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

Holocene evolution of a barrier island system, Ria Formosa, South Portugal

Holocene evolution of the Ria Formosa barrier island system was studied through the examination of a large subsurface dataset acquired from 191 boreholes and five seismic refraction profiles. Two boreholes with total depths of 26 and 16.5 m were selected for a multi-proxy detailed laboratory analysis, including mean grain size distribution, organic matter (OM) content, color variation, shell identification, and benthic foraminifera assemblages. Selected cores are thought to be representative of the identified depositional sub-basins. Subsurface age data from 16 AMS C-14 dated samples were plotted against depth and resulted in a coherent age model of sedimentary infill. The system evolution was largely controlled by sediment availability, accommodation space, and Holocene sea level rise, first at a rapid rate of 7 mm/yr from 10 kcal yr BP to 7.25 kcal yr BP, followed by a slowdown to 1.1 mm/yr until present. A conceptual model for the origin and Holocene evolution of the Ria Formosa barrier island system implies three main steps, leading to the present system geomorphology: (1) marine flooding of incised palaeovalleys by the rapid transgression of palaeovalleys in the early Holocene(2) development of a proto-barrier island chain perched on Pleistocene detritic headlands and steeper interfluve areas during the early to middle Holoceneand (3) full development of the barrier islands chain and enclosing of the coastal lagoon, followed by the maturation of the system with subsequent siltation and salt marsh expansion from the middle Holocene until present. The onset of barrier system formation dates back to ca. 8 kcal yr BP, predating previously proposed age.SIHER project [PTDC/CTE-GIX112236/2009]EU Erasmus Mundus Joint Doctorate in Marine and Coastal Management (MACOMA) fellowship grant, under University of AlgarveEU Erasmus Mundus Joint Doctorate in Marine and Coastal Management (MACOMA) fellowship grant, under University of Cadi

Genome of the Avirulent Human-Infective Trypanosome—Trypanosoma rangeli

Background: Trypanosoma rangeli is a hemoflagellate protozoan parasite infecting humans and other wild and domestic mammals across Central and South America. It does not cause human disease, but it can be mistaken for the etiologic agent of Chagas disease, Trypanosoma cruzi. We have sequenced the T. rangeli genome to provide new tools for elucidating the distinct and intriguing biology of this species and the key pathways related to interaction with its arthropod and mammalian hosts.  Methodology/Principal Findings: The T. rangeli haploid genome is ,24 Mb in length, and is the smallest and least repetitive trypanosomatid genome sequenced thus far. This parasite genome has shorter subtelomeric sequences compared to those of T. cruzi and T. brucei; displays intraspecific karyotype variability and lacks minichromosomes. Of the predicted 7,613 protein coding sequences, functional annotations could be determined for 2,415, while 5,043 are hypothetical proteins, some with evidence of protein expression. 7,101 genes (93%) are shared with other trypanosomatids that infect humans. An ortholog of the dcl2 gene involved in the T. brucei RNAi pathway was found in T. rangeli, but the RNAi machinery is non-functional since the other genes in this pathway are pseudogenized. T. rangeli is highly susceptible to oxidative stress, a phenotype that may be explained by a smaller number of anti-oxidant defense enzymes and heatshock proteins.  Conclusions/Significance: Phylogenetic comparison of nuclear and mitochondrial genes indicates that T. rangeli and T. cruzi are equidistant from T. brucei. In addition to revealing new aspects of trypanosome co-evolution within the vertebrate and invertebrate hosts, comparative genomic analysis with pathogenic trypanosomatids provides valuable new information that can be further explored with the aim of developing better diagnostic tools and/or therapeutic targets

Preclinical Evidence Supporting Early Initiation of Citalopram Treatment in Machado-Joseph Disease

Spinocerebellar ataxias are dominantly inherited neurodegenerative disorders with no disease-modifying treatment. We previously identified the selective serotonin reuptake inhibitor citalopram as a safe and effective drug to be repurposed for Machado-Joseph disease. Pre-symptomatic treatment of transgenic (CMVMJD135) mice strikingly ameliorated mutant ataxin-3 (ATXN3) pathogenesis. Here, we asked whether citalopram treatment initiated at a post-symptomatic age would still show efficacy. We used a cohort of CMVMJD135 mice that shows increased phenotypic severity and faster disease progression (CMVMJD135hi) compared to the mice used in the first trial. Groups of hemizygous CMVMJD135hi mice were orally treated with citalopram. Behavior, protein analysis, and pathology assessment were performed blindly to treatment. Our results show that even when initiated after symptom onset, treatment of CMVMJD135hi mice with citalopram ameliorated motor coordination and balance, attenuating disease progression, albeit to a lesser extent than that seen with pre-symptomatic treatment initiation. There was no impact on ATXN3 aggregation, which contrasts with the robust reduction in ATXN3-positive inclusions observed in CMVMJD135 mice, when treated pre-symptomatically. Post-symptomatic treatment of CMVMJD135hi mice revealed, however, a limited neuroprotective effect by showing a tendency to repair cerebellar calbindin staining, and to increase the number of motor neurons and of NeuN-positive cells in certain brain regions. While supporting that early initiation of treatment with citalopram leads to a marked increase in efficacy, these results strengthen our previous observation that modulation of serotonergic signaling by citalopram is a promising therapeutic approach for Machado-Joseph disease even after symptom onset.European Regional Development Funds (FEDER), through the Competitiveness Factors Operational Programme (COMPETE), and by National funds, through the Foundation for Science and Technology (FCT), under the scope of the project POCI-01-0145-FEDER-007038. This article has been developed under the scope of the project NORTE-01-0145-FEDER-000013, supported by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the FEDER. This work was also supported by FCT and COMPETE through the projects [PTDC/SAU-GMG/112617/2009] (to PM) and [EXPL/BIM-MEC/0239/2012] (to AT-C), by FCT through the project [POCI-01-0145-FEDER-016818 (PTDC/NEU-NMC/3648/2014)] (to PM), by National Ataxia foundation (to PM and to AT-C), and by Ataxia UK (to PM). SE, SD-S, SO, and AT-C were supported by the FCT individual fellowships, SFRH/BD/78554/2011, SFRH/BD/78388/2011, PD/BD/127818/2016, and SFRH/BPD/102317/2014, respectively. FCT fellowships are co-financed by POPH, QREN, Governo da República Portuguesa, and EU/FSEinfo:eu-repo/semantics/publishedVersio

The Developing Human Connectome Project: a minimal processing pipeline for neonatal cortical surface reconstruction

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity