Rags To Burn

Portrait of Frank McFadden; Columns with burning fire on either side of the portraithttps://scholarsjunction.msstate.edu/cht-sheet-music/13867/thumbnail.jp

Outward expansion of the lunar wake: ARTEMIS observations

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95030/1/grl29516.pd

Melanoma Spheroids Grown Under Neural Crest Cell Conditions Are Highly Plastic Migratory/Invasive Tumor Cells Endowed with Immunomodulator Function

International audienceBACKGROUND: The aggressiveness of melanoma tumors is likely to rely on their well-recognized heterogeneity and plasticity. Melanoma comprises multi-subpopulations of cancer cells some of which may possess stem cell-like properties. Although useful, the sphere-formation assay to identify stem cell-like or tumor initiating cell subpopulations in melanoma has been challenged, and it is unclear if this model can predict a functional phenotype associated with aggressive tumor cells. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed the molecular and functional phenotypes of melanoma spheroids formed in neural crest cell medium. Whether from metastatic or advanced primary tumors, spheroid cells expressed melanoma-associated markers. They displayed higher capacity to differentiate along mesenchymal lineages and enhanced expression of SOX2, NANOG, KLF4, and/or OCT4 transcription factors, but not enhanced self-renewal or tumorigenicity when compared to their adherent counterparts. Gene expression profiling attributed a neural crest cell signature to these spheroids and indicated that a migratory/invasive and immune-function modulating program could be associated with these cells. In vitro assays confirmed that spheroids display enhanced migratory/invasive capacities. In immune activation assays, spheroid cells elicited a poorer allogenic response from immune cells and inhibited mitogen-dependent T cells activation and proliferation more efficiently than their adherent counterparts. Our findings reveal a novel immune-modulator function of melanoma spheroids and suggest specific roles for spheroids in invasion and in evasion of antitumor immunity. CONCLUSION/SIGNIFICANCE: The association of a more plastic, invasive and evasive, thus a more aggressive tumor phenotype with melanoma spheroids reveals a previously unrecognized aspect of tumor cells expanded as spheroid cultures. While of limited efficiency for melanoma initiating cell identification, our melanoma spheroid model predicted aggressive phenotype and suggested that aggressiveness and heterogeneity of melanoma tumors can be supported by subpopulations other than cancer stem cells. Therefore, it could be constructive to investigate melanoma aggressiveness, relevant to patients and clinical transferability

The Generation R Study: design and cohort update 2010

The Generation R Study is a population-based prospective cohort study from fetal life until young adulthood. The study is designed to identify early environmental and genetic causes of normal and abnormal growth, development and health during fetal life, childhood and adulthood. The study focuses on four primary areas of research: (1) growth and physical development; (2) behavioural and cognitive development; (3) diseases in childhood; and (4) health and healthcare for pregnant women and children. In total, 9,778 mothers with a delivery date from April 2002 until January 2006 were enrolled in the study. General follow-up rates until the age of 4 years exceed 75%. Data collection in mothers, fathers and preschool children included questionnaires, detailed physical and ultrasound examinations, behavioural observations, and biological samples. A genome wide association screen is available in the participating children. Regular detailed hands on assessment are performed from the age of 5 years onwards. Eventually, results forthcoming from the Generation R Study have to contribute to the development of strategies for optimizing health and healthcare for pregnant women and children

Transnational social networks, health, and care : a systematic narrative literature review

While transnational social ties and exchanges are a core concern within migration studies, health researchers have often overlooked their importance. Continuous and circular exchanges of information within transnational networks, also defined as social remittances, facilitate the diffusion of innovations, potentially driving contemporary social and cultural change. Influences on health, wellbeing, and care-seeking are important, but under-researched, dimensions for consideration. We undertook a systematic narrative evidence synthesis to describe the current state of knowledge in this area and to identify gaps and future directions for health researchers to take. Between April 2017 and May 2019, an iterative series of searches in Medline, Embase, PsycINFO and PubMed, plus backward and forward citation searches identified 1,173 potential papers. Screening resulted in 36 included papers, eighteen focused on migrant populations and eighteen on those who remain behind. The top three health topics were health-seeking strategies, sexual and reproductive health issues, and healthcare support. And, while not always explicitly identified, mental health and wellbeing was a further prominent, cross-cutting theme. Articles on migrant populations were all conducted in the global North and 13 out of 18 used qualitative methods. Five main themes were identified: therapeutic effect of the continuing social relationships, disrupted social relationships, hybridisation of healthcare, facilitation of connections to healthcare providers, and factors encouraging or undermining transnational social exchanges. Papers concerned with those who remain behind were mainly focused on the global South and used a mix of qualitative and quantitative approaches. Four main themes were identified: transnational transfer of health-related advice, norms, and support; associations between migrant linkages and health behaviours/outcomes; transnational collective transfer of health knowledge; and power and resistance in exchanges. Findings suggest that transnational social exchanges can both support and undermine the health of migrants and those who remain behind. This review confirms that the volume and quality of research in this area must be increased so that health policy and practice can be informed by a better understanding of these important influences on the health of both migrants and those who remain behind

TRY plant trait database – enhanced coverage and open access

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

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant 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.Peer reviewe

TRY plant trait database – enhanced coverage and open access

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

TRY plant trait database - enhanced coverage and open access

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