Ethnic Disparities in Early-Onset Gastric Cancer: a Population-Based Study in Texas and California

BACKGROUND: Incidence rates of gastric cancer are increasing in young adults (age \u3c50 \u3eyears), particularly among Hispanic persons. We estimated incidence rates of early-onset gastric cancer (EOGC) among Hispanic and non-Hispanic White persons by census tract poverty level and county-level metro/nonmetro residence. METHODS: We used population-based data from the California and Texas Cancer Registries from 1995 to 2016 to estimate age-adjusted incidence rates of EOGC among Hispanic and non-Hispanic White persons by year, sex, tumor stage, census tract poverty level, metro versus nonmetro county, and state. We used logistic regression models to identify factors associated with distant stage diagnosis. RESULTS: Of 3,047 persons diagnosed with EOGC, 73.2% were Hispanic White. Incidence rates were 1.29 [95% confidence interval (CI), 1.24-1.35] and 0.31 (95% CI, 0.29-0.33) per 100,000 Hispanic White and non-Hispanic White persons, respectively, with consistently higher incidence rates among Hispanic persons at all levels of poverty. There were no statistically significant associations between ethnicity and distant stage diagnosis in adjusted analysis. CONCLUSIONS: There are ethnic disparities in EOGC incidence rates that persist across poverty levels. IMPACT: EOGC incidence rates vary by ethnicity and poverty; these factors should be considered when assessing disease risk and targeting prevention efforts

Informal “Seed” Systems and the Management of Gene Flow in Traditional Agroecosystems: The Case of Cassava in Cauca, Colombia

Our ability to manage gene flow within traditional agroecosystems and their repercussions requires understanding the biology of crops, including farming practices' role in crop ecology. That these practices' effects on crop population genetics have not been quantified bespeaks lack of an appropriate analytical framework. We use a model that construes seed-management practices as part of a crop's demography to describe the dynamics of cassava (Manihot esculenta Crantz) in Cauca, Colombia. We quantify several management practices for cassava—the first estimates of their kind for a vegetatively-propagated crop—describe their demographic repercussions, and compare them to those of maize, a sexually-reproduced grain crop. We discuss the implications for gene flow, the conservation of cassava diversity, and the biosafety of vegetatively-propagated crops in centers of diversity. Cassava populations are surprisingly open and dynamic: farmers exchange germplasm across localities, particularly improved varieties, and distribute it among neighbors at extremely high rates vis-à-vis maize. This implies that a large portion of cassava populations consists of non-local germplasm, often grown in mixed stands with local varieties. Gene flow from this germplasm into local seed banks and gene pools via pollen has been documented, but its extent remains uncertain. In sum, cassava's biology and vegetative propagation might facilitate pre-release confinement of genetically-modified varieties, as expected, but simultaneously contribute to their diffusion across traditional agroecosystems if released. Genetically-modified cassava is unlikely to displace landraces or compromise their diversity; but rapid diffusion of improved germplasm and subsequent incorporation into cassava landraces, seed banks or wild populations could obstruct the tracking and eradication of deleterious transgenes. Attempts to regulate traditional farming practices to reduce the risks could compromise cassava populations' adaptive potential and ultimately prove ineffectual

Evidence confirms an anthropic origin of Amazonian Dark Earths.

Arising from: Silva et al. Nature Communications https://doi.org/10.1038/s41467-020-20184-2 (2021

Ecological Approaches to Crop Domestication

International audienc

Genetic diversity and differentiation among the species of African mahogany (Khaya spp.) based on a large SNP array

The genus Khaya includes some of the highest-value timber species in natural forests in Africa, which are under heavy exploitation pressure. Genetic identification of Khaya species is important to confirm the taxonomic classification for biodiversity conservation purposes and as a forensic tool aiding law enforcement in the fight against illegal logging. We collected samples from a total of 2222 trees belonging to five or six (depending on classification) different Khaya species (K. ivorensis, K. anthotheca/K. nyasica, K. grandifoliola, K. senegalensis, K. madagascariensis). Representative sampling was conducted over the natural ranges of all sampled Khaya species, in humid tropical forest and savanna zones. We genotyped individuals based on 101 molecular markers (67 nuclear, 11 chloroplast and 22 mitochondrial SNPs, 1 chloroplast indel). Bayesian clustering produced three main genetic groups assigning all K. ivorensis and all K. senegalensis trees, respectively, in two different clusters and all remaining individuals in a third cluster. Genetic self-assignment tests with all 101 SNPs had success rates of 97-100% for all species except for K. nyasica and K. madagascariensis, which could not be clearly distinguished from each other. A success rate for species identification nearly as high was observed using a subset of 15 highly differentiated SNPs. There was only very little evidence for hybridization among species and the vast majority (> 97%) of individuals were assigned to the same species group as identified based on morphological characters

A network-based method to detect patters of local crop biodiversity: validation at the species and infr-species levels

In this chapter, we develop new indicators and statistical tests to characterize patterns of crop diversity at local scales to better understand interactions between ecological and socio-cultural functions of agroecosystems. Farms, where a large number of crops (species or landraces) is grown, are known to contribute a large part of the locally available diversity of both rare and common crops but the role of farms with low diversity remains little understood: do they grow only common varieties—following a nestedness pattern typical of mutualistic networks in ecology—or do ‘crop–poor’ farmers also grow rare varieties? This question is pivotal in ongoing efforts to assess the local-scale contribution of small farms to global agrobiodiversity. We develop new network-based approaches to characterize the distribution of local crop diversity (species and infra-species) at the village level and to validate these approaches using meta-datasets from 10 countries. Our results highlight the sources of heterogeneity in crop diversity at the village level. We often identify two or more groups of farms based on their different levels of diversity. In some datasets, ‘crop–poor’ farms significantly contribute to the local crop diversity. Generally, we find that the distribution of crop diversity is more heterogeneous at the species than at the infra-species level. This analysis reveals the absence of a general pattern of crop diversity distribution, suggesting strong dependence on local agro-ecological and socio-cultural contexts. These different patterns of crop diversity distribution reflect an heterogeneity in farmers’ self-organized action in cultivating and maintaining local crop diversity, which ensures the adaptability of agroecosystems to global change