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Richards, M.

Publications and source records attributed to Richards, M..

5 recordsLinked to original sources

Increasing phylogenetic stochasticity at high elevations on summits across a remote North American wilderness

PREMISE OF THE STUDYAt the intersection of ecology and evolutionary biology, community phylogenetics can provide insights into overarching biodiversity patterns, particularly in remote and understudied ecosystems. To understand community assembly of the high-alpine flora of the Sawtooth National Forest, USA, we analyzed phylogenetic structure within and between nine summit communities.\n\nMETHODSWe used high-throughput sequencing to supplement existing data and infer a nearly completely sampled community phylogeny of the alpine vascular flora. We calculated mean nearest taxon distance (MNTD) and mean pairwise distance (MPD) to quantify phylogenetic divergence within summits, and assed how maximum elevation explains phylogenetic structure. To evaluate similarities between summits we quantified phylogenetic turnover, taking into consideration micro-habitats (talus vs. meadows).\n\nKEY RESULTSWe found different patterns of community phylogenetic structure within the six most species-rich orders, but across all vascular plants phylogenetic structure was largely no different from random. There was a significant negative correlation between elevation and tree-wide phylogenetic diversity (MPD) within summits: significant overdispersion degraded as elevation increased. Between summits we found high phylogenetic turnover, which was driven by greater niche heterogeneity on summits with alpine meadows.\n\nCONCLUSIONSThis study provides further evidence that stochastic processes shape the assembly of vascular plant communities in the high-alpine at regional scales. However, order-specific patterns suggest adaptations may be important for assembly of specific sectors of the plant tree of life. Further studies quantifying functional diversity will be important to disentangle the interplay of eco-evolutionary processes that likely shape broad community phylogenetic patterns in extreme environments.

evolutionary biology

Reproducible big data science: A case study in continuous FAIRness

Big biomedical data create exciting opportunities for discovery, but make it difficult to capture analyses and outputs in forms that are findable, accessible, interoperable, and reusable (FAIR). In response, we describe tools that make it easy to capture, and assign identifiers to, data and code throughout the data lifecycle. We illustrate the use of these tools via a case study involving a multi-step analysis that creates an atlas of putative transcription factor binding sites from terabytes of ENCODE DNase I hypersensitive sites sequencing data. We show how the tools automate routine but complex tasks, capture analysis algorithms in understandable and reusable forms, and harness fast networks and powerful cloud computers to process data rapidly, all without sacrificing usability or reproducibility--thus ensuring that big data are not hard-to-(re)use data. We compare and contrast our approach with other approaches to big data analysis and reproducibility.

bioinformatics

Delirium symptoms are associated with decline in cognitive function between ages 53 to 69: findings from a British birth cohort study.

INTRODUCTIONFew population studies have investigated whether longitudinal decline after delirium in mid-to-late life might affect specific cognitive domains.\n\nMETHODSParticipants from a birth cohort completing assessments of search speed, verbal memory and the Addenbrookes Cognitive Examination at age 69 were asked about delirium symptoms between ages 60-69. Linear regression models estimated associations between delirium symptoms and cognitive outcomes.\n\nRESULTSPeriod prevalence of delirium between 60 and 69 was 4% (95% CI 3.2%,4.9%). Self-reported symptoms of delirium over the seventh decade were associated with worse scores in the Addenbrookes Cognitive Examination (-1.7 points, 95% CI -3.2, -0.1, p=0.04). In association with delirium symptoms, verbal memory scores were initially lower, with subsequent decline in search speed by age 69. These effects were independent of other Alzheimers risk factors.\n\nDISCUSSIONDelirium symptoms may be common even at relatively younger ages, and their presence may herald cognitive decline, particularly in search speed, over this time period.

epidemiology

Apolipoprotein-E (ApoE) ϵ4 and cognitive decline over the adult life course

We tested the association between APOE-{varepsilon}4 and processing speed and memory between ages 43 and 69 in a population-based birth cohort. Analyses of processing speed (using a timed letter search task) and episodic memory (a 15-item word learning test) were conducted at ages 43, 53, 60-64 and 69 years using linear and multivariable regression, adjusting for gender and childhood cognition. Linear mixed models, with random intercepts and slopes, were conducted to test the association between APOE and the rate of decline in these cognitive scores from age 43 to 69. Model fit was assessed with the Bayesian Information Criterion. A cross-sectional association between APOE-{varepsilon}4 and memory scores was detected at age 69 for both heterozygotes and homozygotes ({beta}=-0.68 & {beta}=-1.38 respectively, p=.03) with stronger associations in homozygotes; no associations were observed before this age. Homozygous carriers of APOE-{varepsilon}4 had a faster rate of decline in memory between ages 43 and 69, when compared to noncarriers, after adjusting for gender and childhood cognition ({beta}=-0.05, p=.04). There were no cross-sectional or longitudinal associations between APOE-{varepsilon}4 and processing speed. We conclude that APOE-{varepsilon}4 is associated with a subtly faster rate of memory decline from midlife to early old age; this may be due to effects of APOE-{varepsilon}4 becoming manifest around the latter stage of life. Continuing follow-up will determine what proportion of this increase will become clinically significant.

epidemiology

ProbAnnoWeb and ProbAnnoPy: probabilistic annotation and gap-filling of metabolic reconstructions

SummaryGap-filling is a necessary step to produce quality genome-scale metabolic reconstructions capable of flux-balance simulation. Most available gap-filling tools use an organism-agnostic approach, where reactions are selected from a database to fill gaps without consideration of the target organism. Conversely, our likelihood based gap-filling with probabilistic annotations selects candidate reactions based on a likelihood score derived specifically from the target organisms genome. Here, we present two new implementations of probabilistic annotation and likelihood based gap-filling: a web service called ProbAnnoWeb, and a standalone python package called ProbAnnoPy.\n\nAvailability and ImplementationOur tools are available as a web service with no installation needed (ProbAnnoWeb), available at http://probannoweb.systemsbiology.net, and as a local python package implementation (ProbAnnoPy), available for download at http://github.com/PriceLab/probannopy.\n\nContacthttp://Evangelos.Simeonidis@systemsbiology.org; http://Nathan.Price@systemsbiology.org

systems biology