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IntroductionChagas disease is caused by theTrypanosoma cruziinfection. It is a neglected tropical disease with considerable impact on the physical, psychological, familiar, and social spheres. The Valle Alto of Cochabamba is a hyperendemic region of Bolivia where efforts to control the transmission of the disease have progressed over the years. However, many challenges remain, above all, timely detection and health-care access.MethodsFollowing the Science Shop process, this bottom-up research emerged with the participation of the civil society from Valle Alto and representatives of the Association ofCorazones Unidos por el Chagasfrom Cochabamba. The aim of this study is to explore the social determinants in the living realities of those affected by Chagas disease or the silent infection and how families in the Valle Alto of Cochabamba cope with it. An interdisciplinary research team conducted a case study of the life stories of three families using information from in-depth interviews and performed a descriptive qualitative content analysis and triangulation processes.FindingsFindings provide insights into social circumstances of the research subjects’ lives; particularly, on how exposure toTrypanosoma cruziinfection affects their daily lives in terms of seeking comprehensive health care. Research subjects revealed needs and shared their experiences, thus providing an understanding of the complexity of Chagas disease from the socioeconomic, sociocultural, political, and biomedical perspectives. Results enlighten on three dimensions: structural, psychosocial, and plural health system. The diverse perceptions and attitudes toward Chagas within families, including the denial of its existence, are remarkable as gender and ethnocultural aspects. Findings support recommendations to various stakeholders and translation materials.ConclusionsIntersectional disease management and community involvement are essential for deciding the most appropriate and effective actions. Education, detection, health care, and social programs engaging family units ought to be the pillars of a promising approach.

Motivation: Trait variation within species can reveal plastic and/or genetic responses to environmental gradients, and may indicate where local adaptation has occurred. Here, we present a dataset of rangewide variation in leaf traits from seven of the most ecologically and economically important tree species in Europe. Sample collection and trait assessment are embedded in the GenTree project (EU‐Horizon 2020), which aims at characterizing the genetic and phenotypic variability of forest tree species to optimize the management and sustainable use of forest genetic resources. Our dataset captures substantial intra‐ and interspecific leaf phenotypic variability, and provides valuable information for studying the relationship between ecosystem functioning and trait variability of individuals, and the response and resilience of species to environmental changes. Main types of variable contained: We chose morphological and chemical characters linked to trade‐offs between acquisition and conservation of resources and water use, namely specific leaf area, leaf size, carbon and nitrogen content and their ratio, and the isotopic signature of stable isotope ¹³C and ¹⁵N in leaves. Spatial location and grain: We surveyed between 18 and 22 populations per species, 141 in total, across Europe. Time period: Leaf sampling took place between 2016 and 2017. Major taxa and level of measurement: We sampled at least 25 individuals in each population, 3,569 trees in total, and measured traits in 35,755 leaves from seven European tree species, i.e. the conifers Picea abies, Pinus pinaster and Pinus sylvestris, and the broadleaves Betula pendula, Fagus sylvatica, Populus nigra and Quercus petraea. Software format: The data files are in ASCII text, tab delimited, not compressed.

Trees play a key role in the structure and function of many ecosystems worldwide. In the Mediterranean Basin, forests cover approximately 22% of the total land area hosting a large number of endemics (46 species). Despite its particularities and vulnerability, the biodiversity of Mediterranean trees is not well known at the taxonomic, spatial, functional, and genetic levels required for conservation applications. The WOODIV database fills this gap by providing reliable occurrences, four functional traits (plant height, seed mass, wood density, and specific leaf area), and sequences from three DNA-regions (rbcL, matK, and trnH-psbA), together with modelled occurrences and a phylogeny for all 210 Euro-Mediterranean tree species. We compiled, homogenized, and verified occurrence data from sparse datasets and collated them on an INSPIRE-compliant 10 × 10 km grid. We also gathered functional trait and genetic data, filling existing gaps where possible. The WOODIV database can benefit macroecological studies in the fields of conservation, biogeography, and community ecology.

Background: Progress in the field of evolutionary forest ecology has been hampered by the huge challenge of phenotyping trees across their ranges in their natural environments, and the limitation in high-resolution environmental information. Findings: The GenTree Platform contains phenotypic and environmental data from 4,959 trees from 12 ecologically and economically important European forest tree species: Abies alba Mill. (silver fir), Betula pendula Roth. (silver birch), Fagus sylvatica L. (European beech), Picea abies (L.) H. Karst (Norway spruce), Pinus cembra L. (Swiss stone pine), Pinus halepensis Mill. (Aleppo pine), Pinus nigra Arnold (European black pine), Pinus pinaster Aiton (maritime pine), Pinus sylvestris L. (Scots pine), Populus nigra L. (European black poplar), Taxus baccata L. (English yew), and Quercus petraea (Matt.) Liebl. (sessile oak). Phenotypic (height, diameter at breast height, crown size, bark thickness, biomass, straightness, forking, branch angle, fructification), regeneration, environmental in situ measurements (soil depth, vegetation cover, competition indices), and environmental modeling data extracted by using bilinear interpolation accounting for surrounding conditions of each tree (precipitation, temperature, insolation, drought indices) were obtained from trees in 194 sites covering the species’ geographic ranges and reflecting local environmental gradients. Conclusions: The GenTree Platform is a new resource for investigating ecological and evolutionary processes in forest trees. The coherent phenotyping and environmental characterization across 12 species in their European ranges allow for a wide range of analyses from forest ecologists, conservationists, and macro-ecologists. Also, the data here presented can be linked to the GenTree Dendroecological collection, the GenTree Leaf Trait collection, and the GenTree Genomic collection presented elsewhere, which together build the largest evolutionary forest ecology data collection available.

In multiple myeloma, novel treatments with proteasome inhibitors (PIs) and immunomodulatory agents (IMiDs) have prolonged survival but the disease remains incurable. At relapse, next-generation sequencing has shown occasional mutations of drug targets but has failed to identify unifying features that underlie chemotherapy resistance. We studied 42 patients refractory to both PIs and IMiDs. Whole-exome sequencing was performed in 40 patients, and RNA sequencing (RNA-seq) was performed in 27. We found more mutations than were reported at diagnosis and more subclonal mutations, which implies ongoing evolution of the genome of myeloma cells during treatment. The mutational landscape was different from that described in published studies on samples taken at diagnosis. The TP53 pathway was the most frequently inactivated (in 45% of patients). Conversely, point mutations of genes associated with resistance to IMiDs were rare and were always subclonal. Refractory patients were uniquely characterized by having a mutational signature linked to exposure to alkylating agents, whose role in chemotherapy resistance and disease progression remains to be elucidated. RNA-seq analysis showed that treatment or mutations had no influence on clustering, which was instead influenced by karyotypic events. We describe a cluster with both amp(1q) and del(13) characterized by CCND2 upregulation and also overexpression of MCL1, which represents a novel target for experimental treatments. Overall, high-risk features were found in 65% of patients. However, only amp(1q) predicted survival. Gene mutations of IMiD and PI targets are not a preferred mode of drug resistance in myeloma. Chemotherapy resistance of the bulk tumor population is likely attained through differential, yet converging evolution of subclones that are overall variable from patient to patient and within the same patient. © 2020 by The American Society of Hematology.