Genetic variation in the serotonin transporter gene (5-HTTLPR, rs25531) influences the analgesic response to the short acting opioid Remifentanil in humans

<p>Abstract</p> <p>Background</p> <p>There is evidence from animal studies that serotonin (5-HT) can influence the antinociceptive effects of opioids at the spinal cord level. Therefore, there could be an influence of genetic polymorphisms in the serotonin system on individual variability in response to opioid treatment of pain. The serotonin transporter (5-HTT) is a key regulator of serotonin metabolism and availability and its gene harbors several known polymorphisms that are known to affect 5-HTT expression (e.g. 5-HTTLPR, rs25531). The aim of this study was to investigate if the triallelic 5-HTTLPR influences pain sensitivity or the analgesic effect of opioids in humans. 43 healthy volunteers (12 men, 31 women, mean age 26 years) underwent heat pain stimulations before and after intravenous injection of Remifentanil; a rapid and potent opioid drug acting on μ-type receptors. Subjects rated their perceived pain on a visual analogue scale (VAS). All participants were genotyped for the 5-HTTLPR and the rs25531 polymorphism. We recruited by advertising, with no history of drug abuse, chronic pain or psychiatric disorders.</p> <p>Results</p> <p>At baseline, there was no difference in pain ratings for the different triallelic 5-HTTLPR genotype groups. However, the opiod drug had a differential analgesic effect depending on the triallelic 5-HTTLPR genotype. Remifentanil had a significantly better analgesic effect in individuals with a genotype coding for low 5-HTT expression (S_A/S_Aand S_A/L_G) as compared to those with high expression(L_A/L_A), p < 0.02. The analgesic effect for the three different genotype groups was linear to degree of 5-HTT expression.</p> <p>Conclusion</p> <p>This is the first report showing an influence of the triallelic 5-HTTLPR on pain sensitivity or the analgesic effect of opioids in humans. Previously the 5-HTTLPR s-allele has been associated with higher risk of developing chronic pain conditions but in this study we show that the genotype coding for low 5-HTT expression is associated with a better analgesic effect of an opioid. The s-allele has been associated with downregulation of 5-HT1 receptors and we suggest that individuals with a desensitization of 5-HT1 receptors have an increased analgesic response to opioids during acute pain stimuli, but may still be at increased risk of developing chronic pain conditions.</p

Identifying the favored mutation in a positive selective sweep.

Most approaches that capture signatures of selective sweeps in population genomics data do not identify the specific mutation favored by selection. We present iSAFE (for "integrated selection of allele favored by evolution"), a method that enables researchers to accurately pinpoint the favored mutation in a large region (∼5 Mbp) by using a statistic derived solely from population genetics signals. iSAFE does not require knowledge of demography, the phenotype under selection, or functional annotations of mutations

The spectra of lifted digraphs

We present a method to derive the complete spectrum of the lift \mathrm{\Gamma\alpha} of a base digraph \mathrm{\Gamma}, with voltage assignment α on a (finite) group $\textit{G}$. The method is based on assigning to \mathrm{\Gamma} a quotient-like matrix whose entries are elements of the group algebra \mathds{C}[$\textit{G}$], which fully represents \mathrm{\Gamma\alpha}. This allows us to derive the eigenvectors and eigenvalues of the lift in terms of those of the base digraph and the irreducible characters of G. Thus, our main theorem generalizes some previous results of Lovász and Babai concerning the spectra of Cayley digraphs

Performance of Monolayer Graphene Nanomechanical Resonators with Electrical Readout

The enormous stiffness and low density of graphene make it an ideal material for nanoelectromechanical (NEMS) applications. We demonstrate fabrication and electrical readout of monolayer graphene resonators, and test their response to changes in mass and temperature. The devices show resonances in the MHz range. The strong dependence of the resonant frequency on applied gate voltage can be fit to a membrane model, which yields the mass density and built-in strain. Upon removal and addition of mass, we observe changes in both the density and the strain, indicating that adsorbates impart tension to the graphene. Upon cooling, the frequency increases; the shift rate can be used to measure the unusual negative thermal expansion coefficient of graphene. The quality factor increases with decreasing temperature, reaching ~10,000 at 5 K. By establishing many of the basic attributes of monolayer graphene resonators, these studies lay the groundwork for applications, including high-sensitivity mass detectors

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Boundary Conditions and Unitarity: the Maxwell-Chern-Simons System in AdS_3/CFT_2

We consider the holography of the Abelian Maxwell-Chern-Simons (MCS) system in Lorentzian three-dimensional asymptotically-AdS spacetimes, and discuss a broad class of boundary conditions consistent with conservation of the symplectic structure. As is well-known, the MCS theory contains a massive sector dual to a vector operator in the boundary theory, and a topological sector consisting of flat connections dual to U(1) chiral currents; the boundary conditions we examine include double-trace deformations in these two sectors, as well as a class of boundary conditions that mix the vector operators with the chiral currents. We carefully study the symplectic product of bulk modes and show that almost all such boundary conditions induce instabilities and/or ghost excitations, consistent with violations of unitarity bounds in the dual theory.Comment: 50+1 pages, 6 figures, PDFLaTeX; v2: added references, corrected typo

Using interpretative phenomenological analysis to inform physiotherapy practice: An introduction with reference to the lived experience of cerebellar ataxia

The attached file is a pre-published version of the full and final paper which can be found at the link below.This article has been made available through the Brunel Open Access Publishing Fund.Qualitative research methods that focus on the lived experience of people with health conditions are relatively underutilised in physiotherapy research. This article aims to introduce interpretative phenomenological analysis (IPA), a research methodology oriented toward exploring and understanding the experience of a particular phenomenon (e.g., living with spinal cord injury or chronic pain, or being the carer of someone with a particular health condition). Researchers using IPA try to find out how people make sense of their experiences and the meanings they attach to them. The findings from IPA research are highly nuanced and offer a fine grained understanding that can be used to contextualise existing quantitative research, to inform understanding of novel or underresearched topics or, in their own right, to provoke a reappraisal of what is considered known about a specified phenomenon. We advocate IPA as a useful and accessible approach to qualitative research that can be used in the clinical setting to inform physiotherapy practice and the development of services from the perspective of individuals with particular health conditions.This article is available through the Brunel Open Access Publishing Fund

Impacts of carbohydrate-restricted diets on micronutrient intakes and status: a systematic review

A systematic review of published evidence on micronutrient intake/status with carbohydrate‐restricted diets (CRD) was conducted in Web of Science, Medline, Embase, Scopus, CENTRAL, and ClinicalTrials.gov up to October 2018. We identified 10 studies: seven randomized controlled trials (RCTs) (“Atkins”‐style, n = 5; “Paleolithic” diets, n = 2), two Atkins‐style noncontrolled trials and one cross‐sectional study. Prescribed carbohydrate varied 4% to 34% of energy intake. Only one noncontrolled trial prescribed multivitamin supplements. Dietary intakes/status were reported over 2 to 104 weeks, with weight losses from 2 to 9 kg. No diagnoses of deficiency were reported. Intakes of thiamine, folate, magnesium, calcium, iron, and iodine all decreased significantly (−10% to −70% from baseline) with any CRD types. Atkins diet trials (n = 6; 4%‐34%E carbohydrate) showed inconsistent changes in vitamin A, E, and β‐carotene intakes, while a single “Paleolithic” diet trial (28%E carbohydrate) reported increases in these micronutrients. One other “Paleolithic” diet (30%E carbohydrate) reported a rise in moderate iodine deficiency from 15% to 73% after 6 months. In conclusion, few studies have assessed the impacts of CRD on micronutrients. Studies with different designs point towards reductions in several vitamins and minerals, with potential risk of micronutrient inadequacies. Trial reporting standards are expected to include analysis of micronutrient intake/status. Micronutrients in foods and/or supplements should be considered when designing, prescribing or following CRDs