Uptake and depuration of gold nanoparticles in Daphnia magna

This study presents a series of short-term studies (total duration 48 h) of uptake and depuration of engineered nanoparticles (ENP) in neonate Daphnia magna. Gold nanoparticles (Au NP) were used to study the influence of size, stabilizing agent and feeding on uptake and depuration kinetics and animal body burdens. 10 and 30 nm Au NP with different stabilizing agents [citrate (CIT) and mercaptoundecanoic acid (MUDA)] were tested in concentrations around 0.5 mg Au/L. Fast initial uptake was observed for all studied Au NP, with CIT stabilized Au NP showing similar rates independent of size and MUDA showing increased uptake for the smaller Au NP (MUDA 10 nm > CIT 10 nm, 30 nm > MUDA 30 nm). However, upon transfer to clean media no clear trend on depuration rates was found in terms of stabilizing agent or size. Independent of stabilizing agent, 10 nm Au NP resulted in higher residual whole-animal body burdens after 24 h depuration than 30 nm Au NP with residual body burdens about one order of magnitude higher of animals exposed to 10 nm Au NP. The presence of food (P. subcapitata) did not significantly affect the body burden after 24 h of exposure, but depuration was increased. While food addition is not necessary to ensure D. magna survival in the presented short-term test design, the influence of food on uptake and depuration kinetics is essential to consider in long term studies of ENP where food addition is necessary. This study demonstrates the feasibility of a short-term test design to assess the uptake and depuration of ENP in D. magna. The findings underlines that the assumptions behind the traditional way of quantifying bioconcentration are not fulfilled when ENPs are studied.Peer reviewed: YesNRC publication: Ye

Isolation and Biophysical Characterisation of Bioactive Polysaccharides from Cucurbita Moschata (Butternut Squash)

Cucurbits are plants that have been used frequently as functional foods. This study includes the extraction, isolation, and characterisation of the mesocarp polysaccharide of Cucurbita moschata. The polysaccharide component was purified by gel filtration into three fractions (NJBTF1, NJBTF2, and NJBTF3) of different molecular weights. Characterisation includes the hydrodynamic properties, identification of monosaccharide composition, and bioactivity. Sedimentation velocity also indicated the presence of small amounts of additional discrete higher molecular weight components even after fractionation. Sedimentation equilibrium revealed respective weight average molecular weights of 90, 31, and 19 kDa, with the higher fractions (NJBTF1 and NJBTF2) indicating a tendency to self-associate. Based on the limited amount of data (combinations of 3 sets of viscosity and sedimentation data corresponding to the 3 fractions), HYDFIT indicates an extended, semi-flexible coil conformation. Of all the fractions obtained, NJBTF1 showed the highest bioactivity. All fractions contained galacturonic acid and variable amounts of neutral sugars. To probe further, the extent of glycosidic linkages in NJBTF1 was estimated using gas chromatography–mass spectrometry (GCMS), yielding a high galacturonic acid content (for pectin polysaccharide) and the presence of fructans—the first evidence of fructans (levan) in the mesocarp. Our understanding of the size and structural flexibility together with the high bioactivity suggests that the polysaccharide obtained from C. moschata has the potential to be developed into a therapeutic agent

Animal model integration to AutDB, a genetic database for autism

<p>Abstract</p> <p>Background</p> <p>In the post-genomic era, multi-faceted research on complex disorders such as autism has generated diverse types of molecular information related to its pathogenesis. The rapid accumulation of putative candidate genes/loci for Autism Spectrum Disorders (ASD) and ASD-related animal models poses a major challenge for systematic analysis of their content. We previously created the Autism Database (AutDB) to provide a publicly available web portal for ongoing collection, manual annotation, and visualization of genes linked to ASD. Here, we describe the design, development, and integration of a new module within AutDB for ongoing collection and comprehensive cataloguing of ASD-related animal models.</p> <p>Description</p> <p>As with the original AutDB, all data is extracted from published, peer-reviewed scientific literature. Animal models are annotated with a new standardized vocabulary of phenotypic terms developed by our researchers which is designed to reflect the diverse clinical manifestations of ASD. The new Animal Model module is seamlessly integrated to AutDB for dissemination of diverse information related to ASD. Animal model entries within the new module are linked to corresponding candidate genes in the original "Human Gene" module of the resource, thereby allowing for cross-modal navigation between gene models and human gene studies. Although the current release of the Animal Model module is restricted to mouse models, it was designed with an expandable framework which can easily incorporate additional species and non-genetic etiological models of autism in the future.</p> <p>Conclusions</p> <p>Importantly, this modular ASD database provides a platform from which data mining, bioinformatics, and/or computational biology strategies may be adopted to develop predictive disease models that may offer further insights into the molecular underpinnings of this disorder. It also serves as a general model for disease-driven databases curating phenotypic characteristics of corresponding animal models.</p

A Brain Region-Specific Predictive Gene Map for Autism Derived by Profiling a Reference Gene Set

Molecular underpinnings of complex psychiatric disorders such as autism spectrum disorders (ASD) remain largely unresolved. Increasingly, structural variations in discrete chromosomal loci are implicated in ASD, expanding the search space for its disease etiology. We exploited the high genetic heterogeneity of ASD to derive a predictive map of candidate genes by an integrated bioinformatics approach. Using a reference set of 84 Rare and Syndromic candidate ASD genes (AutRef84), we built a composite reference profile based on both functional and expression analyses. First, we created a functional profile of AutRef84 by performing Gene Ontology (GO) enrichment analysis which encompassed three main areas: 1) neurogenesis/projection, 2) cell adhesion, and 3) ion channel activity. Second, we constructed an expression profile of AutRef84 by conducting DAVID analysis which found enrichment in brain regions critical for sensory information processing (olfactory bulb, occipital lobe), executive function (prefrontal cortex), and hormone secretion (pituitary). Disease specificity of this dual AutRef84 profile was demonstrated by comparative analysis with control, diabetes, and non-specific gene sets. We then screened the human genome with the dual AutRef84 profile to derive a set of 460 potential ASD candidate genes. Importantly, the power of our predictive gene map was demonstrated by capturing 18 existing ASD-associated genes which were not part of the AutRef84 input dataset. The remaining 442 genes are entirely novel putative ASD risk genes. Together, we used a composite ASD reference profile to generate a predictive map of novel ASD candidate genes which should be prioritized for future research

Animal keeping in Chalcolithic North-Central Anatolia:What can stable isotope analysis add?

Stable isotope analysis is an essential investigative technique, complementary to more traditional zooarchaeological approaches to elucidating animal keeping practices. Carbon (δ13C) and nitrogen (δ15N) stable isotope values of 132 domesticates (cattle, caprines and pigs) were evaluated to investigate one aspect of animal keeping, animal forage, at the Late Chalcolithic (mid-fourth millennium BC) site of Çamlıbel Tarlası, which is located in north-central Anatolia. The analyses indicated that all of the domesticates had diets based predominantly on C3 plants. Pig and caprine δ13C and δ15N values were found to be statistically indistinguishable. However, cattle exhibited distinctive stable isotope values and, therefore, differences in diet from both pigs and caprines at Çamlıbel Tarlası. This difference may relate to the distinct patterns of foraging behaviour exhibited by the domesticates. Alternatively, this diversity may result from the use of different grazing areas or from the foddering practices of the Çamlıbel Tarlası inhabitants

Euclid preparation XLIV. Modelling spectroscopic clustering on mildly nonlinear scales in beyond-ΛCDM models

Context. The Euclid space satellite mission will measure the large-scale clustering of galaxies at an unprecedented precision, providing a unique probe of modifications to the ΛCDM model. // Aims. We investigated the approximations needed to efficiently predict the large-scale clustering of matter and dark matter halos in the context of modified gravity and exotic dark energy scenarios. We examined the normal branch of the Dvali–Gabadadze–Porrati model, the Hu–Sawicki f(R) model, a slowly evolving dark energy model, an interacting dark energy model, and massive neutrinos. For each, we tested approximations for the perturbative kernel calculations, including the omission of screening terms and the use of perturbative kernels based on the Einstein–de Sitter universe; we explored different infrared-resummation schemes, tracer bias models and a linear treatment of massive neutrinos; we investigated various approaches for dealing with redshift-space distortions and modelling the mildly nonlinear scales, namely the Taruya–Nishimishi–Saito prescription and the effective field theory of large-scale structure. This work provides a first validation of the various codes being considered by Euclid for the spectroscopic clustering probe in beyond-ΛCDM scenarios. // Methods. We calculated and compared the χ2 statistic to assess the different modelling choices. This was done by fitting the spectroscopic clustering predictions to measurements from numerical simulations and perturbation theory-based mock data. We compared the behaviour of this statistic in the beyond-ΛCDM cases, as a function of the maximum scale included in the fit, to the baseline ΛCDM case. // Results. We find that the Einstein–de Sitter approximation without screening is surprisingly accurate for the modified gravity cases when comparing to the halo clustering monopole and quadrupole obtained from simulations and mock data. Further, we find the same goodness-of-fit for both cases – the one including and the one omitting non-standard physics in the predictions. Our results suggest that the inclusion of multiple redshift bins, higher-order multipoles, higher-order clustering statistics (such as the bispectrum), and photometric probes such as weak lensing, will be essential to extract information on massive neutrinos, modified gravity and dark energy. Additionally, we show that the three codes used in our analysis, namely, PBJ, Pybird and MG-Copter, exhibit sub-percent agreement for k ≤ 0.5 h Mpc−1 across all the models. This consistency underscores their value as reliable tools

Spontaneous Breathing in Early Acute Respiratory Distress Syndrome: Insights From the Large Observational Study to UNderstand the Global Impact of Severe Acute Respiratory FailurE Study

OBJECTIVES: To describe the characteristics and outcomes of patients with acute respiratory distress syndrome with or without spontaneous breathing and to investigate whether the effects of spontaneous breathing on outcome depend on acute respiratory distress syndrome severity. DESIGN: Planned secondary analysis of a prospective, observational, multicentre cohort study. SETTING: International sample of 459 ICUs from 50 countries. PATIENTS: Patients with acute respiratory distress syndrome and at least 2 days of invasive mechanical ventilation and available data for the mode of mechanical ventilation and respiratory rate for the 2 first days. INTERVENTIONS: Analysis of patients with and without spontaneous breathing, defined by the mode of mechanical ventilation and by actual respiratory rate compared with set respiratory rate during the first 48 hours of mechanical ventilation. MEASUREMENTS AND MAIN RESULTS: Spontaneous breathing was present in 67% of patients with mild acute respiratory distress syndrome, 58% of patients with moderate acute respiratory distress syndrome, and 46% of patients with severe acute respiratory distress syndrome. Patients with spontaneous breathing were older and had lower acute respiratory distress syndrome severity, Sequential Organ Failure Assessment scores, ICU and hospital mortality, and were less likely to be diagnosed with acute respiratory distress syndrome by clinicians. In adjusted analysis, spontaneous breathing during the first 2 days was not associated with an effect on ICU or hospital mortality (33% vs 37%; odds ratio, 1.18 [0.92-1.51]; p = 0.19 and 37% vs 41%; odds ratio, 1.18 [0.93-1.50]; p = 0.196, respectively ). Spontaneous breathing was associated with increased ventilator-free days (13 [0-22] vs 8 [0-20]; p = 0.014) and shorter duration of ICU stay (11 [6-20] vs 12 [7-22]; p = 0.04). CONCLUSIONS: Spontaneous breathing is common in patients with acute respiratory distress syndrome during the first 48 hours of mechanical ventilation. Spontaneous breathing is not associated with worse outcomes and may hasten liberation from the ventilator and from ICU. Although these results support the use of spontaneous breathing in patients with acute respiratory distress syndrome independent of acute respiratory distress syndrome severity, the use of controlled ventilation indicates a bias toward use in patients with higher disease severity. In addition, because the lack of reliable data on inspiratory effort in our study, prospective studies incorporating the magnitude of inspiratory effort and adjusting for all potential severity confounders are required

Identifying associations between diabetes and acute respiratory distress syndrome in patients with acute hypoxemic respiratory failure: an analysis of the LUNG SAFE database

Background: Diabetes mellitus is a common co-existing disease in the critically ill. Diabetes mellitus may reduce the risk of acute respiratory distress syndrome (ARDS), but data from previous studies are conflicting. The objective of this study was to evaluate associations between pre-existing diabetes mellitus and ARDS in critically ill patients with acute hypoxemic respiratory failure (AHRF). Methods: An ancillary analysis of a global, multi-centre prospective observational study (LUNG SAFE) was undertaken. LUNG SAFE evaluated all patients admitted to an intensive care unit (ICU) over a 4-week period, that required mechanical ventilation and met AHRF criteria. Patients who had their AHRF fully explained by cardiac failure were excluded. Important clinical characteristics were included in a stepwise selection approach (forward and backward selection combined with a significance level of 0.05) to identify a set of independent variables associated with having ARDS at any time, developing ARDS (defined as ARDS occurring after day 2 from meeting AHRF criteria) and with hospital mortality. Furthermore, propensity score analysis was undertaken to account for the differences in baseline characteristics between patients with and without diabetes mellitus, and the association between diabetes mellitus and outcomes of interest was assessed on matched samples. Results: Of the 4107 patients with AHRF included in this study, 3022 (73.6%) patients fulfilled ARDS criteria at admission or developed ARDS during their ICU stay. Diabetes mellitus was a pre-existing co-morbidity in 913 patients (22.2% of patients with AHRF). In multivariable analysis, there was no association between diabetes mellitus and having ARDS (OR 0.93 (0.78-1.11); p = 0.39), developing ARDS late (OR 0.79 (0.54-1.15); p = 0.22), or hospital mortality in patients with ARDS (1.15 (0.93-1.42); p = 0.19). In a matched sample of patients, there was no association between diabetes mellitus and outcomes of interest. Conclusions: In a large, global observational study of patients with AHRF, no association was found between diabetes mellitus and having ARDS, developing ARDS, or outcomes from ARDS. Trial registration: NCT02010073. Registered on 12 December 2013

Euclid : I. Overview of the Euclid mission

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015–2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14 000 deg2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance