Mass-Balance-Consistent Geological Stock Accounting: a New Approach toward Sustainable Management of Mineral Resources

Global resource extraction raises concerns about environmental pressures and the security of mineral supply. Strategies to address these concerns depend on robust information on natural resource endowments, and on suitable methods to monitor and model their changes over time. However, current mineral resources and reserves reporting and accounting workflows are poorly suited for addressing mineral depletion or answering questions about the long-term sustainable supply. Our integrative review finds that the lack of a robust theoretical concept and framework for mass-balance (MB)-consistent geological stock accounting hinders systematic industry-government data integration, resource governance, and strategy development. We evaluate the existing literature on geological stock accounting, identify shortcomings of current monitoring of mine production, and outline a conceptual framework for MB-consistent system integration based on material flow analysis (MFA). Our synthesis shows that recent developments in Earth observation, geoinformation management, and sustainability reporting act as catalysts that make MB-consistent geological stock accounting increasingly feasible. We propose first steps for its implementation and anticipate that our perspective as “resource realists” will facilitate the integration of geological and anthropogenic material systems, help secure future mineral supply, and support the global sustainability transition

Long-Term Blocking of Calcium Channels in mdx Mice Results in Differential Effects on Heart and Skeletal Muscle

The disease mechanisms underlying dystrophin-deficient muscular dystrophy are complex, involving not only muscle membrane fragility, but also dysregulated calcium homeostasis. Specifically, it has been proposed that calcium channels directly initiate a cascade of pathological events by allowing calcium ions to enter the cell. The objective of this study was to investigate the effect of chronically blocking calcium channels with the aminoglycoside antibiotic streptomycin from onset of disease in the mdx mouse model of Duchenne muscular dystrophy (DMD)

VEGFR2 promotes central endothelial activation and the spread of pain in inflammatory arthritis

Chronic pain can develop in response to conditions such as inflammatory arthritis. The central mechanisms underlying the development and maintenance of chronic pain in humans are not well elucidated although there is evidence for a role of microglia and astrocytes. However in pre-clinical models of pain, including models of inflammatory arthritis, there is a wealth of evidence indicating roles for pathological glial reactivity within the CNS. In the spinal dorsal horn of rats with painful inflammatory arthritis we found both a significant increase in CD11b+ microglia-like cells and GFAP+ astrocytes associated with blood vessels, and the number of activated blood vessels expressing the adhesion molecule ICAM-1, indicating potential glio-vascular activation. Using pharmacological interventions targeting VEGFR2 in arthritic rats, to inhibit endothelial cell activation, the number of dorsal horn ICAM-1+ blood vessels, CD11b+ microglia and the development of secondary mechanical allodynia, an indicator of central sensitization, were all prevented. Targeting endothelial VEGFR2 by inducible Tie2-specific VEGFR2 knock-out also prevented secondary allodynia in mice and glio-vascular activation in the dorsal horn in response to inflammatory arthritis. Inhibition of VEGFR2 in vitro significantly blocked ICAM-1-dependent monocyte adhesion to brain microvascular endothelial cells, when stimulated with inflammatory mediators TNFa and VEGF-A165a. Taken together our findings suggest that a novel VEGFR2-mediated spinal cord gliovascular mechanism may promote peripheral CD11b+ circulating cell transmigration into the CNS parenchyma and contribute to the development of chronic pain in inflammatory arthritis. We hypothesise that preventing this glio-vascular activation and circulating cell translocation into the spinal cord could be a new therapeutic strategy for pain caused by rheumatoid arthritis

Identification of genetic variants associated with Huntington's disease progression: a genome-wide association study

Background Huntington's disease is caused by a CAG repeat expansion in the huntingtin gene, HTT. Age at onset has been used as a quantitative phenotype in genetic analysis looking for Huntington's disease modifiers, but is hard to define and not always available. Therefore, we aimed to generate a novel measure of disease progression and to identify genetic markers associated with this progression measure. Methods We generated a progression score on the basis of principal component analysis of prospectively acquired longitudinal changes in motor, cognitive, and imaging measures in the 218 indivduals in the TRACK-HD cohort of Huntington's disease gene mutation carriers (data collected 2008–11). We generated a parallel progression score using data from 1773 previously genotyped participants from the European Huntington's Disease Network REGISTRY study of Huntington's disease mutation carriers (data collected 2003–13). We did a genome-wide association analyses in terms of progression for 216 TRACK-HD participants and 1773 REGISTRY participants, then a meta-analysis of these results was undertaken. Findings Longitudinal motor, cognitive, and imaging scores were correlated with each other in TRACK-HD participants, justifying use of a single, cross-domain measure of disease progression in both studies. The TRACK-HD and REGISTRY progression measures were correlated with each other (r=0·674), and with age at onset (TRACK-HD, r=0·315; REGISTRY, r=0·234). The meta-analysis of progression in TRACK-HD and REGISTRY gave a genome-wide significant signal (p=1·12 × 10−10) on chromosome 5 spanning three genes: MSH3, DHFR, and MTRNR2L2. The genes in this locus were associated with progression in TRACK-HD (MSH3 p=2·94 × 10−8 DHFR p=8·37 × 10−7 MTRNR2L2 p=2·15 × 10−9) and to a lesser extent in REGISTRY (MSH3 p=9·36 × 10−4 DHFR p=8·45 × 10−4 MTRNR2L2 p=1·20 × 10−3). The lead single nucleotide polymorphism (SNP) in TRACK-HD (rs557874766) was genome-wide significant in the meta-analysis (p=1·58 × 10−8), and encodes an aminoacid change (Pro67Ala) in MSH3. In TRACK-HD, each copy of the minor allele at this SNP was associated with a 0·4 units per year (95% CI 0·16–0·66) reduction in the rate of change of the Unified Huntington's Disease Rating Scale (UHDRS) Total Motor Score, and a reduction of 0·12 units per year (95% CI 0·06–0·18) in the rate of change of UHDRS Total Functional Capacity score. These associations remained significant after adjusting for age of onset. Interpretation The multidomain progression measure in TRACK-HD was associated with a functional variant that was genome-wide significant in our meta-analysis. The association in only 216 participants implies that the progression measure is a sensitive reflection of disease burden, that the effect size at this locus is large, or both. Knockout of Msh3 reduces somatic expansion in Huntington's disease mouse models, suggesting this mechanism as an area for future therapeutic investigation

Using Genome Query Language (GQL) to uncover genetic variation

Motivation:With high throughput DNA sequencing costs dropping below $1,000 for human genomes, data storage, retrieval, and analysis are the major bottlenecks in biological studies. In order to address the large-data challenges, we advocate a clean separation between the evidence collection and the inference in variant calling. We define and implement a Genome Query Language (GQL) that allows for the rapid collection of evidence needed for calling variants. Results: We provide a number of cases to showcase the use of GQL for complex evidence collection, such as the evidence for large structural variations. Specifically, typical GQL queries can be written in5-10 lines of high level code, and search large data sets (100GB) in minutes. We also demonstrate its complementarity with other variant calling tools. Popular variant calling tools can achieve one order of magnitude speed-up by using GQL to retrieve evidence. Finally, we show how GQL can be used to query and compare multiple data-sets. By separating the evidence and inference for variant calling, it frees all variant detection tools from the data intensive evidence collection, and focus on statistical inference. Availability: GQL can be downloaded fro