Detection of brain functional-connectivity difference in post-stroke patients using group-level covariance modeling

Functional brain connectivity, as revealed through distant correlations in the signals measured by functional Magnetic Resonance Imaging (fMRI), is a promising source of biomarkers of brain pathologies. However, establishing and using diagnostic markers requires probabilistic inter-subject comparisons. Principled comparison of functional-connectivity structures is still a challenging issue. We give a new matrix-variate probabilistic model suitable for inter-subject comparison of functional connectivity matrices on the manifold of Symmetric Positive Definite (SPD) matrices. We show that this model leads to a new algorithm for principled comparison of connectivity coefficients between pairs of regions. We apply this model to comparing separately post-stroke patients to a group of healthy controls. We find neurologically-relevant connection differences and show that our model is more sensitive that the standard procedure. To the best of our knowledge, these results are the first report of functional connectivity differences between a single-patient and a group and thus establish an important step toward using functional connectivity as a diagnostic tool

Mortality Rates above Emergency Threshold in Population Affected by Conflict in North Kivu, Democratic Republic of Congo, July 2012-April 2013

The area of Walikale in North Kivu, Democratic Republic of Congo, is intensely affected by conflict and population displacement. Médecins-Sans-Frontières (MSF) returned to provide primary healthcare in July 2012. To better understand the impact of the ongoing conflict and displacement on the population, a retrospective mortality survey was conducted in April 2013. A two-stage randomized cluster survey using 31 clusters of 21 households was conducted. Heads of households provided information on their household make-up, ownership of non-food items (NFIs), access to healthcare and information on deaths and occurrence of self-reported disease in the household during the recall period. The recall period was of 325 days (July 2012-April 2013). In total, 173 deaths were reported during the recall period. The crude mortality rate (CMR) was of 1.4/10,000 persons/day (CI95%: 1.2-1.7) and the under-five- mortality rate (U5MR) of 1.9/10,000 persons per day (CI95%: 1.3-2.5). The most frequently reported cause of death was fever/malaria 34.1% (CI95%: 25.4-42.9). Thirteen deaths were due to intentional violence. Over 70% of all households had been displaced at some time during the recall period. Out of households with someone sick in the last two weeks, 63.8% sought health care; the main reason not to seek health care was the lack of money (n = 134, 63.8%, CI95%: 52.2-75.4). Non Food Items (NFI) ownership was low: 69.0% (CI95%: 53.1-79.7) at least one 10 liter jerry can, 30.1% (CI95%: 24.3-36.5) of households with visible soap available and 1.6 bednets per household. The results from this survey in Walikale clearly illustrate the impact that ongoing conflict and displacement are having on the population in this part of DRC. The gravity of their health status was highlighted by a CMR that was well above the emergency threshold of 1 person/10,000/day and an U5MR that approaches the 2 children/10,000/day threshold for the recall period

Antibiotic Resistance (ABR) in Neonates with Suspected Sepsis admitted to a Medecins Sans Frontieres (MSF) supported Medium Care Unit in Quetta, Pakistan

BACKGROUND: Neonatal Sepsis is a major cause of infant death, especially if associated with ABR. Choice of empirical antibiotics is particularly challenging without access to culture/DST, as in most resource limited settings. MSF care included blood cultures (BCs) since 2015. Here we describe the characteristics of babies, etiologies, ABR, treatment and outcomes

High resolution whole brain diffusion imaging at 7 T for the Human Connectome Project

Mapping structural connectivity in healthy adults for the Human Connectome Project (HCP) benefits from high quality, high resolution, multiband (MB)-accelerated whole brain diffusion MRI (dMRI). Acquiring such data at ultrahigh fields (7 T and above) can improve intrinsic signal-to-noise ratio (SNR), but suffers from shorter T2 and T2⁎ relaxation times, increased B1+ inhomogeneity (resulting in signal loss in cerebellar and temporal lobe regions), and increased power deposition (i.e. specific absorption rate (SAR)), thereby limiting our ability to reduce the repetition time (TR). Here, we present recent developments and optimizations in 7 T image acquisitions for the HCP that allow us to efficiently obtain high quality, high resolution whole brain in-vivo dMRI data at 7 T. These data show spatial details typically seen only in ex-vivo studies and complement already very high quality 3 T HCP data in the same subjects. The advances are the result of intensive pilot studies aimed at mitigating the limitations of dMRI at 7 T. The data quality and methods described here are representative of the datasets that will be made freely available to the community in 2015

Measures for pathway analysis in brain white matter using diffusion tensor images

In this paper we discuss new measures for connectivity analysis of brain white matter, using MR diffusion tensor imaging. Our approach is based on Riemannian geometry, the viability of which has been demonstrated by various researchers in foregoing work. In the Riemannian framework bundles of axons are represented by geodesies on the manifold. Here we do not discuss methods to compute these geodesies, nor do we rely on the availability of geodesies. Instead we propose local measures which are directly computable from the local DTI data, and which enable us to preselect viable or exclude uninteresting seed points for the potentially time consuming extraction of geodesies. If geodesies are available, our measures can be readily applied to these as well. We consider two types of geodesic measures. One pertains to the connectivity saliency of a geodesic, the second to its stability with respect to local spatial perturbations. For the first type of measure we consider both differential as well as integral measures for characterizing a geodesic's saliency either locally or globally. (In the latter case one needs to be in possession of the geodesic curve, in the former case a single tangent vector suffices.) The second type of measure is intrinsically local, and turns out to be related to a well known tensor in Riemannian geometry.</p

Artifact-Based Rendering: Harnessing Natural and Traditional Visual Media for More Expressive and Engaging 3D Visualizations

We introduce Artifact-Based Rendering (ABR), a framework of tools, algorithms, and processes that makes it possible to produce real, data-driven 3D scientific visualizations with a visual language derived entirely from colors, lines, textures, and forms created using traditional physical media or found in nature. A theory and process for ABR is presented to address three current needs: (i) designing better visualizations by making it possible for non-programmers to rapidly design and critique many alternative data-to-visual mappings; (ii) expanding the visual vocabulary used in scientific visualizations to depict increasingly complex multivariate data; (iii) bringing a more engaging, natural, and human-relatable handcrafted aesthetic to data visualization. New tools and algorithms to support ABR include front-end applets for constructing artifact-based colormaps, optimizing 3D scanned meshes for use in data visualization, and synthesizing textures from artifacts. These are complemented by an interactive rendering engine with custom algorithms and interfaces that demonstrate multiple new visual styles for depicting point, line, surface, and volume data. A within-the-research-team design study provides early evidence of the shift in visualization design processes that ABR is believed to enable when compared to traditional scientific visualization systems. Qualitative user feedback on applications to climate science and brain imaging support the utility of ABR for scientific discovery and public communication.Comment: Published in IEEE VIS 2019, 9 pages of content with 2 pages of references, 12 figure

Finsler geometry on higher order tensor fields and applications to high angular resolution diffusion imaging.

We study 3D-multidirectional images, using Finsler geometry. The application considered here is in medical image analysis, specifically in High Angular Resolution Diffusion Imaging (HARDI) (Tuch et al. in Magn. Reson. Med. 48(6):1358–1372, 2004) of the brain. The goal is to reveal the architecture of the neural fibers in brain white matter. To the variety of existing techniques, we wish to add novel approaches that exploit differential geometry and tensor calculus. In Diffusion Tensor Imaging (DTI), the diffusion of water is modeled by a symmetric positive definite second order tensor, leading naturally to a Riemannian geometric framework. A limitation is that it is based on the assumption that there exists a single dominant direction of fibers restricting the thermal motion of water molecules. Using HARDI data and higher order tensor models, we can extract multiple relevant directions, and Finsler geometry provides the natural geometric generalization appropriate for multi-fiber analysis. In this paper we provide an exact criterion to determine whether a spherical function satisfies the strong convexity criterion essential for a Finsler norm. We also show a novel fiber tracking method in Finsler setting. Our model incorporates a scale parameter, which can be beneficial in view of the noisy nature of the data. We demonstrate our methods on analytic as well as simulated and real HARDI data

A new species of Colostethus (Anura, Dendrobatidae) from French Guiana with a redescription of Colostethus beebei (Noble, 1923) from its type locality

A new species of Colostethus, long mistaken for Colostethus beebei, is described from French Guiana. The new species can be distinguished from congeners by absence of median lingual process, first finger longer than second, third finger not distinctly swollen in males, differences in tadpole morphology, coloration and pattern (e.g. absence of dorsolateral stripe), bioacoustics, and reproductive behavior. A complete redescription of Colostethus beebei plus description of its tadpole and call is provided on the basis of recently collected topotypic specimens. The range of C. beebei is restricted to the Kaieteur plateau, Pakaraima Mountains, Guyana

Manganese pigmented anodized copper as solar selective absorber

The study concerns the optical and structural properties of layers obtained by a new efficient surface treatment totally free of chromium species. The process is made up of an anodic oxidation of copper in an alkaline solution followed by an alkaline potassium permanganate dipping post-treatment. Coatings, obtained at the lab and pilot scales, are stable up to 220 °C in air and vacuum, present low emissivity (0.14 at 70 °C) and high solar absorptivity (0.96), i.e. a suitable thermal efficiency (0.84 at 70 °C)

Arsenic induces metabolome remodeling in mature human adipocytes.

Human lifetime exposure to arsenic through drinking water, food supply or industrial pollution leads to its accumulation in many organs such as liver, kidneys, lungs or pancreas but also adipose tissue. Recently, population-based studies revealed the association between arsenic exposure and the development of metabolic diseases such as obesity and type 2 diabetes. To shed light on the molecular bases of such association, we determined the concentration that inhibited 17% of cell viability and investigated the effects of arsenic acute exposure on adipose-derived human mesenchymal stem cells differentiated in vitro into mature adipocytes and treated with sodium arsenite (NaAsO &lt;sub&gt;2&lt;/sub&gt; , 10 nM to 10 µM). Untargeted metabolomics and gene expression analyses revealed a strong dose-dependent inhibition of lipogenesis and lipolysis induction, reducing the cellular ability to store lipids. These dysregulations were emphasized by the inhibition of the cellular response to insulin, as shown by the perturbation of several genes and metabolites involved in the mentioned biological pathways. Our study highlighted the activation of an adaptive oxidative stress response with the strong induction of metallothioneins and increased glutathione levels in response to arsenic accumulation that could exacerbate the decreased insulin sensitivity of the adipocytes. Arsenic exposure strongly affected the expression of arsenic transporters, responsible for arsenic influx and efflux, and induced a pro-inflammatory state in adipocytes by enhancing the expression of the inflammatory interleukin 6 (IL6). Collectively, our data showed that an acute exposure to low levels of arsenic concentrations alters key adipocyte functions, highlighting its contribution to the development of insulin resistance and the pathogenesis of metabolic disorders