1,326 research outputs found

    Electroencephalogram of Healthy Horses During Inhaled Anesthesia.

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    BackgroundPrevious study of the diagnostic validity of electroencephalography (EEG) to detect abnormalities in equine cerebral cortical function relied on the administration of various drugs for sedation, induction, and maintenance of general anesthesia but used identical criteria to interpret recordings.ObjectivesTo determine the effects of 2 inhalation anesthetics on the EEG of healthy horses.AnimalsSix healthy horses.MethodsProspective study. After the sole administration of one of either isoflurane or halothane at 1.2, 1.4, and 1.6 times the minimum alveolar concentration, EEG was recorded during controlled ventilation, spontaneous ventilation, and nerve stimulation.ResultsBurst suppression was observed with isoflurane, along with EEG events that resembled epileptiform discharges. Halothane results were variable between horses, with epileptiform-like discharges and bursts of theta, alpha, and beta recorded intermittently. One horse died and 2 were euthanized as the result of anesthesia-related complications.Conclusions and clinical importanceThe results of this study indicate that the effects of halothane and isoflurane on EEG activity in the normal horse can be quite variable, even when used in the absence of other drugs. It is recommended that equine EEG be performed without the use of these inhalation anesthetics and that general anesthesia be induced and maintained by other contemporary means

    Qualitative and Quantitative Characteristics of the Electroencephalogram in Normal Horses during Administration of Inhaled Anesthesia.

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    BackgroundThe effects of anesthesia on the equine electroencephalogram (EEG) after administration of various drugs for sedation, induction, and maintenance are known, but not that the effect of inhaled anesthetics alone for EEG recording.ObjectiveTo determine the effects of isoflurane and halothane, administered as single agents at multiple levels, on the EEG and quantitative EEG (qEEG) of normal horses.AnimalsSix healthy horses.MethodsProspective study. Digital EEG with video and quantitative EEG (qEEG) were recorded after the administration of one of the 2 anesthetics, isoflurane or halothane, at 3 alveolar doses (1.2, 1.4 and 1.6 MAC). Segments of EEG during controlled ventilation (CV), spontaneous ventilation (SV), and with peroneal nerve stimulation (ST) at each MAC multiple for each anesthetic were selected, analyzed, and compared. Multiple non-EEG measurements were also recorded.ResultsSpecific raw EEG findings were indicative of changes in the depth of anesthesia. However, there was considerable variability in EEG between horses at identical MAC multiples/conditions and within individual horses over segments of a given epoch. Statistical significance for qEEG variables differed between anesthetics with bispectral index (BIS) CV MAC and 95% spectral edge frequency (SEF95) SV MAC differences in isoflurane only and median frequency (MED) differences in SV MAC with halothane only.Conclusions and clinical importanceUnprocessed EEG features (background and transients) appear to be beneficial for monitoring the depth of a particular anesthetic, but offer little advantage over the use of changes in mean arterial pressure for this purpose

    The perception of affective touch in Parkinson's disease and its relation to small fibre neuropathy.

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    Affective touch sensation is conducted by a sub-class of C-fibres in hairy skin known as C-Tactile (CT) afferents. CT afferents respond maximally to gentle skin stroking at velocities between 1-10 cm/sec. Parkinson's disease (PD) is characterised by markedly reduced cutaneous C-fibres. It is not known if affective touch perception is influenced by C fibre density and if affective touch is impaired in PD compared to healthy controls. We predicted that perceived pleasantness to gentle stroking in PD would correlate with C afferent density and that affective touch perception would be impaired in PD compared to healthy controls. Twenty-four PD patients and 27 control subjects rated the pleasantness of brush stroking at an optimum CT stimulation velocity (3cm/sec) and two sub-optimal velocities (0.3cm/sec & 30cm/sec). PD patients underwent quantification of C-fibre density using skin biopsies and corneal confocal microscopy. All participants rated stroking velocity of 3cm/sec as the most pleasant with significantly lower ratings for 0.3cm/sec and 30cm/sec. There was a significant positive correlation between C-fibre density and pleasantness ratings at 3cm/sec and 30cm/sec but not 0.3cm/sec. Mean pleasantness ratings were consistently higher in PD patients compared to control subjects across all three velocities. This study shows that perceived pleasantness to gentle touch correlate significantly with C-fibre density in PD. The higher perceived pleasantness in PD patients compared to controls suggests central sensitisation to peripheral inputs, which may have been enhanced by dopamine therapy. This article is protected by copyright. All rights reserved

    Modelling with non-stratified chain event graphs

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    © 2019, Springer Nature Switzerland AG. Chain Event Graphs (CEGs) are recent probabilistic graphical modelling tools that have proved successful in modelling scenarios with context-specific independencies. Although the theory underlying CEGs supports appropriate representation of structural zeroes, the literature so far does not provide an adaptation of the vanilla CEG methods for a real-world application presenting structural zeroes also known as the non-stratified CEG class. To illustrate these methods, we present a non-stratified CEG representing a public health intervention designed to reduce the risk and rate of falling in the elderly. We then compare the CEG model to the more conventional Bayesian Network model when applied to this setting

    Mosaic DNA imports with interspersions of recipient sequence after natural transformation of Helicobacter pylori

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    Helicobacter pylori colonizes the gastric mucosa of half of the human population, causing gastritis, ulcers, and cancer. H. pylori is naturally competent for transformation by exogenous DNA, and recombination during mixed infections of one stomach with multiple H. pylori strains generates extensive allelic diversity. We developed an in vitro transformation protocol to study genomic imports after natural transformation of H. pylori. The mean length of imported fragments was dependent on the combination of donor and recipient strain and varied between 1294 bp and 3853 bp. In about 10% of recombinant clones, the imported fragments of donor DNA were interrupted by short interspersed sequences of the recipient (ISR) with a mean length of 82 bp. 18 candidate genes were inactivated in order to identify genes involved in the control of import length and generation of ISR. Inactivation of the antimutator glycosylase MutY increased the length of imports, but did not have a significant effect on ISR frequency. Overexpression of mutY strongly increased the frequency of ISR, indicating that MutY, while not indispensable for ISR formation, is part of at least one ISR-generating pathway. The formation of ISR in H. pylori increases allelic diversity, and contributes to the uniquely low linkage disequilibrium characteristic of this pathogen

    miR-155 in the progression of lung fibrosis in systemic sclerosis

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    Background: MicroRNA (miRNA) control key elements of mRNA stability and likely contribute to the dysregulated lung gene expression observed in systemic sclerosis associated interstitial lung disease (SSc-ILD). We analyzed the miRNA gene expression of tissue and cells from patients with SSc-ILD. A chronic lung fibrotic murine model was used. Methods: RNA was isolated from lung tissue of 12 patients with SSc-ILD and 5 controls. High-resolution computed tomography (HRCT) was performed at baseline and 2-3 years after treatment. Lung fibroblasts and peripheral blood mononuclear cells (PBMC) were isolated from healthy controls and patients with SSc-ILD. miRNA and mRNA were analyzed by microarray, quantitative polymerase chain reaction, and/or Nanostring; pathway analysis was performed by DNA Intelligent Analysis (DIANA)-miRPath v2.0 software. Wild-type and miR-155 deficient (miR-155ko) mice were exposed to bleomycin. Results: Lung miRNA microarray data distinguished patients with SSc-ILD from healthy controls with 185 miRNA differentially expressed (q < 0.25). DIANA-miRPath revealed 57 Kyoto Encyclopedia of Genes and Genomes pathways related to the most dysregulated miRNA. miR-155 and miR-143 were strongly correlated with progression of the HRCT score. Lung fibroblasts only mildly expressed miR-155/miR-21 after several stimuli. miR-155 PBMC expression strongly correlated with lung function tests in SSc-ILD. miR-155ko mice developed milder lung fibrosis, survived longer, and weaker lung induction of several genes after bleomycin exposure compared to wild-type mice. Conclusions: miRNA are dysregulated in the lungs and PBMC of patients with SSc-ILD. Based on mRNA-miRNA interaction analysis and pathway tools, miRNA may play a role in the progression of the disease. Our findings suggest that targeting miR-155 might provide a novel therapeutic strategy for SSc-ILD

    The Minimum Detectable Difference (MDD) Concept for Establishing Trust in Nonsignificant Results: A Critical Review

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    Current regulatory guidelines for pesticide risk assessment recommend that nonsignificant results should be complemented by the minimum detectable difference (MDD), a statistical indicator that is used to decide whether the experiment could have detected biologically relevant effects. We review the statistical theory of the MDD and perform simulations to understand its properties and error rates. Most importantly, we compare the skill of the MDD in distinguishing between true and false negatives (i.e., type II errors) with 2 alternatives: the minimum detectable effect (MDE), an indicator based on a post hoc power analysis common in medical studies; and confidence intervals (CIs). Our results demonstrate that MDD and MDE only differ in that the power of the MDD depends on the sample size. Moreover, although both MDD and MDE have some skill in distinguishing between false negatives and true absence of an effect, they do not perform as well as using CI upper bounds to establish trust in a nonsignificant result. The reason is that, unlike the CI, neither MDD nor MDE consider the estimated effect size in their calculation. We also show that MDD and MDE are no better than CIs in identifying larger effects among the false negatives. We conclude that, although MDDs are useful, CIs are preferable for deciding whether to treat a nonsignificant test result as a true negative, or for determining an upper bound for an unknown true effect.Environ Toxicol Chem2020;00:1-15. (c) 2020 The Authors.Environmental Toxicology and Chemistrypublished by Wiley Periodicals LLC on behalf of SETAC

    When is an optimization not an optimization? Evaluation of clinical implications of information content (signal-to-noise ratio) in optimization of cardiac resynchronization therapy, and how to measure and maximize it

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    Impact of variability in the measured parameter is rarely considered in designing clinical protocols for optimization of atrioventricular (AV) or interventricular (VV) delay of cardiac resynchronization therapy (CRT). In this article, we approach this question quantitatively using mathematical simulation in which the true optimum is known and examine practical implications using some real measurements. We calculated the performance of any optimization process that selects the pacing setting which maximizes an underlying signal, such as flow or pressure, in the presence of overlying random variability (noise). If signal and noise are of equal size, for a 5-choice optimization (60, 100, 140, 180, 220 ms), replicate AV delay optima are rarely identical but rather scattered with a standard deviation of 45 ms. This scatter was overwhelmingly determined (ρ = −0.975, P < 0.001) by Information Content, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}SignalSignal+Noise {\frac{\text{Signal}}{{{\text{Signal}} + {\text{Noise}}}}} \end{document}, an expression of signal-to-noise ratio. Averaging multiple replicates improves information content. In real clinical data, at resting, heart rate information content is often only 0.2–0.3; elevated pacing rates can raise information content above 0.5. Low information content (e.g. <0.5) causes gross overestimation of optimization-induced increment in VTI, high false-positive appearance of change in optimum between visits and very wide confidence intervals of individual patient optimum. AV and VV optimization by selecting the setting showing maximum cardiac function can only be accurate if information content is high. Simple steps to reduce noise such as averaging multiple replicates, or to increase signal such as increasing heart rate, can improve information content, and therefore viability, of any optimization process

    Identifying the science and technology dimensions of emerging public policy issues through horizon scanning

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    Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security.Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security
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