Biology subjects

Griffin, S.

Publications and source records attributed to Griffin, S..

3 recordsLinked to original sources

bioRxiv2018

Targeting hepatitis C virus p7 channel activity reveals prospect for bimodal antiviral prophylaxis

Since the 1960s, a single class of agent has been licensed targeting virus-encoded ion channels, or \"viroporins\", contrasting the success of channel blocking drugs in other areas of medicine. Although resistance arose to these prototypic adamantane inhibitors of the influenza A virus (IAV) M2 proton channel, a growing number of clinically and economically important viruses are now recognised to encode essential viroporins providing potential targets for modern drug discovery.\n\nWe describe the first rationally designed viroporin inhibitor with a comprehensive structure-activity relationship (SAR). This step-change in understanding not only revealed a second biological function for the p7 viroporin from hepatitis C virus (HCV) during virus entry, but also enabled the synthesis of a labelled tool compound that retained biological activity. Hence, p7 inhibitors (p7i) represent a unique class of HCV antiviral targeting both the spread and establishment of infection, as well as a precedent for future viroporin-targeted drug discovery.

microbiology↗

bioRxiv2018

Orbitofrontal cortex, dorsolateral prefrontal cortex, and hippocampus represent the magnitude of event saliency

Two primary functions attributed to the hippocampus and prefrontal cortex network are retaining the temporal and spatial associations of events and detecting deviant events. It is, however, unclear how these two functions converge onto one mechanism. Here, we tested whether increased activity with perceiving salient events is a deviant detection signal or contains information about the event associations by reflecting the magnitude of deviance (i.e., event saliency). We also tested how the deviant detection signal is affected by the degree of anticipation. We studied regional neural activity when people watched a movie that had varying saliency of a novel or an anticipated flow of salient events. Using intracranial electroencephalography from ten patients, we observed that high-frequency activity (50-150 Hz) in the hippocampus, dorsolateral prefrontal cortex (dorsolateral PFC), and medial orbitofrontal cortex (OFC) tracked event saliency. We also observed that medial OFC activity was stronger when the salient events were anticipated than when they were novel. These results suggest that dorsolateral PFC and medial OFC, as well as the hippocampus, signify the saliency magnitude of events, reflecting the hierarchical structure of event associations.

neuroscience↗

bioRxiv2017

Integrated analysis of anatomical and electrophysiological human intracranial data

The exquisite spatiotemporal precision of human intracranial EEG recordings (iEEG) permits characterizing neural processing with a level of detail that is inaccessible to scalp-EEG, MEG, or fMRI. However, the same qualities that make iEEG an exceptionally powerful tool also present unique challenges. Until now, the fusion of anatomical data (MRI and CT images) with the electrophysiological data and its subsequent analysis has relied on technologically and conceptually challenging combinations of software. Here, we describe a comprehensive protocol that addresses the complexities associated with human iEEG, providing complete transparency and flexibility in the evolution of raw data into illustrative representations. The protocol is directly integrated with an open source toolbox for electrophysiological data analysis (FieldTrip). This allows iEEG researchers to build on a continuously growing body of scriptable and reproducible analysis methods that, over the past decade, have been developed and employed by a large research community. We demonstrate the protocol for an example complex iEEG data set to provide an intuitive and rapid approach to dealing with both neuroanatomical information and large electrophysiological data sets. We explain how the protocol can be largely automated, taking under an hour to complete, and readily adjusted to iEEG data sets with other characteristics.

neuroscience↗