Biology subjects

Palmer, A.

Publications and source records attributed to Palmer, A..

4 recordsLinked to original sources

bioRxiv2018

Latent Structure of Risk Perception

Risk-taking behavior affects many aspects of life, including maladaptive behaviors such as illicit substance use, unsafe driving, and risky sexual behavior. Risk-taking has been measured using both self-report measures and behavioral tasks designed for the purpose, but there is little consensus in the associations among measures and our understanding of the latent constructs underlying different forms of risk is limited. In the present study we examined the construct of risk using data from over 1000 young adults who completed measures of risk-taking, including self-reports of perception of risk, propensity to engage in risky behaviors and performance on behavioral tasks designed to measure risk. To examine the latent structure of risk preferences, we conducted a principal component analysis (PCA). The PCA revealed a latent structure of three distinct components of risk-taking behavior: \"Lifestyle Risk Sensitivity\", \"Financial Risk Sensitivity\", and \"Behavioral Risk Sensitivity\", which consisted only of the Balloon Analogue Risk Task (BART; Lejuez et al., 2002). As expected, risk-taking and perception of risk differed in men and women. Yet, the PCA components were similar in men and women. Future work utilizing additional measures of risk-taking behavior in more heterogeneous samples will help to identify the true biobehavioral constructs underlying these behaviors.

neuroscience↗

bioRxiv2018

How molecular mechanisms of resistance affect resistance evolution

Combatting antibiotic resistance will require both new antibiotics and strategies to preserve the effectiveness of existing drugs. Both approaches would benefit from predicting optimal dosing of antibiotics based on drug-target binding parameters that can be measured early in drug development and that can change when bacteria become resistant. This would avoid the currently frequently employed trial-and-error approaches and might reduce the number of antibiotic candidates that fail late in drug development.\n\nHere, we describe a computational model (COMBAT-COmputational Model of Bacterial Antibiotic Target-binding) that leverages accessible biochemical parameters to quantitatively predict antibiotic dose-response relationships. We validate our model with MICs of a range of quinolone antibiotics in clinical isolates demonstrating that antibiotic efficacy can be predicted from drug-target binding (R2 > 0.9). To further challenge our approach, we do not only predict antibiotic efficacy from biochemical parameters, but also do the reverse: estimate the magnitude of changes in drug-target binding based on antibiotic dose-response curves. We experimentally demonstrate that changes in drug-target binding can be predicted from antibiotic dose-response curves with 92-94 % accuracy by exposing bacteria overexpressing target molecules to ciprofloxacin. To test the generality of COMBAT, we apply it to a different antibiotic class, the beta-lactam ampicillin, and can again predict binding parameters from dose-response curves with 90 % accuracy. We then apply COMBAT to predict antibiotic concentrations that can select for resistance due to novel resistance mutations.\n\nOur goal here is dual: First, we address a fundamental biological question and demonstrate that drug-target binding determines bacterial response to antibiotics, although antibiotic action involves many additional effects downstream of drug-target binding. Second, we create a tool that can help accelerate drug development by predicting optimal dosing and preserve the efficacy of existing antibiotics by predicting optimal treatment for possible resistant mutants.

biochemistry↗

bioRxiv2017

Inhibition of Glyoxalase 1 reduces alcohol self-administration in dependent and nondependent rats

Previous studies showed that the glyoxalase 1 (Glo1) gene modulates anxiety-like behavior, seizure susceptibility, depression-like behavior, and alcohol drinking in the drinking-in-the-dark paradigm in nondependent mice. Administration of the small-molecule GLO1 inhibitor S-bromobenzylglutathione cyclopentyl diester (pBBG) decreased alcohol drinking in nondependent mice, suggesting a possible therapeutic strategy. However, the preclinical therapeutic efficacy of pBBG in animal models of alcohol dependence remains to be demonstrated. We tested the effect of pBBG (7.5 and 25 mg/kg) on operant alcohol self-administration in alcohol-dependent and nondependent rats. Wistar rats were trained to self-administer 10% alcohol (v/v) and made dependent by chronic intermittent passive exposure to alcohol vapor for 5 weeks. Pretreatment with pBBG dose-dependently reduced alcohol self-administration in both nondependent and dependent animals, without affecting water self-administration. pBBG treatment was more effective in dependent rats than in nondependent rats. These data extend previous findings that implicated Glo1 in alcohol drinking in nondependent mice by showing even more profound effects in alcohol-dependent rats. These results suggest that the pharmacological inhibition of GLO1 is a relevant therapeutic target for the treatment of alcohol use disorders.\n\nHighlightsO_LIAlcohol use disorder (AUD) places an enormous burden on society, and there is an urgent need for new druggable targets.\nC_LIO_LIGlo1 inhibition by pBBG dose-dependently reduces alcohol self-administration in both nondependent and dependent animals.\nC_LIO_LIpBBG treatment is more effective in reducing alcohol intake in dependent rats than in nondependent rats.\nC_LI

neuroscience↗

bioRxiv2017

Curatr: a web application for creating, curating, and sharing a mass spectral library

MotivationIdentification from metabolomics mass spectrometry experiments requires comparison of fragmentation spectra from experimental samples to spectra from analytical standards. As the quality of identification depends directly on the quality of the reference spectra, manual curation is routine during the selection of reference spectra to include in a spectral library. Whilst building our own in-house spectral library we realised that there is currently no vendor neutral open access tool for for facilitating manual curation of spectra from raw LC-MS data into a custom spectral library.\n\nResultsWe developed a web application curatr for the rapid generation of high quality mass spectral fragmentation libraries for liquid-chromatography mass spectrometry analysis. Curatr handles datasets from single or multiplexed standards, automatically extracting chromatographic profiles and potential fragmentation spectra for multiple adducts. These are presented through an intuitive interface for manual curation before being documented in a custom spectral library. Searchable molecular information and the providence of each standard is stored along with metadata on the experimental protocol. Curatr support the export of spectral libraries in several standard formats for easy use with third party software or submission to community databases, maximising the return on investment for these costly measurements. We demonstrate the use of curatr to generate the EMBL Metabolomics Core Facility spectral library which is publicly available at http://curatr.mcf.embl.de.\n\nAvailabilityThe source code is freely available at http://github.com/alexandrovteam/curatr/ along with example data.\n\nSupplementary informationA step-by step user manual is available in the supplementary information

bioinformatics↗