Oligosaccharide and Glycoprotein Microarrays as Tools in HIV Glycobiology Glycan-Dependent gp120/Protein Interactions

AbstractDefining HIV envelope glycoprotein interactions with host factors or binding partners advances our understanding of the infectious process and provides a basis for the design of vaccines and agents that interfere with HIV entry. Here we employ carbohydrate and glycoprotein microarrays to analyze glycan-dependent gp120-protein interactions. In concert with new linking chemistries and synthetic methods, the carbohydrate arrays combine the advantages of microarray technology with the flexibility and precision afforded by organic synthesis. With these microarrays, we individually and competitively determined the binding profiles of five gp120 binding proteins, established the carbohydrate structural requirements for these interactions, and identified a potential strategy for HIV vaccine development

Acetophenone Monomers from Acronychia trifoliolata

Seven new [acronyculatins I-O (1-7)] and four known acetophenone monomers were isolated from a CH 3 OH/CH 2 Cl 2 (1:1) extract (N089419) of Acronychia trifoliolata provided by the U.S. National Cancer Institute (NCI, Frederick, MD, USA). Their structures were characterized by using various NMR and HRMS techniques. Among the known compounds, the structure of acronyculatin B (8) was revised. Some of the isolated compounds were evaluated for antiproliferative activity against human cancer cell lines. While most of the tested compounds were not cytotoxic, acronyculatins I (1) and J (2) showed moderate antiproliferative activity

Investigation of Griffithsin's Interactions with Human Cells Confirms Its Outstanding Safety and Efficacy Profile as a Microbicide Candidate

Many natural product-derived lectins such as the red algal lectin griffithsin (GRFT) have potent in vitro activity against viruses that display dense clusters of oligomannose N-linked glycans (NLG) on their surface envelope glycoproteins. However, since oligomannose NLG are also found on some host proteins it is possible that treatment with antiviral lectins may trigger undesirable side effects. For other antiviral lectins such as concanavalin A, banana lectin and cyanovirin-N (CV-N), interactions between the lectin and as yet undescribed cellular moieties have been reported to induce undesirable side effects including secretion of inflammatory cytokines and activation of host T-cells. We show that GRFT, unlike CV-N, binds the surface of human epithelial and peripheral blood mononuclear cells (PBMC) through an exclusively oligosaccharide-dependent interaction. In contrast to several other antiviral lectins however, GRFT treatment induces only minimal changes in secretion of inflammatory cytokines and chemokines by epithelial cells or human PBMC, has no measureable effect on cell viability and does not significantly upregulate markers of T-cell activation. In addition, GRFT appears to retain antiviral activity once bound to the surface of PBMC. Finally, RNA microarray studies show that, while CV-N and ConA regulate expression of a multitude of cellular genes, GRFT treatment effects only minimal alterations in the gene expression profile of a human ectocervical cell line. These studies indicate that GRFT has an outstanding safety profile with little evidence of induced toxicity, T-cell activation or deleterious immunological consequence, unique attributes for a natural product-derived lectin

Grid Cells, Place Cells, and Geodesic Generalization for Spatial Reinforcement Learning

Reinforcement learning (RL) provides an influential characterization of the brain's mechanisms for learning to make advantageous choices. An important problem, though, is how complex tasks can be represented in a way that enables efficient learning. We consider this problem through the lens of spatial navigation, examining how two of the brain's location representations—hippocampal place cells and entorhinal grid cells—are adapted to serve as basis functions for approximating value over space for RL. Although much previous work has focused on these systems' roles in combining upstream sensory cues to track location, revisiting these representations with a focus on how they support this downstream decision function offers complementary insights into their characteristics. Rather than localization, the key problem in learning is generalization between past and present situations, which may not match perfectly. Accordingly, although neural populations collectively offer a precise representation of position, our simulations of navigational tasks verify the suggestion that RL gains efficiency from the more diffuse tuning of individual neurons, which allows learning about rewards to generalize over longer distances given fewer training experiences. However, work on generalization in RL suggests the underlying representation should respect the environment's layout. In particular, although it is often assumed that neurons track location in Euclidean coordinates (that a place cell's activity declines “as the crow flies” away from its peak), the relevant metric for value is geodesic: the distance along a path, around any obstacles. We formalize this intuition and present simulations showing how Euclidean, but not geodesic, representations can interfere with RL by generalizing inappropriately across barriers. Our proposal that place and grid responses should be modulated by geodesic distances suggests novel predictions about how obstacles should affect spatial firing fields, which provides a new viewpoint on data concerning both spatial codes

Evaluation of the Oscillatory Interference Model of Grid Cell Firing through Analysis and Measured Period Variance of Some Biological Oscillators

Models of the hexagonally arrayed spatial activity pattern of grid cell firing in the literature generally fall into two main categories: continuous attractor models or oscillatory interference models. Burak and Fiete (2009, PLoS Comput Biol) recently examined noise in two continuous attractor models, but did not consider oscillatory interference models in detail. Here we analyze an oscillatory interference model to examine the effects of noise on its stability and spatial firing properties. We show analytically that the square of the drift in encoded position due to noise is proportional to time and inversely proportional to the number of oscillators. We also show there is a relatively fixed breakdown point, independent of many parameters of the model, past which noise overwhelms the spatial signal. Based on this result, we show that a pair of oscillators are expected to maintain a stable grid for approximately t = 5µ3/(4πσ)2 seconds where µ is the mean period of an oscillator in seconds and σ2 its variance in seconds2. We apply this criterion to recordings of individual persistent spiking neurons in postsubiculum (dorsal presubiculum) and layers III and V of entorhinal cortex, to subthreshold membrane potential oscillation recordings in layer II stellate cells of medial entorhinal cortex and to values from the literature regarding medial septum theta bursting cells. All oscillators examined have expected stability times far below those seen in experimental recordings of grid cells, suggesting the examined biological oscillators are unfit as a substrate for current implementations of oscillatory interference models. However, oscillatory interference models can tolerate small amounts of noise, suggesting the utility of circuit level effects which might reduce oscillator variability. Further implications for grid cell models are discussed

Accurate path integration in continuous attractor network models of grid cells

Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rat's velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of ~10–100 meters and ~1–10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other

From the outside in: narratives of creative arts practitioners working in the criminal justice system

This is an accepted manuscript of an article published by Wiley-Blackwell in The Howard Journal of Crime and Justice on 31/12/2019, available online: https://doi.org/10.1111/hojo.12318 The accepted version of the publication may differ from the final published version.The penal voluntary sector is highly variegated in its roles, practices and functions, though research to date has largely excluded the experiences of front-line practitioners. We argue that engaging with the narratives of practitioners can provide fuller appreciation of the potential of the sector’s work. Though life story and narrative have been recognised as important in offender desistance (Maruna, 2001), the narrative identities of creative arts practitioners, who are important ‘change agents’ (Albertson, 2015), are typically absent. This is despite evidence to suggest that a practitioner’s life history can be a significant and positive influence in the rehabilitation of offenders (Harris, 2017). Using narratological analysis (Bal, 2009), this study examined the narratives of 19 creative practitioners in prisons in England and Wales. Of particular interest were the formative experiences of arts practitioners in their journey to prison work. The findings suggest that arts practitioners identify with an ‘outsider’ status and may be motivated by an ethic of mutual aid. In the current climate of third sector involvement in the delivery of criminal justice interventions, such a capacity may be both a strength and weakness for arts organisations working in this field