The Utility of Genomic Variant Databases in Genetic Counseling

Organizations such as the American College of Medical Genetics (ACMG) and the National Society of Genetic Counselors (NSGC) are in agreement that public genomic data sharing will benefit patient care. Despite these recommendations, not all clinical laboratories share their variant data onto public databases. As the amount of genetic material being analyzed for patient care continues to increase, more variants of unknown significance (VUS) are reported as well. Genetic counselors need to properly interpret VUS results in order to aid patients in making educated health decisions. For this paper, genetic counselors were asked about genomic data sharing and how they handle VUS results for patients. While almost all genetic counselors agree that there is a need for genomic data sharing, only some took laboratories’ data sharing practices into account when deciding where to order testing. Genetic counselors do not have a standard way of processing VUS results; there is little consistency to how often genetic counselors look up variants in public databases or which databases they use

Comportamento do consumidor de luxo falsificado: motivações na compra de bolsas de luxo falsificadas

Este trabalho consiste em uma pesquisa sobre o consumo de bolsas de luxo falsificadas entre mulheres da classe A da cidade do Rio de Janeiro. A pesquisa tem como objetivo identificar quais os motivos que levam o consumidor a comprar produtos de luxo falsificados e mais especificamente bolsas de luxo falsificadas. Através desse estudo, será possível compreender como aspectos como qualidade e marca influenciam o consumidor em sua tomada de decisão. Esse trabalho tem como finalidade contribuir para a formulação de políticas e campanhas que visam o combate a pirataria. A metodologia utilizada foi a realização de um levantamento através de questionários autoadministrados com o público-alvo da pesquisa e algumas entrevistas informais feitas com ambulantes de rua. A consolidação dos dados foi feita via Excel e o resultado mostra que as respondentes acreditam que a redução do preço do produto original poderia gerar uma mudança de atitude dos consumidores, embora algumas delas acreditem que o fato destas bolsas terem um preço elevado é o que gera o diferencial delas

Nested singletons in molecular trees: Utility of adding morphological and geographical data from digitized herbarium specimens to test taxon concepts at species level in the case of Casearia (Salicaceae)

Using the genus Casearia, we assessed the status of nested singletons: individual specimens corresponding to accepted species but in molecular trees appearing nested within clades of closely related species. Normally, such cases would be left undecided, while on the other hand, timely taxonomic decisions are required. We argue that morphological, chorological, and ecological data can be informative to illuminate patterns of speciation. Their use can provide a first step in testing taxon concepts at species level. We focused on five cases of nested singletons in trees of the genus Casearia. We employed PCA and cluster analysis to assess phenotypic differentiation. Using geocoordinates, we calculated niche space differentiation based on 19 bioclim variables, by means of PCA and niche equivalency and similarity tests and generated dot maps. We found that the singletons were morphologically distinctive in two of the five cases (Casearia selloana and C. manausensis), relatively distinctive in two other cases (C. zizyphoides and C. mariquitensis), and partially overlapping in the last case (C. grandiflora). For two cases (C. mariquitensis and C. selloana), ecological niche space was broadly overlapping, in two cases it was found broadly nested (C. grandiflora and C. zizyphoides), and in one case narrowly nested (C. manausensis), but in no case niche differentiation was observed. Niche overlap, similarity and equivalency showed corresponding patterns. Given these data, one would interpret C. selloana and C. manausensis as presumably well-distinguished taxa, their narrow distribution ranges suggesting recently emerging lineages. The other three cases are not clearcut. Morphological data would suggest particularly C. grandiflora conspecific with C. arborea, but differences in the distribution are intriguing. Our approach would reject the notion of potential synonymy based on nested phylogenetic placement for at least two of the five cases. The other case also shows no complete lack of differentiation which would support synonymy

Character evolution and biogeography of Casearia (Salicaceae): Evidence for the South American origin of a pantropical genus and for multiple migrations to the Caribbean islands

Casearia (Salicaceae) is a pantropical genus of circa 200 species, around half of which dwell in the Neotropics. Despite the availability of phylogenetic studies that suggest that Casearia sensu Sleumer is not monophyletic, a strong phylogenetic framework was still lacking for this genus. We tested the monophyly of Casearia and examined the relationships of its species to other taxa of the tribe Samydeae, including Laetia, Samyda and Zuelania, which recently have been sunk into Casearia, as well as Euceraea, Lunania, Neoptychocarpus, Ryania and Tetrathylacium. We further put a focus on the Neotropical taxa since Casearia and allies are speciose both on the Caribbean islands and adjacent mainlands, thus providing an interesting group to address the origin of the Caribbean and Cuban flora. Our phylogenetic analyses based on four combined rapidly evolving plastid regions (petD, rpl16, rps4-trnT-L-F, trnK-matK-psbA) as well as nuclear ITS revealed Casearia as monophyletic with high support, including not only the former members of Laetia, Samyda and Zuelania but also Euceraea and Neoptychocarpus. Casearia is constituted by several major clades, mostly being entirely Neotropical, one of which exclusively comprises species endemic to the Caribbean islands. Another clade, which includes all Palaeotropical species, is nested among Neotropical lineages. Our divergence date estimates using the plastid dataset and fossil calibration points in Salicaceae indicate that the Casearia crown group started to diversify during the late Eocene, approximately 39 Ma. The stem of the Old World clade diverged from Neotropical ancestors around 27 Ma, in the Oligocene. We used BayesTraits to reconstruct the evolution of seven characters commonly used to define Casearia and allied genera. We found morphological characters, such as branched inflorescences (fasciculate, glomerulous, cymose) or uniseriate stamen series, that work well to circumscribe the genus, whereas dioecy, which was used to diagnose Neoptychocarpus, or higher stamen numbers (>12), found in Laetia and Zuelania, are homoplastic in Salicaceae, the latter character derived within Casearia from ancestors with 7–12 stamens. Pellucid dots appear to have evolved earlier than the divergence of the Casearia clade in Samydeae, and were lost in Ryania and Tetrathylacium, and thus are no synapomorphy for Casearia. In order to establish a monophyletic genus concept for Casearia, we propose to also merge Euceraea and Neoptychocarpus. Our reconstruction of ancestral areas using BioGeoBears indicate that South America is the ancestral area of Casearia. From there, multiple migrations occurred to Mesoamerica and the Caribbean islands. The Caribbean that comprises nearly all Caribbean endemics started to diversify around 9.5 Ma. Our trees depict C. corymbosa, which exhibits significant infraspecific phylogenetic structure for the sampled Mexican and Colombian individuals, as the sister to the Caribbean clade. The other clade, with Cuban endemics (C. ternstroemioides) but also Mesoamerican and South American taxa, is not sufficiently resolved internally, to allow biogeographic conclusions. The Old World clade of Casearia provides another example for a late Laurasian migration starting in the Neotropics

Assessment of Land Cover Changes in the Hinterland of Barranquilla (Colombia) Using Landsat Imagery and Logistic Regression

Barranquilla is known as a dynamically growing city in the Colombian Caribbean. Urbanisation induces land use and land cover (LULC) changes in the city and its hinterland affecting the region’s climate and biodiversity. This paper aims to identify the trends of land use and land cover changes in the hinterland of Barranquilla corresponding to 13 municipalities in the north of the Department Atlántico. Landsat TM/ETM/OLI imagery from 1985 to 2017 was used to map and analyse the spatio-temporal development of land use and land cover changes. During the investigation period, the settlement areas grew by approximately 50% (from 103.3 to 153.6 km2), while areas with woody vegetation cover experienced dynamic changes and increased in size since 2001. Peri-urban and rural areas were characterized by highly dynamic changes, particularly regarding clearing and recovery of vegetated areas. Regression analyses were performed to identify the impact factors of detected vegetation cover changes. Computed logistic regression models included 20 independent variables, such as relief, climate, soil, proximity characteristics and socio-economic data. The results of this study may act as a basis to enable researchers and decision-makers to focus on the most important signals of systematic landscape transformations and on the conservation of ecosystems and the services they provide

Seeing the wood despite the trees: Exploring human disturbance impact on plant diversity, community structure, and standing biomass in fragmented high Andean forests

High Andean forests harbor a remarkably high biodiversity and play a key role in providing vital ecosystem services for neighboring cities and settlements. However, they are among the most fragmented and threatened ecosystems in the neotropics. To preserve their unique biodiversity, a deeper understanding of the effects of anthropogenic perturbations on them is urgently needed. Here, we characterized the plant communities of high Andean forest remnants in the hinterland of Bogota in 32 0.04 ha plots. We assessed the woody vegetation and sampled the understory and epiphytic cover. We gathered data on compositional and structural parameters and compiled a broad array of variables related to anthropogenic disturbance, ranging from local to landscape-wide metrics. We also assessed phylogenetic diversity and functional diversity. We employed nonmetric multidimensional scaling (NMDS) to select meaningful variables in a first step of the analysis. Then, we performed partial redundancy analysis (pRDA) and generalized linear models (GLMs) in order to test how selected environmental and anthropogenic variables are affecting the composition, diversity, and aboveground biomass of these forests. Identified woody vegetation and understory layer communities were characterized by differences in elevation, temperature, and relative humidity, but were also related to different levels of human influence. We found that the increase of human-related disturbance resulted in less phylogenetic diversity and in the phylogenetic clustering of the woody vegetation and in lower aboveground biomass (AGB) values. As to the understory, disturbance was associated with a higher diversity, jointly with a higher phylogenetic dispersion. The most relevant disturbance predictors identified here were as follows: edge effect, proximity of cattle, minimum fragment age, and median patch size. Interestingly, AGB was efficiently predicted by the proportion of late successional species. We therefore recommend the use of AGB and abundance of late successional species as indicators of human disturbance on high Andean forests

Efficiently analyzing large patient registries with Bayesian joint models for longitudinal and time-to-event data

The joint modeling of longitudinal and time-to-event outcomes has become a popular tool infollow-up studies. However, fitting Bayesian joint models to large datasets, such as patientregistries, can require extended computing times. To speed up sampling, we divided a patient registry dataset into subsamples, analyzed them in parallel, and combined the resultingMarkov chain Monte Carlo draws into a consensus distribution. We used a simulation studyto investigate how different consensus strategies perform with joint models. In particular,we compared grouping all draws together with using equal- and precision-weighted averages.We considered scenarios reflecting different sample sizes, numbers of data splits, and processor characteristics. Parallelization of the sampling process substantially decreased the timerequired to run the model. We found that the weighted-average consensus distributions forlarge sample sizes were nearly identical to the target posterior distribution. The proposedalgorithm has been made available in an R package for joint models, JMbayes2. This workwas motivated by the clinical interest in investigating the association between ppFEV1, acommonly measured marker of lung function, and the risk of lung transplant or death, using data from the US Cystic Fibrosis Foundation Patient Registry (35,153 individuals with372,366 years of cumulative follow-up). Splitting the registry into five subsamples resultedin an 85% decrease in computing time, from 9.22 to 1.39 hours. Splitting the data and finding a consensus distribution by precision-weighted averaging proved to be a computationallyefficient and robust approach to handling large datasets under the joint modeling framework

Air pollution, epigenetics, and asthma

Exposure to traffic-related air pollution (TRAP) has been implicated in asthma development, persistence, and exacerbation. This exposure is highly significant as large segments of the global population resides in zones that are most impacted by TRAP and schools are often located in high TRAP exposure areas. Recent findings shed new light on the epigenetic mechanisms by which exposure to traffic pollution may contribute to the development and persistence of asthma. In order to delineate TRAP induced effects on the epigenome, utilization of newly available innovative methods to assess and quantify traffic pollution will be needed to accurately quantify exposure. This review will summarize the most recent findings in each of these areas. Although there is considerable evidence that TRAP plays a role in asthma, heterogeneity in both the definitions of TRAP exposure and asthma outcomes has led to confusion in the field. Novel information regarding molecular characterization of asthma phenotypes, TRAP exposure assessment methods, and epigenetics are revolutionizing the field. Application of these new findings will accelerate the field and the development of new strategies for interventions to combat TRAP-induced asthma

Efficiently analyzing large patient registries with Bayesian joint models for longitudinal and time-to-event data

The joint modeling of longitudinal and time-to-event outcomes has become a popular tool infollow-up studies. However, fitting Bayesian joint models to large datasets, such as patientregistries, can require extended computing times. To speed up sampling, we divided a patient registry dataset into subsamples, analyzed them in parallel, and combined the resultingMarkov chain Monte Carlo draws into a consensus distribution. We used a simulation studyto investigate how different consensus strategies perform with joint models. In particular,we compared grouping all draws together with using equal- and precision-weighted averages.We considered scenarios reflecting different sample sizes, numbers of data splits, and processor characteristics. Parallelization of the sampling process substantially decreased the timerequired to run the model. We found that the weighted-average consensus distributions forlarge sample sizes were nearly identical to the target posterior distribution. The proposedalgorithm has been made available in an R package for joint models, JMbayes2. This workwas motivated by the clinical interest in investigating the association between ppFEV1, acommonly measured marker of lung function, and the risk of lung transplant or death, using data from the US Cystic Fibrosis Foundation Patient Registry (35,153 individuals with372,366 years of cumulative follow-up). Splitting the registry into five subsamples resultedin an 85% decrease in computing time, from 9.22 to 1.39 hours. Splitting the data and finding a consensus distribution by precision-weighted averaging proved to be a computationallyefficient and robust approach to handling large datasets under the joint modeling framework