Assessing the Health of Richibucto Estuary with the Latent Health Factor Index

The ability to quantitatively assess the health of an ecosystem is often of great interest to those tasked with monitoring and conserving ecosystems. For decades, research in this area has relied upon multimetric indices of various forms. Although indices may be numbers, many are constructed based on procedures that are highly qualitative in nature, thus limiting the quantitative rigour of the practical interpretations made from these indices. The statistical modelling approach to construct the latent health factor index (LHFI) was recently developed to express ecological data, collected to construct conventional multimetric health indices, in a rigorous quantitative model that integrates qualitative features of ecosystem health and preconceived ecological relationships among such features. This hierarchical modelling approach allows (a) statistical inference of health for observed sites and (b) prediction of health for unobserved sites, all accompanied by formal uncertainty statements. Thus far, the LHFI approach has been demonstrated and validated on freshwater ecosystems. The goal of this paper is to adapt this approach to modelling estuarine ecosystem health, particularly that of the previously unassessed system in Richibucto in New Brunswick, Canada. Field data correspond to biotic health metrics that constitute the AZTI marine biotic index (AMBI) and abiotic predictors preconceived to influence biota. We also briefly discuss related LHFI research involving additional metrics that form the infaunal trophic index (ITI). Our paper is the first to construct a scientifically sensible model to rigorously identify the collective explanatory capacity of salinity, distance downstream, channel depth, and silt-clay content --- all regarded a priori as qualitatively important abiotic drivers --- towards site health in the Richibucto ecosystem.Comment: On 2013-05-01, a revised version of this article was accepted for publication in PLoS One. See Journal reference and DOI belo

Determination of βS haplotypes in patients with sickle-cell anemia in the state of Rio Grande do Norte, Brazil

βS haplotypes were studied in 47 non-related patients with sickle-cell anemia from the state of Rio Grande do Norte, Brazil. Molecular analysis was conducted by PCR/RFLP using restriction endonucleases XmnI, HindIII, HincII and HinfI to analyze six polymorphic sites from the beta cluster. Twenty-seven patients (57.5%) were identified with genotype CAR/CAR, 9 (19.1%) CAR/BEN, 6 (12.8%) CAR/CAM, 1 (2.1%) BEN/BEN, 2 (4.3%) CAR/Atp, 1 (2.1%) BEN/Atp and 1 (2.1%) with genotype Atp/Atp. The greater frequency of Cameroon haplotypes compared to other Brazilian states suggests the existence of a peculiarity of African origin in the state of Rio Grande do Norte

Stress-induced c-Fos expression is differentially modulated by dexamethasone, diazepam and imipramine

Immobilization stress upregulates c-Fos expression in several CNS areas. Repeated stress or the use of drugs can modulate stress-induced c-Fos expression. Here, we investigated in 40 different areas of the rat brain the effects of dexamethasone (SDX, a synthetic glucocorticoid), diazepam (SBDZ, a benzodiazepine), and imipramine (IMI, an antidepressant) on the c-Fos expression induced by restraint stress. Wistar rats were divided into four groups and submitted to 20 days of daily injection of saline (three first groups) or imipramine, 15 mg/kg, i.p. On day 21, animals were submitted to injections of saline (somatosensory, SS), SDX (1 mg/kg, i.p.), SBDZ (5 mg/kg, i.p.), or IMI (15 mg/kg, i.p.) before being submitted to restraint. Immediately after stress, the animals were perfused and their brains processed with immunohistochemistry for c-Fos (Ab-5 Oncogene Science). Dexamethasone reduced stress- induced c-Fos expression in SS cortex, hippocampus, paraventricular nucleus of the hypothalamus (PVH), and locus coeruleus (LC), whereas diazepam reduced c-Fos staining in the SS cortex, hippocampus, bed nucleus of stria terminalis, septal area, and hypothalamus (preoptic area and supramammillary nucleus). Chronic administration of imipramine decreased staining in the hippocampus, PVH, and LC, while increasing it in the nucleus raphe pallidus. We conclude that dexamethasone, diazepam and imipramine differentially modulate stress-induced Fos expression. the present study provides an important comparative background that may help in the further understanding of the effects of these compounds and on the brain activation as well as on the behavioral, neuroendocrine, and autonomic responses to stress.UFRRJ, Dept Physiol Sci, BR-23890000 Rio de Janeiro, BrazilUniversidade Federal de São Paulo, Dept Physiol, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Psychobiol, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Physiol, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Psychobiol, São Paulo, BrazilWeb of Scienc

Genome-Wide Linkage Scan of a Pedigree with Familial Hypercholesterolemia Suggests Susceptibility Loci on Chromosomes 3q25-26 and 21q22

BACKGROUND: Familial hypercholesterolemia (FH) is a heritable disorder that can increase the risk of premature coronary heart disease. Studies suggest there are substantial genetic heterogeneities for different populations. Here we tried to identify novel susceptibility loci for FH in a Chinese pedigree. METHODOLOGY/PRINCIPAL FINDINGS: We performed a SNP-based genome-wide linkage scan with the Chinese FH pedigree. Two suggestive linkage loci not previously reported were identified on chromosomes 3q25.1-26.1 (NPL = 9.01, nominal P<0.00001, and simulated occurrence per genome scan = 1.08) and 21q22.3 (NPL = 8.95, nominal P<0.00001, and simulated occurrence per genome scan = 1.26). In the interaction analysis with a trimmed version of the pedigree, we obtained a significantly increased joint LOD score (2.70) compared with that obtained when assuming the two loci uncorrelated, suggesting that more than one locus was involved in this pedigree. Exon screening of two candidate genes ABCG1 and LSS from one of the suggestive region 21q22 didn't report any causative mutations. CONCLUSIONS/SIGNIFICANCES: These results confirm complex etiologies and suggest new genetic casual factors for the FH disorder. Further study of the two candidate regions is advocated

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