Dynamique des populations de Gerbilliscus kempi et Taterillus gracilis (Rodentia, Muridae) à Tanongou dans la réserve de biosphère de la pendjari au Bénin

Pour préserver les agrosystèmes plus stables et peu perturbés de Tanongou dans la zone d’occupation contrôlée de la réserve de biosphère de la pendjari au Nord-Ouest du Bénin, des pullulations de rongeurs, la dynamique des populations de Gerbilliscus kempi et Taterillus gracilis a été étudiée entre septembre 2010 et Novembre 2011. Les résultats ont montré que sur une richesse spécifique de 6 espèces, Taterillus gracilis et Gerbilliscus kempi sont les plus abondantes avec 0,53 pour l’indice de diversité de Simpson, 1,24 pour celui de Shannon-Wiener et 0,86 pour celui d’Equitabilité de Piélou. La densité moyenne globale était de 8,62 individus/ha avec 4,87 individus/ha pour T. gracilis contre 2,83 individus/ha pour G. kempi. La connaissance du cycle annuel d’abondance des deux espèces de rongeurs et de la période des minima d’abondance, constitue un outil essentiel dans la lutte préventive contre leur éventuelle pullulation.Mots clés : Rongeurs, espèces, abondance, cycle annuel, Bénin

Using Machine Learning to Collect and Facilitate Remote Access to Biomedical Databases: Development of the Biomedical Database Inventory

[Abstract] Background: Currently, existing biomedical literature repositories do not commonly provide users with specific means to locate and remotely access biomedical databases. Objective: To address this issue, we developed the Biomedical Database Inventory (BiDI), a repository linking to biomedical databases automatically extracted from the scientific literature. BiDI provides an index of data resources and a path to access them seamlessly. Methods: We designed an ensemble of deep learning methods to extract database mentions. To train the system, we annotated a set of 1242 articles that included mentions of database publications. Such a data set was used along with transfer learning techniques to train an ensemble of deep learning natural language processing models targeted at database publication detection. Results: The system obtained an F1 score of 0.929 on database detection, showing high precision and recall values. When applying this model to the PubMed and PubMed Central databases, we identified over 10,000 unique databases. The ensemble model also extracted the weblinks to the reported databases and discarded irrelevant links. For the extraction of weblinks, the model achieved a cross-validated F1 score of 0.908. We show two use cases: one related to “omics” and the other related to the COVID-19 pandemic. Conclusions: BiDI enables access to biomedical resources over the internet and facilitates data-driven research and other scientific initiatives. The repository is openly available online and will be regularly updated with an automatic text processing pipeline. The approach can be reused to create repositories of different types (ie, biomedical and others).Proyecto colaborativo de integración de datos genómicos; PI17/0156

Morphometric characterization of parasite Varroa sp. of bee Apis Mellifera L. in Benin

Open Access JournalVarroa sp. is one of the most important pests of world of bees A. mellifera Linnaeus (Hymenoptera: Apidae). The aim of this study is to analyze the morphological variability of Varroa so as to identify the different morphotypes of V. destructor. The study was conducted in 24 localities and 24 municipalities located in three regions (North-East, North-West and the Centre) of Benin. One to two hives were randomly selected per locality for collecting samples. In total 46 Varroa were examined in this study. Analysis of variance components was used to determine the share of the variability of morphological characteristics of V. destructor based on localities and climatic zones. Numerical classification was performed to group the populations of V. destructor based on morphological descriptors. The results show that the variability of morphological descriptors of V. destructor is usually larger at the community level than in climatic zones. In total four morphotypes of V. destructor are distinguished in Benin through the 4 variables used in the study

Engineering the spatial confinement of exciton-polaritons in semiconductors

We demonstrate the spatial confinement of electronic excitations in a solid state system, within novel artificial structures that can be designed having arbitrary dimensionality and shape. The excitations under study are exciton-polaritons in a planar semiconductor microcavity. They are confined within a micron-sized region through lateral trapping of their photon component. Striking signatures of confined states of lower and upper polaritons are found in angle-resolved light emission spectra, where a discrete energy spectrum and broad angular patterns are present. A theoretical model supports unambiguously our observations

Improving Knowledge Acquisition in Collaborative Knowledge Construction Tool with Virtual Catalyst

Noctua is a web tool to assist in Knowledge Acquisition and Collaborative Knowledge Construction processes. Noctua has an innovation: a Virtual Catalyst designed to facilitate the task of eliciting and validating knowledge. The Virtual Catalyst queries participants, proposing new knowledge, seeking confirmation to the knowledge already elicited, and showing conflicting opinions. The Virtual Catalyst takes into account participants' profiles in order to automatically ask them questions related to each one's field of knowledge or interest. This paper presents Noctua and its Virtual Catalyst. The tool was submitted to experimentation and the analysis of the results showed that the primary goal of increasing the rate of knowledge construction was achieved (up to 144 % in the rate of knowledge creation), and also showed some unexpected beneficial outcomes

Backflashes from fast-gated avalanche photodiodes in quantum key distribution

InGaAs single-photon avalanche photodiodes (APDs) are key enablers for high-bit rate quantum key distribution. However, the deviation of such detectors from ideal models can open side-channels for an eavesdropper, Eve, to exploit. The phenomenon of backflashes, whereby APDs reemit photons after detecting a photon, gives Eve the opportunity to passively learn the information carried by the detected photon without the need to actively interact with the legitimate receiver, Bob. While this has been observed in slow-gated detectors, it has not been investigated in fast-gated APDs where it has been posited that this effect would be lessened. Here, we perform the first experiment to characterize the security threat that backflashes provide in a GHz-gated self-differencing APD using the metric of information leakage. We find that, indeed, the information leakage is lower than that reported for slower-gated detectors, and we show that its effect on the secure key rate is negligible. We also relate the rate of backflash events to the APD dark current, thereby suggesting that their origin is the InP multiplication region in the APD

A Hybrid Integrated Quantum Key Distribution Transceiver Chip

Quantum photonic technologies, such as quantum key distribution, are already benefiting greatly from the rise of integrated photonics. However, the flexibility in design of these systems is often restricted by the properties of the integration material platforms. Here, we overcome this choice by using hybrid integration of ultra-low-loss silicon nitride waveguides with indium phosphide electro-optic modulators to produce high-performance quantum key distribution transceiver chips. Access to the best properties of both materials allows us to achieve active encoding and decoding of photonic qubits on-chip at GHz speeds and with sub-1% quantum bit error rates over long fibre distances. We demonstrate bidirectional secure bit rates of 1.82 Mbps over 10 dB channel attenuation and positive secure key rates out to 250 km of fibre. The results support the imminent utility of hybrid integration for quantum photonic circuits and the wider field of photonics.Comment: 13 pages, 5 figures, 1 tabl

Dithiolethione ACDT suppresses neuroinflammation and ameliorates disease severity in experimental autoimmune encephalomyelitis

Multiple sclerosis (MS) is an autoimmune disorder characterized by the central nervous system (CNS) infiltration of myelin-specific pathogenic T cells followed by brain inflammation in association with demyelination. Similarly, experimental autoimmune encephalomyelitis (EAE), the animal model of MS, also exhibits increased CNS infiltration of pathogenic T cells, including Th1 and Th17, leading to detrimental effects of neuroinflammation and demyelination. We previously reported that 3H-1,2-dithiole-3-thione (D3T), the structurally-simplest of the sulfur-containing dithiolethiones, exerted a promising therapeutic effect in EAE. In the current study we report that 5-Amino-3-thioxo-3H-(1,2)dithiole-4-carboxylic acid ethyl ester (ACDT), a substituted derivative of D3T, exhibits anti-inflammatory properties in EAE. ACDT, administered post immunization, delayed disease onset and reduced disease severity in chronic C57BL/6 EAE, and ACDT, administered during disease remission, suppressed disease relapse in relapsing-remitting SJL/J EAE. Further analysis of the cellular and molecular mechanisms underlying the protective effects of ACDT in EAE revealed that ACDT inhibited pathogenic T cell infiltration, suppressed microglia activation, repressed neurotoxic A1 astrocyte generation, lessened blood-brain barrier disruption, and diminished MMP3/9 production in the CNS of EAE. In summary, we demonstrate that ACDT suppresses neuroinflammation and ameliorates disease severity in EAE through multiple cellular mechanisms. Our findings suggest the potential of developing ACDT as a novel therapeutic agent for the treatment of MS/EAE

Foxh1/Nodal Defines Context-Specific Direct Maternal Wnt/β-Catenin Target Gene Regulation in Early Development

We thank Jessica Cheung (UC Irvine) and Yvonne Turnbull (University of Aberdeen) for technical and management support; Gert Jan Veenstra (Radboud University, Nijmegen) for discussion; and Adam Lynch and Victor Velecela (University of Aberdeen), for comments on the manuscript. We also thank Professor Masanori Taira (University of Tokyo, currently Chuo University) and Dr Norihiro Sudou (Nara Institute of Science and Technology, currently Tokyo Women's Medical University) for the siamois antibody; and Professor Dan Kessler (University of Pennsylvania) for siamois constructs. This research was supported by the Biotechnology and Biological Sciences Research Council (BBSRC) in the United Kingdom (BB/M001695/1) and by NIH in the United States (NIH GM126395). SH additionally acknowledges personal funding support as a Royal Society/Leverhulme Trust Senior Research Fellow (SRF\R1\191017).Peer reviewedPublisher PD

Dimethyl itaconate, an itaconate derivative, exhibits immunomodulatory effects on neuroinflammation in experimental autoimmune encephalomyelitis

Background: Inflammatory stimuli induce immunoresponsive gene 1 (IRG1) expression that in turn catalyzes the production of itaconate from the tricarboxylic acid cycle. Itaconate has recently emerged as a regulator of immune cell functions, especially in macrophages. Studies show that itaconate is required for the activation of anti-inflammatory transcription factor Nrf2 by LPS in mouse and human macrophages, and LPS-activated IRG1-/- macrophages that lack endogenous itaconate production exhibit augmented inflammatory responses. Moreover, dimethyl itaconate (DMI), an itaconate derivative, inhibits IL-17-induced IκBς activation in keratinocytes and modulates IL-17-IκBς pathway-mediated skin inflammation in an animal model of psoriasis. Currently, the effect of itaconate on regulating macrophage functions and peripheral inflammatory immune responses is well established. However, its effect on microglia (MG) and CNS inflammatory immune responses remains unexplored. Thus, we investigated whether itaconate possesses an immunomodulatory effect on regulating MG activation and CNS inflammation in animal models of multiple sclerosis, experimental autoimmune encephalomyelitis (EAE). Methods: Chronic C57BL/6 EAE was induced followed by DMI treatment. The effect of DMI on disease severity, blood-brain barrier (BBB) disruption, MG activation, peripheral Th1/Th17 differentiation, and the CNS infiltration of Th1/Th17 cells in EAE was determined. Primary MG was cultured to study the effect of DMI on MG activation. Relapsing-remitting SJL/J EAE was induced to assess the therapeutic effect of DMI. Results: Our results show DMI ameliorated disease severity in the chronic C57BL/6 EAE model. Further analysis of the cellular and molecular mechanisms revealed that DMI mitigated BBB disruption, inhibited MMP3/MMP9 production, suppressed microglia activation, inhibited peripheral Th1/Th17 differentiation, and repressed the CNS infiltration of Th1 and Th17 cells. Strikingly, DMI also exhibited a therapeutic effect on alleviating severity of relapse in the relapsing-remitting SJL/J EAE model. Conclusions: We demonstrate that DMI suppresses neuroinflammation and ameliorates disease severity in EAE through multiple cellular and molecular mechanisms, suggesting that DMI can be developed as a novel therapeutic agent for th