195 research outputs found

    IL1B and DEFB1 Polymorphisms Increase Susceptibility to Invasive Mold Infection After Solid-Organ Transplantation.

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    BACKGROUND: Single-nucleotide polymorphisms (SNPs) in immune genes have been associated with susceptibility to invasive mold infection (IMI) among hematopoietic stem cell but not solid-organ transplant (SOT) recipients. METHODS: Twenty-four SNPs from systematically selected genes were genotyped among 1101 SOT recipients (715 kidney transplant recipients, 190 liver transplant recipients, 102 lung transplant recipients, 79 heart transplant recipients, and 15 recipients of other transplants) from the Swiss Transplant Cohort Study. Association between SNPs and the end point were assessed by log-rank test and Cox regression models. Cytokine production upon Aspergillus stimulation was measured by enzyme-linked immunosorbent assay in peripheral blood mononuclear cells (PBMCs) from healthy volunteers and correlated with relevant genotypes. RESULTS: Mold colonization (n = 45) and proven/probable IMI (n = 26) were associated with polymorphisms in the genes encoding interleukin 1β (IL1B; rs16944; recessive mode, P = .001 for colonization and P = .00005 for IMI, by the log-rank test), interleukin 1 receptor antagonist (IL1RN; rs419598; P = .01 and P = .02, respectively), and β-defensin 1 (DEFB1; rs1800972; P = .001 and P = .0002, respectively). The associations with IL1B and DEFB1 remained significant in a multivariate regression model (P = .002 for IL1B rs16944; P = .01 for DEFB1 rs1800972). The presence of 2 copies of the rare allele of rs16944 or rs419598 was associated with reduced Aspergillus-induced interleukin 1β and tumor necrosis factor α secretion by PBMCs. CONCLUSIONS: Functional polymorphisms in IL1B and DEFB1 influence susceptibility to mold infection in SOT recipients. This observation may contribute to individual risk stratification

    Less is Different: Emergence and Reduction Reconciled

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    This is a companion to another paper. Together they rebut two widespread philosophical doctrines about emergence. The first, and main, doctrine is that emergence is incompatible with reduction. The second is that emergence is supervenience; or more exactly, supervenience without reduction. In the other paper, I develop these rebuttals in general terms, emphasising the second rebuttal. Here I discuss the situation in physics, emphasising the first rebuttal. I focus on limiting relations between theories and illustrate my claims with four examples, each of them a model or a framework for modelling, from well-established mathematics or physics. I take emergence as behaviour that is novel and robust relative to some comparison class. I take reduction as, essentially, deduction. The main idea of my first rebuttal will be to perform the deduction after taking a limit of some parameter. Thus my first main claim will be that in my four examples (and many others), we can deduce a novel and robust behaviour, by taking the limit, N goes to infinity, of a parameter N. But on the other hand, this does not show that that the infinite limit is "physically real", as some authors have alleged. For my second main claim is that in these same examples, there is a weaker, yet still vivid, novel and robust behaviour that occurs before we get to the limit, i.e. for finite N. And it is this weaker behaviour which is physically real. My examples are: the method of arbitrary functions (in probability theory); fractals (in geometry); superselection for infinite systems (in quantum theory); and phase transitions for infinite systems (in statistical mechanics).Comment: 75 p

    Chronotype Genetic Variant in PER2 is Associated with Intrinsic Circadian Period in Humans

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    This is the final version. Available on open access from Nature Research via the DOI in this recordData Availability: The data that support the findings of this study from the UK BioBank will be made available at https://sleepgenetics.org and the underlying genotype and phenotype data are available through application to the UK Biobank. Other phenotype data are available on request, due to privacy or other restrictions, through co-corresponding author Dr. Scheer ([email protected]).The PERIOD2 (PER2) gene is a core molecular component of the circadian clock and plays an important role in the generation and maintenance of daily rhythms. rs35333999, a missense variant of PER2 common in European populations, has been shown to associate with later chronotype. Chronotype relates to the timing of biological and behavioral activities, including when we sleep, eat, and exercise, and later chronotype is associated with longer intrinsic circadian period (cycle length), a fundamental property of the circadian system. Thus, we tested whether this PER2 variant was associated with circadian period and found significant associations with longer intrinsic circadian period as measured under forced desynchrony protocols, the ‘gold standard’ for intrinsic circadian period assessment. Minor allele (T) carriers exhibited significantly longer circadian periods when determinations were based on either core body temperature or plasma melatonin measurements, as compared to non-carriers (by 12 and 11 min, respectively; accounting for ~7% of inter-individual variance). These findings provide a possible underlying biological mechanism for inter-individual differences in chronotype, and support the central role of PER2 in the human circadian timing system.European CommissionWellcome TrustMedical Research Council (MRC

    Water Availability Is the Main Climate Driver of Neotropical Tree Growth

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    • Climate models for the coming century predict rainfall reduction in the Amazonian region, including change in water availability for tropical rainforests. Here, we test the extent to which climate variables related to water regime, temperature and irradiance shape the growth trajectories of neotropical trees. • We developed a diameter growth model explicitly designed to work with asynchronous climate and growth data. Growth trajectories of 205 individual trees from 54 neotropical species censused every 2 months over a 4-year period were used to rank 9 climate variables and find the best predictive model. • About 9% of the individual variation in tree growth was imputable to the seasonal variation of climate. Relative extractable water was the main predictor and alone explained more than 60% of the climate effect on tree growth, i.e. 5.4% of the individual variation in tree growth. Furthermore, the global annual tree growth was more dependent on the diameter increment at the onset of the rain season than on the duration of dry season. • The best predictive model included 3 climate variables: relative extractable water, minimum temperature and irradiance. The root mean squared error of prediction (0.035 mm.d–1) was slightly above the mean value of the growth (0.026 mm.d–1). • Amongst climate variables, we highlight the predominant role of water availability in determining seasonal variation in tree growth of neotropical forest trees and the need to include these relationships in forest simulators to test, in silico, the impact of different climate scenarios on the future dynamics of the rainforest

    TRY plant trait database - enhanced coverage and open access

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    Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits

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    There are few examples of robust associations between rare copy number variants (CNVs) and complex continuous human traits. Here we present a large-scale CNV association meta-analysis on anthropometric traits in up to 191,161 adult samples from 26 cohorts. The study reveals five CNV associations at 1q21.1, 3q29, 7q11.23, 11p14.2, and 18q21.32 and confirms two known loci at 16p11.2 and 22q11.21, implicating at least one anthropometric trait. The discovered CNVs are recurrent and rare (0.01-0.2%), with large effects on height (> 2.4 cm), weight ( 5 kg), and body mass index (BMI) (> 3.5 kg/m(2)). Burden analysis shows a 0.41 cm decrease in height, a 0.003 increase in waist-to-hip ratio and increase in BMI by 0.14 kg/m2 for each Mb of total deletion burden (P = 2.5 x 10(-10), 6.0 x 10(-5), and 2.9 x 10(-3)). Our study provides evidence that the same genes (e.g., MC4R, FIBIN, and FMO5) harbor both common and rare variants affecting body size and that anthropometric traits share genetic loci with developmental and psychiatric disorders
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