1,045 research outputs found

    Investing in Biodiversity Conservation: Proceedings of a Workshop

    Get PDF
    This document presents the proceedings of a one-day Workshop on Investing in Biodiversity Conservation held at the Inter-American Development Bank in Washington, D.C., on October 28, 1996. The first part of the workshop was dedicated to the presentation of key topics on biodiversity financing by five leaders in the field. The second part of the workshop was dedicated to a discussion and exchange of ideas on the role of the IDB in investing in biodiversity conservation. Three main recommendations emerged: 1) The Bank should prepare a report on on its experience in biodiversity projects and development programs with biodiversity components; 2) A task force should be formed to work on a bio-diversity policy or strategy; 3) IDB staff should be trained to understand the biodiversity concept and its implications in project preparation and implementation.Environmental Policy, Biodiversity, Natural Resources Management

    Identifying and Inactivating Bacterial Spores

    Get PDF
    Problems associated with, and new strategies for, inactivating resistant organisms like Bacillus canaveralius (found at Kennedy Space Center during a survey of three NASA cleanrooms) have been defined. Identifying the particular component of the spore that allows its heightened resistance can guide the development of sterilization procedures that are targeted to the specific molecules responsible for resistance, while avoiding using unduly harsh methods that jeopardize equipment. The key element of spore resistance is a multilayered protein shell that encases the spore called the spore coat. The coat of the best-studied spore-forming microbe, B. subtilis, consists of at least 45 proteins, most of which are poorly characterized. Several protective roles for the coat are well characterized including resistance to desiccation, large toxic molecules, ortho-phthalaldehyde, and ultraviolet (UV) radiation. One important long-term specific goal is an improved sterilization procedure that will enable NASA to meet planetary protection requirements without a terminal heat sterilization step. This would support the implementation of planetary protection policies for life-detection missions. Typically, hospitals and government agencies use biological indicators to ensure the quality control of sterilization processes. The spores of B. canaveralius that are more resistant to osmotic stress would serve as a better biological indicator for potential survival than those in use currently

    JAM: A Scalable Bayesian Framework for Joint Analysis of Marginal SNP Effects.

    Get PDF
    Recently, large scale genome-wide association study (GWAS) meta-analyses have boosted the number of known signals for some traits into the tens and hundreds. Typically, however, variants are only analysed one-at-a-time. This complicates the ability of fine-mapping to identify a small set of SNPs for further functional follow-up. We describe a new and scalable algorithm, joint analysis of marginal summary statistics (JAM), for the re-analysis of published marginal summary statistics under joint multi-SNP models. The correlation is accounted for according to estimates from a reference dataset, and models and SNPs that best explain the complete joint pattern of marginal effects are highlighted via an integrated Bayesian penalized regression framework. We provide both enumerated and Reversible Jump MCMC implementations of JAM and present some comparisons of performance. In a series of realistic simulation studies, JAM demonstrated identical performance to various alternatives designed for single region settings. In multi-region settings, where the only multivariate alternative involves stepwise selection, JAM offered greater power and specificity. We also present an application to real published results from MAGIC (meta-analysis of glucose and insulin related traits consortium) - a GWAS meta-analysis of more than 15,000 people. We re-analysed several genomic regions that produced multiple significant signals with glucose levels 2 hr after oral stimulation. Through joint multivariate modelling, JAM was able to formally rule out many SNPs, and for one gene, ADCY5, suggests that an additional SNP, which transpired to be more biologically plausible, should be followed up with equal priority to the reported index

    Ultraviolet-Resistant Bacterial Spores

    Get PDF
    A document summarizes a study in which it was found that spores of the SAFR-032 strain of Bacillus pumilus can survive doses of ultraviolet (UV) radiation, radiation, and hydrogen peroxide in proportions much greater than those of other bacteria. The study was part of a continuing effort to understand the survivability of bacteria under harsh conditions and develop means of sterilizing spacecraft to prevent biocontamination of Mars that could interfere with the search for life there

    Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study

    Get PDF
    Background: Computed tomography (CT) is the most common imaging modality in traumatic brain injury (TBI). However, its conventional use requires expert clinical interpretation and does not provide detailed quantitative outputs, which may have prognostic importance. Deep learning could reliably and efficiently detect, distinguish, and quantify different lesion types, providing opportunities for personalised treatment strategies and clinical research. Methods: An initial convolutional neural network (CNN) was trained and validated on expert manual segmentations (97 scans). This CNN was then used to automatically segment a new set of 839 scans, which were then manually corrected by experts. From these, a subset of 184 scans was used to train a final CNN for multi-class, voxel-wise segmentation of lesion types. The performance of this CNN was evaluated on a held-out test set with 655 scans. External validation was performed on a large, independent set of 500 patients from a different continent. Findings: When compared to manual reference, CNN-derived lesion volumes showed a mean error of 0·86mL (95% CI -5·23 to 6·94) for intraparenchymal haemorrhage (IPH), 1·83mL (-12·01 to 15·66) for extra-axial haemorrhage (EAH), 2·09mL (-9·38 to 13·56) for perilesional oedema and 0·07mL (-1·00 to 1·13) for intraventricular haemorrhage (IVH). Further, the CNN detected lesions with AUCs of 0·90 (0·86-0·94) for IPH, 0·80 (0·75-0·85) for EAH, 0·95 (0·89-1·00) for IVH on the external, independent patient dataset. Interpretation: We demonstrate the ability of a CNN to separately segment, detect and quantify multi-class haemorrhagic lesions and importantly, perilesional oedema. These volumetric lesion estimates allow clinically relevant quantification of lesion burden and progression, with potential applications in clinical care and research in TBI. Funding: European Union 7th Framework Programme, Hannelore Kohl Stiftung; OneMind; Integra Neurosciences; European Research Council Horizon 2020; Engineering and Physical Sciences Research Council (UK); Academy of Medical Sciences/Health Foundation (UK); National Institute for Health Research (UK).CENTER-TBI study was supported by the European Union 7th Framework program (EC grant 602150). Additional funding sources: Hannelore Kohl Stiftung; NeuroTrauma Sciences; Integra Neurosciences; European Research Council (ERC) Horizon 2020 (EC grant 757173); Engineering and Physical Sciences Research Council (EPSRC) (EP/R511547/1); Academy of Medical Sciences/The Health Foundation (UK); National Institute for Health Research (UK)
    corecore