| 1. |
- Berger, Eloise, et al.
(författare)
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Association between low-grade inflammation and Breast cancer and B-cell Myeloma and Non-Hodgkin Lymphoma : Findings from two prospective cohorts
- 2018
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Chronic inflammation may be involved in cancer development and progression. Using 28 inflammatory-related proteins collected from prospective blood samples from two case-control studies nested in the Italian component of the European Prospective Investigation into Cancer and nutrition (n = 261) and in the Northern Sweden Health and Disease Study (n = 402), we tested the hypothesis that an inflammatory score is associated with breast cancer (BC) and Β-cell Non-Hodgkin Lymphoma (B-cell NHL, including 68 multiple myeloma cases) onset. We modelled the relationship between this inflammatory score and the two cancers studied: (BC and B-cell NHL) using generalised linear models, and assessed, through adjustments the role of behaviours and lifestyle factors. Analyses were performed by cancer types pooling both populations, and stratified by cohorts, and time to diagnosis. Our results suggested a lower inflammatory score in B-cell NHL cases (β = -1.28, p = 0.012), and, to lesser, extent with BC (β = -0.96, p = 0.33) compared to controls, mainly driven by cancer cases diagnosed less than 6 years after enrolment. These associations were not affected by subsequent adjustments for potential intermediate confounders, notably behaviours. Sensitivity analyses indicated that our findings were not affected by the way the inflammatory score was calculated. These observations call for further studies involving larger populations, larger variety of cancer types and repeated measures of larger panel of inflammatory markers.
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| 2. |
- Delpierre, Cyrille, et al.
(författare)
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Origins of heath inequalities : the case for Allostatic Load
- 2016
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Ingår i: Longitudinal and Life Course Studies. - : Bristol University Press. - 1757-9597. ; 7:1, s. 79-103
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Tidskriftsartikel (refereegranskat)abstract
- In an opening paper Delpierre et al. explore the concept of allostatic load. The impact of the environment on our biological systems is summarised by the concept of embodiment. The biological embedding of social conditions could therefore be a relevant mechanism to partly explain the social gradient in health. A key issue is how to measure the 'physiological reality' the biological expression of embodiment at individual and population levels. Allostatic load (AL) has been proposed as a measure of the overall cost of adapting to the environment and may be a relevant tool or concept for measuring the way we have embodied our environment. Social inequalities in health may be partly explained by the embodiment of social environments, and AL may allow us to measure and compare embodiment between socioeconomic groups. However, before operationalising AL, a number of issues deserve further exploration. Among these, the choice of biological systems, and variables within each system, that should be included to remain 'loyal' to the theory of biological multisystem wastage underlying AL and the most appropriate methodological approach to be used to build an AL score, are particularly important. Moreover, studies analysing the link between adverse environments (physical, chemical, nutritional, psychosocial) across the life course and AL remain rare. Such studies require cohorts with data on socioeconomic and psychosocial environments over the life course, with multiple biological measures, made at various stages across the life span. The development and maintenance of these cohorts is essential to continue exploring the promising results that could enhance our understanding of the genesis of the social gradient in health by measuring embodiment. These points are then debated in commentaries by Linn Getz and Margret Olafia Tomasdottir, Tony Robertson and Per Gustafson. The commentaries are followed by a response from the authors of the opening paper.
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| 3. |
- Kattge, Jens, et al.
(författare)
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TRY plant trait database - enhanced coverage and open access
- 2020
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Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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