A Shock to the (Nervous) System: Bioelectricity Within Peripheral Nerve Tissue Engineering

The peripheral nervous system has the remarkable ability to regenerate in response to injury. However, this is only successful over shorter nerve gaps and often provides poor outcomes for patients. Currently, the gold standard of treatment is the surgical intervention of an autograft, whereby patient tissue is harvested and transplanted to bridge the nerve gap. Despite being the gold standard, over half of patients have dissatisfactory functional recovery after an autograft. Peripheral nerve tissue engineering aims to create biomaterials that can therapeutically surpass the autograft. Current tissue engineered constructs are designed to deliver a combination of therapeutic benefits to the regenerating nerve, such as supportive cells, alignment, extracellular matrix, soluble factors, immunosuppressants and other therapies. An emerging therapeutic opportunity in nerve tissue engineering is the use of electrical stimulation (ES) to modify and enhance cell function. ES has been shown to positively affect four key cell types, neurons, endothelial cells, macrophages, and Schwann cells, involved in peripheral nerve repair. Changes elicited include faster neurite extension, cellular alignment, and changes in cell phenotype associated with improved regeneration and functional recovery. This review considers the relevant modes of administration and cellular responses that could underpin incorporation of ES into nerve tissue engineering strategies

Methods for detecting and quantifying individual specialisation in movement and foraging strategies of marine predators

There is increasing realisation that individuals in many animal populations differ substantially in resource, space or habitat use. Differences that cannot be attributed to any a priori way of classifying individuals (i.e. age, sex and other group effects) are often termed ‘individual specialisation’. The aim of this paper is to assess the most common approaches for detecting and quantifying individual specialisation and consistencies in foraging behaviour, movement patterns and diet of marine predators using 3 types of data: conventional diet data, stable isotope ratios and tracking data. Methods using conventional diet data rely on a comparison between the proportions of each dietary source in the total diet and in the diet of individuals, or analyses of the statistical distribution of a prey metric (e.g. size); the latter often involves comparing ratios of individual and population variance. Approaches frequently used to analyse stable isotope or tracking data reduced to 1 dimension (trip characteristics, e.g. maximum trip distance or latitude/longitude at certain landmarks) include correlation tests and repeatability analysis. Finally, various spatial analyses are applied to other types of tracking data (e.g. distances between centroids of distributions or migratory routes, or overlap between distributions), and methods exist to compare habitat use. We discuss the advantages and disadvantages of these approaches, issues arising from other effects unrelated to individual specialisation per se (in particular those related to temporal scale) and potential solutions

EIT and diffusion of atomic coherence

We study experimentally the effect of diffusion of Rb atoms on Electromagnetically Induced Transparency (EIT) in a buffer gas vapor cell. In particular, we find that diffusion of atomic coherence in-and-out of the laser beam plays a crucial role in determining the EIT resonance lineshape and the stored light lifetime.Comment: 5 pages, 8 figure

Regional Mapping and Spatial Distribution Analysis of Canopy Palms in an Amazon Forest Using Deep Learning and VHR Images

Mapping plant species at the regional scale to provide information for ecologists and forest managers is a challenge for the remote sensing community. Here, we use a deep learning algorithm called U-net and very high-resolution multispectral images (0.5 m) from GeoEye satellite to identify, segment and map canopy palms over ∼3000 km2 of Amazonian forest. The map was used to analyse the spatial distribution of canopy palm trees and its relation to human disturbance and edaphic conditions. The overall accuracy of the map was 95.5% and the F1-score was 0.7. Canopy palm trees covered 6.4% of the forest canopy and were distributed in more than two million patches that can represent one or more individuals. The density of canopy palms is affected by human disturbance. The post-disturbance density in secondary forests seems to be related to the type of disturbance, being higher in abandoned pasture areas and lower in forests that have been cut once and abandoned. Additionally, analysis of palm trees’ distribution shows that their abundance is controlled naturally by local soil water content, avoiding both flooded and waterlogged areas near rivers and dry areas on the top of the hills. They show two preferential habitats, in the low elevation above the large rivers, and in the slope directly below the hill tops. Overall, their distribution over the region indicates a relatively pristine landscape, albeit within a forest that is critically endangered because of its location between two deforestation fronts and because of illegal cutting. New tree species distribution data, such as the map of all adult canopy palms produced in this work, are urgently needed to support Amazon species inventory and to understand their distribution and diversity

Experimental Biological Protocols with Formal Semantics

Both experimental and computational biology is becoming increasingly automated. Laboratory experiments are now performed automatically on high-throughput machinery, while computational models are synthesized or inferred automatically from data. However, integration between automated tasks in the process of biological discovery is still lacking, largely due to incompatible or missing formal representations. While theories are expressed formally as computational models, existing languages for encoding and automating experimental protocols often lack formal semantics. This makes it challenging to extract novel understanding by identifying when theory and experimental evidence disagree due to errors in the models or the protocols used to validate them. To address this, we formalize the syntax of a core protocol language, which provides a unified description for the models of biochemical systems being experimented on, together with the discrete events representing the liquid-handling steps of biological protocols. We present both a deterministic and a stochastic semantics to this language, both defined in terms of hybrid processes. In particular, the stochastic semantics captures uncertainties in equipment tolerances, making it a suitable tool for both experimental and computational biologists. We illustrate how the proposed protocol language can be used for automated verification and synthesis of laboratory experiments on case studies from the fields of chemistry and molecular programming

Crystal structure of a quinoenzyme: copper amine oxidase of Escherichia coli at 2 å resolution

AbstractBackground: Copper amine oxidases are a ubiquitous and novel group of quinoenzymes that catalyze the oxidative deamination of primary amines to the corresponding aldehydes, with concomitant reduction of molecular oxygen to hydrogen peroxide. The enzymes are dimers of identical 70–90 kDa subunits, each of which contains a single copper ion and a covalently bound cofactor formed by the post-translational modification of a tyrosine side chain to 2,4,5-trihydroxyphenylalanine quinone (TPQ).Results The crystal structure of amine oxidase from Escherichia coli has been determined in both an active and an inactive form. The only structural differences are in the active site, where differences in copper coordination geometry and in the position and interactions of the redox cofactor, TPQ, are observed. Each subunit of the mushroom-shaped dimer comprises four domains: a 440 amino acid C-terminal β sandwich domain, which contains the active site and provides the dimer interface, and three smaller peripheral α/β domains (D1–D3), each of about 100 amino acids. D2 and D3 show remarkable structural and sequence similarity to each other and are conserved throughout the quinoenzyme family. In contrast, D1 is absent from some amine oxidases. The active sites are well buried from solvent and lie some 35 å apart, connected by a pair of β hairpin arms.Conclusion The crystal structure of E. coli copper amine oxidase reveals a number of unexpected features and provides a basis for investigating the intriguing similarities and differences in catalytic mechanism of members of this enzyme family. In addition to the three conserved histidines that bind the copper, our studies identify a number of other conserved residues close to the active site, including a candidate for the catalytic base and a fourth conserved histidine which is involved in an interesting intersubunit interaction

Entropy Projection Curved Gabor with Random Forest and SVM for Face Recognition

In this work, we propose a workflow for face recognition under occlusion using the entropy projection from the curved Gabor filter, and create a representative and compact features vector that describes a face. Despite the reduced vector obtained by the entropy projection, it still presents opportunity for further dimensionality reduction. Therefore, we use a Random Forest classifier as an attribute selector, providing a 97% reduction of the original vector while keeping suitable accuracy. A set of experiments using three public image databases: AR Face, Extended Yale B with occlusion and FERET illustrates the proposed methodology, evaluated using the SVM classifier. The results obtained in the experiments show promising results when compared to the available approaches in the literature, obtaining 98.05% accuracy for the complete AR Face, 97.26% for FERET and 81.66% with Yale with 50% occlusion

Surface-Atmosphere Coupling Scale, the Fate of Water, and Ecophysiological Function in a Brazilian Forest

This is the final verison. Available from American Geophysical Union (AGU) via the DOI in this record.The K83 observational data are available from AmeriFlux (ameriflux.lbl.gov), NCEP Reanalysis data provided by NOAA/ESRL/PSD, Boulder, Colorado, USA, from the http://www.cdc.noaa.gov/ website. Model code and output is stored at GitLab (gitlab.com). This project is password protected, and the password can be obtained from the corresponding author at [email protected] upon request.Tropical South America plays a central role in global climate. Bowen ratio teleconnects to circulation and precipitation processes far afield, and the global CO2 growth rate is strongly influenced by carbon cycle processes in South America. However, quantification of basin-wide seasonality of flux partitioning between latent and sensible heat, the response to anomalies around climatic norms, and understanding of the processes and mechanisms that control the carbon cycle remains elusive. Here, we investigate simulated surface-atmosphere interaction at a single site in Brazil, using models with different representations of precipitation and cloud processes, as well as differences in scale of coupling between the surface and atmosphere. We find that the model with parameterized clouds/precipitation has a tendency toward unrealistic perpetual light precipitation, while models with explicit treatment of clouds produce more intense and less frequent rain. Models that couple the surface to the atmosphere on the scale of kilometers, as opposed to tens or hundreds of kilometers, produce even more realistic distributions of rainfall. Rainfall intensity has direct consequences for the “fate of water,” or the pathway that a hydrometeor follows once it interacts with the surface. We find that the model with explicit treatment of cloud processes, coupled to the surface at small scales, is the most realistic when compared to observations. These results have implications for simulations of global climate, as the use of models with explicit (as opposed to parameterized) cloud representations becomes more widespread.National Aeronautics and Space Administration (NASA)National Science Foundation (NSF)National Science Foundation (NSF)U.S. Department of Energy (DOE

Relative commutants of strongly self-absorbing C*-algebras

The relative commutant $A'\cap A^{\mathcal{U}}$ of a strongly self-absorbing algebra $A$ is indistinguishable from its ultrapower $A^{\mathcal{U}}$. This applies both to the case when $A$ is the hyperfinite II$_1$ factor and to the case when it is a strongly self-absorbing C*-algebra. In the latter case we prove analogous results for $\ell_\infty(A)/c_0(A)$ and reduced powers corresponding to other filters on $\bf N$. Examples of algebras with approximately inner flip and approximately inner half-flip are provided, showing the optimality of our results. We also prove that strongly self-absorbing algebras are smoothly classifiable, unlike the algebras with approximately inner half-flip.Comment: Some minor correction