1,654 research outputs found

    Adaptive introgression underlies polymorphic seasonal camouflage in snowshoe hares

    Get PDF
    Snowshoe hares (Lepus americanus) maintain seasonal camouflage by molting to a white winter coat, but some hares remain brown during the winter in regions with low snow cover. We show that cis-regulatory variation controlling seasonal expression of the Agouti gene underlies this adaptive winter camouflage polymorphism. Genetic variation at Agouti clustered by winter coat color across multiple hare and jackrabbit species, revealing a history of recurrent interspecific gene flow. Brown winter coats in snowshoe hares likely originated from an introgressed black-tailed jackrabbit allele that has swept to high frequency in mild winter environments. These discoveries show that introgression of genetic variants that underlie key ecological traits can seed past and ongoing adaptation to rapidly changing environments. (c) The Authors, Some Rights Reserved

    Potential of genomic technologies to improve disease resistance in molluscan aquaculture

    Get PDF
    Molluscan aquaculture is a major contributor to global seafood production, but is hampered by infectious disease outbreaks that can cause serious economic losses. Selective breeding has been widely used to improve disease resistance in major agricultural and aquaculture species, and has clear potential in molluscs, albeit its commercial application remains at a formative stage. Advances in genomic technologies, especially the development of cost-efficient genomic selection, have the potential to accelerate genetic improvement. However, tailored approaches are required owing to the distinctive reproductive and life cycle characteristics of molluscan species. Transgenesis and genome editing, in particular CRISPR/Cas systems, have been successfully trialled in molluscs and may further understanding and improvement of genetic resistance to disease through targeted changes to the host genome. Whole-organism genome editing is achievable on a much greater scale compared to other farmed species, making genome-wide CRISPR screening approaches plausible. This review discusses the current state and future potential of selective breeding, genomic tools and genome editing approaches to understand and improve host resistance to infectious disease in molluscs. This article is part of the Theo Murphy meeting issue ‘Molluscan genomics: broad insights and future directions for a neglected phylum’

    Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

    Full text link
    From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

    Quality of life at the end of life

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Little is known about self-perceived quality of life (QOL) near the end of life, because such information is difficult to collect and to interpret. Here, we describe QOL in the weeks near death and determine correlates of QOL over time, with emphasis on accounting for death and missing data.</p> <p>Methods</p> <p>Data on QOL were collected approximately every week in an ongoing randomized trial involving persons at the end of life. We used these data to describe QOL in the 52 weeks after enrollment in the trial (prospective analysis, N = 115), and also in the 10 weeks just prior to death (retrospective analysis, N = 83). The analysis consisted of graphs and regressions that accounted explicitly for death and imputed missing data.</p> <p>Results</p> <p>QOL was better than expected until the final 3 weeks of life, when a terminal drop was observed. Gender, race, education, cancer, and baseline health status were not significantly related to the number of “weeks of good-quality life” (WQL) during the study period. Persons younger than 60 had significantly higher WQL than older persons in the prospective analysis, but significantly lower WQL in the retrospective analysis. The retrospective results were somewhat sensitive to the imputation model.</p> <p>Conclusion</p> <p>In this exploratory study, QOL was better than expected in persons at the end of life, but special interventions may be needed for persons approaching a premature death, and also for the last 3 weeks of life. Our descriptions of the trajectory of QOL at the end of life may help other investigators to plan and analyze future studies of QOL. Methodology for dealing with death and the high amount of missing data in longitudinal studies at the end of life needs further investigation.</p

    Innocent parties or devious drug users: the views of primary healthcare practitioners with respect to those who misuse prescription drugs

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Many health professionals engage in providing health services for drug users; however, there is evidence of stigmatisation by some health professionals. Prescription drug misusers as a specific group, may also be subject to such judgment. This study aimed to understand issues for primary care health practitioners in relation to prescription drug misuse (PDM), by exploring the attitudes and experiences of healthcare professionals with respect to PDM.</p> <p>Methods</p> <p>Tape-recorded interviews were conducted with a purposive sample of general practitioners (17), community pharmacists (16) and 'key experts' (18) in New Zealand. Interviews were transcribed verbatim and a thematic analysis undertaken. Participants were offered vouchers to the value of NZ$30 for their participation.</p> <p>Results</p> <p>A major theme that was identified was that of two different types of patients involved in PDM, as described by participants - the 'abuser' and the 'overuser'. The 'abuser' was believed to acquire prescription medicines through deception for their own use or for selling on to the illicit market, to use the drugs recreationally, for a 'high' or to stave off withdrawal from illicit drugs. 'Overusers' were characterised as having become 'addicted' through inadvertent overuse and over prescribing, and were generally viewed more sympathetically by practitioners. It also emerged that practitioners' attitudes may have impacted on whether any harm reduction interventions might be offered. Furthermore, whilst practitioners might be more willing to offer help to the 'over-user', it seemed that there is a lack of appropriate services for this group, who may also lack a peer support network.</p> <p>Conclusions</p> <p>A binary view of PDM may not be helpful in understanding the issues surrounding PDM, nor in providing appropriate interventions. There is a need for further exploration of 'over users’ whose needs may not be being met by mainstream drug services, and issues of stigma in relation to ‘abusers’.</p

    Scoring of senescence signalling in multiple human tumour gene expression datasets, identification of a correlation between senescence score and drug toxicity in the NCI60 panel and a pro-inflammatory signature correlating with survival advantage in peritoneal mesothelioma

    Get PDF
    Background: Cellular senescence is a major barrier to tumour progression, though its role in pathogenesis of cancer and other diseases is poorly understood in vivo. Improved understanding of the degree to which latent senescence signalling persists in tumours might identify intervention strategies to provoke "accelerated senescence" responses as a therapeutic outcome. Senescence involves convergence of multiple pathways and requires ongoing dynamic signalling throughout its establishment and maintenance. Recent discovery of several new markers allows for an expression profiling approach to study specific senescence phenotypes in relevant tissue samples. We adopted a "senescence scoring" methodology based on expression profiles of multiple senescence markers to examine the degree to which signals of damage-associated or secretory senescence persist in various human tumours. Results: We first show that scoring captures differential induction of damage or inflammatory pathways in a series of public datasets involving radiotherapy of colon adenocarcinoma, chemotherapy of breast cancer cells, replicative senescence of mesenchymal stem cells, and progression of melanoma. We extended these results to investigate correlations between senescence score and growth inhibition in response to similar to 1500 compounds in the NCI60 panel. Scoring of our own mesenchymal tumour dataset highlighted differential expression of secretory signalling pathways between distinct subgroups of MPNST, liposarcomas and peritoneal mesothelioma. Furthermore, a proinflammatory signature yielded by hierarchical clustering of secretory markers showed prognostic significance in mesothelioma. Conclusions: We find that "senescence scoring" accurately reports senescence signalling in a variety of situations where senescence would be expected to occur and highlights differential expression of damage associated and secretory senescence pathways in a context-dependent manner

    Observation and study of baryonic B decays: B -> D(*) p pbar, D(*) p pbar pi, and D(*) p pbar pi pi

    Get PDF
    We present a study of ten B-meson decays to a D(*), a proton-antiproton pair, and a system of up to two pions using BaBar's data set of 455x10^6 BBbar pairs. Four of the modes (B0bar -> D0 p anti-p, B0bar -> D*0 p anti-p, B0bar -> D+ p anti-p pi-, B0bar -> D*+ p anti-p pi-) are studied with improved statistics compared to previous measurements; six of the modes (B- -> D0 p anti-p pi-, B- -> D*0 p anti-p pi-, B0bar -> D0 p anti-p pi- pi+, B0bar -> D*0 p anti-p pi- pi+, B- -> D+ p anti-p pi- pi-, B- -> D*+ p anti-p pi- pi-) are first observations. The branching fractions for 3- and 5-body decays are suppressed compared to 4-body decays. Kinematic distributions for 3-body decays show non-overlapping threshold enhancements in m(p anti-p) and m(D(*)0 p) in the Dalitz plots. For 4-body decays, m(p pi-) mass projections show a narrow peak with mass and full width of (1497.4 +- 3.0 +- 0.9) MeV/c2, and (47 +- 12 +- 4) MeV/c2, respectively, where the first (second) errors are statistical (systematic). For 5-body decays, mass projections are similar to phase space expectations. All results are preliminary.Comment: 28 pages, 90 postscript figures, submitted to LP0
    • 

    corecore