Predictive modeling of suitable habitats for threatened marine invertebrates and implications for conservation assessment in Brazil

Neste estudo foram utilizadas análises espaciais e ferramentas de modelagem para predizer a distribuição dos hábitats adequados aos invertebrados marinhos ameaçados e estimar a sobreposição destas áreas em relação às áreas marinhas protegidas existentes. Registros de ocorrência das espécies foram obtidos das coleções incluídas no Ocean Biogeographic Information System (OBIS-Brasil) e de dados provenientes da literatura. Dados de distribuição de 16 das 33 espécies ameaçadas, com pelo menos 10 registros de ocorrência, foram selecionados para modelagem utilizando o algoritmo Maxent (Maximum Entropy Modeling) e variáveis ambientais (temperatura, salinidade, batimetria e derivados). Os mapas resultantes foram filtrados para obtenção de áreas altamente adequadas, através de um limiar de corte de 0.5, e sobrepostos com o mapa digital de áreas protegidas. O algoritmo apresentou modelos de predição satisfatórios, mostrando que os padrões previstos no modelo são coerentes com o conhecimento atual sobre as espécies. A distribuição das áreas altamente adequadas mostrou baixa sobreposição com as áreas protegidas brasileiras. Este estudo indicou como a adequabilidade de hábitats para espécies ameaçadas pode ser realizada, utilizando aplicações em SIG e ferramentas de modelagem.Spatial analysis and modeling tools were employed to predict suitable habitat distribution for threatened marine invertebrates and estimate the overlap between highly suitable areas for these species and the Brazilian marine protected areas (MPAs). Records of the occurrence of species were obtained from the collections included in the Ocean Biogeographic Information System (OBIS-Brazil), with additional records culled from the literature. The distribution data of 16 out of 33 threatened species, with at least ten occurrences in the available records, were selected for modeling by Maxent algorithm (Maximum Entropy Modeling) based on environmental variables (temperature, salinity, bathymetry and their derivatives). The resulting maps were filtered with a fixed threshold of 0.5 (to distinguish only the highly suitable areas) and superimposed on MPA digital maps. The algorithm produced reasonable predictions of the species' potential distributions, showing that the patterns predicted by the model are largely consistent with current knowledge of the species. The distribution of the highly suitable areas showed little overlapping with Brazilian MPAs. This study showed how the habitat suitability for threatened species can be assessed using GIS applications and modeling tools

A rapid malaria appraisal in the Venezuelan Amazon

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Predicting the state of synchronization of financial time series using cross recurrence plots

Cross-correlation analysis is a powerful tool for understanding the mutual dynamics of time series. This study introduces a new method for predicting the future state of synchronization of the dynamics of two financial time series. To this end, we use the cross recurrence plot analysis as a nonlinear method for quantifying the multidimensional coupling in the time domain of two time series and for determining their state of synchronization. We adopt a deep learning framework for methodologically addressing the prediction of the synchronization state based on features extracted from dynamically sub-sampled cross recurrence plots. We provide extensive experiments on several stocks, major constituents of the S &P100 index, to empirically validate our approach. We find that the task of predicting the state of synchronization of two time series is in general rather difficult, but for certain pairs of stocks attainable with very satisfactory performance (84% F1-score, on average)

Effect of influenza-induced fever on human bioimpedance values

BACKGROUND AND AIMS: Bioelectrical impedance analysis (BIA) is a widely used technique to assess body composition and nutritional status. While bioelectrical values are affected by diverse variables, there has been little research on validation of BIA in acute illness, especially to understand prognostic significance. Here we report the use of BIA in acute febrile states induced by influenza. METHODS: Bioimpedance studies were conducted during an H1N1 influenza A outbreak in Venezuelan Amerindian villages from the Amazonas. Measurements were performed on 52 subjects between 1 and 40 years of age, and 7 children were re-examined after starting Oseltamivir treatment. Bioelectrical Impedance Vector Analysis (BIVA) and permutation tests were applied. RESULTS: For the entire sample, febrile individuals showed a tendency toward greater reactance (p=0.058) and phase angle (p=0.037) than afebrile individuals, while resistance and impedance were similar in the two groups. Individuals with repeated measurements showed significant differences in bioimpedance values associated with fever, including increased reactance (p<0.001) and phase angle (p=0.007), and decreased resistance (p=0.007) and impedance (p<0.001). CONCLUSIONS: There are bioelectrical variations induced by influenza that can be related to dehydration, with lower extracellular to intracellular water ratio in febrile individuals, or a direct thermal effect. Caution is recommended when interpreting bioimpedance results in febrile states

Characterizing SL2S galaxy groups using the Einstein radius

We analyzed the Einstein radius, $\theta_E$, in our sample of SL2S galaxy groups, and compared it with $R_A$ (the distance from the arcs to the center of the lens), using three different approaches: 1.- the velocity dispersion obtained from weak lensing assuming a Singular Isothermal Sphere profile ($\theta_{E,I}$), 2.- a strong lensing analytical method ($\theta_{E,II}$) combined with a velocity dispersion-concentration relation derived from numerical simulations designed to mimic our group sample, 3.- strong lensing modeling ($\theta_{E,III}$) of eleven groups (with four new models presented in this work) using HST and CFHT images. Finally, $R_A$ was analyzed as a function of redshift $z$ to investigate possible correlations with L, N, and the richness-to-luminosity ratio (N/L). We found a correlation between $\theta_{E}$ and $R_A$, but with large scatter. We estimate $\theta_{E,I}$ = (2.2 $\pm$ 0.9) + (0.7 $\pm$ 0.2)$R_A$, $\theta_{E,II}$ = (0.4 $\pm$ 1.5) + (1.1 $\pm$ 0.4)$R_A$, and $\theta_{E,III}$ = (0.4 $\pm$ 1.5) + (0.9 $\pm$ 0.3)$R_A$ for each method respectively. We found a weak evidence of anti-correlation between $R_A$ and $z$, with Log$R_A$ = (0.58$\pm$0.06) - (0.04$\pm$0.1)$z$, suggesting a possible evolution of the Einstein radius with $z$, as reported previously by other authors. Our results also show that $R_A$ is correlated with L and N (more luminous and richer groups have greater $R_A$), and a possible correlation between $R_A$ and the N/L ratio. Our analysis indicates that $R_A$ is correlated with $\theta_E$ in our sample, making $R_A$ useful to characterize properties like L and N (and possible N/L) in galaxy groups. Additionally, we present evidence suggesting that the Einstein radius evolves with $z$.Comment: Accepted for publication in Astronomy & Astrophysics. Typos correcte

Analysis of Croatian wild and cultivated grapevine diversity by genotyping by sequencing

Minor varieties represent a significant part of the grapevine germplasm (Vitis vinifera L. subsp. vinifera) in Croatia. During the long history of grape cultivation in insular, coastal and continental Croatia, numerous local varieties were cultivated, many of which are still used today. There are also several populations of wild grapevine (Vitis vinifera subsp. sylvestris Hegi Gmel) that have survived until the present in natural sites. Here, we developed a single primer enrichment technology (SPET) panel consisting of 61,308 probes for targeted sequencing of the V. vinifera gene space. In doing so, we examined a total of 28,092 gene models, 88.2% of all predicted genes, interrogating an average of 19 Mb nucleotides per individual genome, which corresponds to 4% of the haploid genome length. This is the first time that SPET-based sequencing has been applied to Croatian grapevine germplasm to generate multilocus genotype data of 126 cultivated accessions and 50 wild specimens. We identified 531,900 variants sites, 208,802 of which reside in coding sequences, 140,836 in introns, 118,416 in UTRs, and 63,424 in the nearby intergenic space that revealed the presence of 33 clonally propagated specimens representing both synonymies and clones within local varieties (22) as well as synonymies between local and international varieties (11), mostly from neighbouring countries. To investigate possible contribution of wild grapevine (Vitis vinifera subsp. sylvestris Hegi Gmel) to the development of present cultivars, four wild grapevine populations were included. None of the cultivated varieties showed close kinship with local wild specimens. This study opens new possibilities for studying the genetic diversity of Croatian grapevine germplasm and provides additional information with respect to SSR genotyping and phenotyping

Galaxy properties from J-PAS narrow-band photometry

We study the consistency of the physical properties of galaxies retrieved from SED-fitting as a function of spectral resolution and signal-to-noise ratio (SNR). Using a selection of physically motivated star formation histories, we set up a control sample of mock galaxy spectra representing observations of the local universe in high-resolution spectroscopy, and in 56 narrow-band and 5 broad-band photometry. We fit the SEDs at these spectral resolutions and compute their corresponding the stellar mass, the mass- and luminosity-weighted age and metallicity, and the dust extinction. We study the biases, correlations, and degeneracies affecting the retrieved parameters and explore the r\^ole of the spectral resolution and the SNR in regulating these degeneracies. We find that narrow-band photometry and spectroscopy yield similar trends in the physical properties derived, the former being considerably more precise. Using a galaxy sample from the SDSS, we compare more realistically the results obtained from high-resolution and narrow-band SEDs (synthesized from the same SDSS spectra) following the same spectral fitting procedures. We use results from the literature as a benchmark to our spectroscopic estimates and show that the prior PDFs, commonly adopted in parametric methods, may introduce biases not accounted for in a Bayesian framework. We conclude that narrow-band photometry yields the same trend in the age-metallicity relation in the literature, provided it is affected by the same biases as spectroscopy; albeit the precision achieved with the latter is generally twice as large as with the narrow-band, at SNR values typical of the different kinds of data.Comment: 26 pages, 15 figures. Accepted for publication in MNRA

Polymorphisms in Pepsinogen C and miRNA Genes Associate with High Serum Pepsinogen II in Gastric Cancer Patients

Background: Pepsinogen (PG) II (PGII) is a serological marker used to estimate the risk of gastric cancer but how PGII expression is regulated is largely unknown. It has been suggested that PGII expression, from the PGC (Progastricsin) gene, is regulated by microRNAs (miRNA), but how PGII levels vary with Helicobacter pylori (H. pylori) infection and miRNAs genotype remains unclear. Methods: Serum levels of PGI and PGII were determined in 80 patients with gastric cancer and persons at risk for gastric cancer (74 first-degree relatives of patients, 62 patients with autoimmune chronic atrophic gastritis, and 2 patients with dysplasia), with and without H. pylori infection. As control from the general population, 52 blood donors were added to the analyses. Associations between PGII levels and genetic variants in PGC and miRNA genes in these groups were explored based on H. pylori seropositivity and the risk for gastric cancer. The two-dimensional difference in gel electrophoresis (2D-DIGE) and the NanoString analysis of messenger RNA (mRNAs) from gastric cancer tissue were used to determine the pathways associated with increased PGII levels. Results: PGII levels were significantly higher in patients with gastric cancer, and in those with H. pylori infection, than in other patients or controls. A PGI/PGII ratio 3 was found better than PGI < 25 ng/mL to identify patients with gastric cancer (15.0% vs. 8.8%). For two genetic variants, namely rs8111742 in miR-Let-7e and rs121224 in miR-365b, there were significant differences in PGII levels between genotype groups among patients with gastric cancer (p = 0.02 and p = 0.01, respectively), but not among other study subjects. Moreover, a strict relation between rs9471643 C-allele with H. pylori infection and gastric cancer was underlined. Fold change in gene expression of mRNA isolated from gastric cancer tissue correlated well with polymorphism, H. pylori infection, increased PGII level, and pathway for bacteria cell entry into the host. Conclusions: Serum PGII levels depend in part on an interaction between H. pylori and host miRNA genotypes, which may interfere with the cut-off of PGI/PGII ratio used to identify persons at risk of gastric cancer. Results reported new findings regarding the relation among H. pylori, PGII-related host polymorphism, and genes involved in this interaction in the gastric cancer setting