Edward Norton, playing an automobile company executive, gave it in Fight Club: “Take the number of vehicles in the field (A), multiply it by the probable rate of failure (B), and multiply the result by the average out of court settlement (C). A*B*C=X. If X is less than the cost of the recall, we don’t do one.” Of course, this dystopic scene also gets to the heart of the issue in another way: acceptable risk deals with mathematical calculations about the value of life, injury, and emotional wreckage, making calculation a difficult matter ethically, politically, and economically. This entry will explore the history of this idea, focusing on its development alongside statistics into its wide importance today

Increase in Ethanol Yield via Elimination of Lactate Production in an Ethanol-Tolerant Mutant of Clostridium Thermocellum

Large-scale production of lignocellulosic biofuel is a potential solution to sustainably meet global energy needs. One-step consolidated bioprocessing (CBP) is a potentially advantageous approach for the production of biofuels, but requires an organism capable of hydrolyzing biomass to sugars and fermenting the sugars to ethanol at commercially viable titers and yields. Clostridium thermocellum, a thermophilic anaerobe, can ferment cellulosic biomass to ethanol and organic acids, but low yield, low titer, and ethanol sensitivity remain barriers to industrial production. Here, we deleted the hypoxanthine phosphoribosyltransferase gene in ethanol tolerant strain of C. thermocellum adhE*(EA) in order to allow use of previously developed gene deletion tools, then deleted lactate dehydrogenase (ldh) to redirect carbon flux towards ethanol. Upon deletion of ldh, the adhE*(EA) Δldh strain produced 30% more ethanol than wild type on minimal medium. The adhE*(EA) Δldh strain retained tolerance to 5% v/v ethanol, resulting in an ethanol tolerant platform strain of C. thermocellum for future metabolic engineering efforts

Targeting of Histone Acetyltransferase p300 by Cyclopentenone Prostaglandin Δ12-PGJ2 through Covalent Binding to Cys1438

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Chemical Research in Toxicology, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see http://pubs.acs.org/doi/abs/10.1021/tx200383cInhibitors of histone acetyltransferases (HATs) are perceived to treat diseases like cancer, neurodegeneration, and AIDS. On the basis of previous studies, we hypothesized that Cys1438 in the substrate binding site could be targeted by Δ12-prostaglandin J2 (Δ12-PGJ2), a cyclopentenone prostaglandin (CyPG) derived from PGD2. We demonstrate here the ability of CyPGs to inhibit p300 HAT-dependent acetylation of histone H3. A cell-based assay system clearly showed that the α,β-unsaturation in the cyclopentenone ring of Δ12-PGJ2 was crucial for the inhibitory activity, while the 9,10-dihydro-15-deoxy- Δ12,14-PGJ2, which lacks the electrophilic carbon (at carbon 9), was ineffective. Molecular docking studies suggested that Δ12-PGJ2 places the electrophilic carbon in the cyclopentenone ring well within the vicinity of Cys1438 of p300 to form a covalent Michael adduct. Site-directed mutagenesis of the p300 HAT domain, peptide competition assay involving p300 wild type and mutant peptides, followed by mass spectrometric analysis confirmed the covalent interaction of Δ12-PGJ2 with Cys1438. Using biotinylated derivatives of Δ12-PGJ2 and 9,10-dihydro-15-deoxy- Δ12,14-PGJ2, we demonstrate the covalent interaction of Δ12-PGJ2 with the p300 HAT domain, but not the latter. In agreement with the in vitro filter binding assay, CyPGs were also found to inhibit H3 histone acetylation in cell-based assays. In addition, Δ12-PGJ2 also inhibited the acetylation of the HIV-1 Tat by recombinant p300 in in vitro assays. This study demonstrates, for the first time, that Δ12-PGJ2 inhibits p300 through Michael addition, where α,β-unsaturated carbonyl function is absolutely required for the inhibitory activity

Effect of Parameter Distributions on Uncertainty Analysis of Hydrologic Models

Increasing concern about the accuracy of hydrologic and water quality models has prompted interest in procedures for evaluating the uncertainty associated with these models. If a Monte Carlo simulation is used in an uncertainty analysis, assumptions must be made relative to the probability distributions to assign to the model input parameters. Some have indicated that since these parameters can not be readily determined, uncertainty analysis is of limited value. In this article we have evaluated the impact of parameter distribution assumptions on estimates of model output uncertainty. We conclude that good estimates of the means and variances of the input parameters are of greater importance than the actual form of the distribution. This conclusion is based on an analysis using the AGNPS model