Are Food Animals Responsible for Transfer of Antimicrobial-Resistant Escherichia coli or Their Resistance Determinants to Human Populations?:A Systematic Review

The role of farm animals in the emergence and dissemination of both AMR bacteria and their resistance determinants to humans is poorly understood and controversial. Here, we systematically reviewed the current evidence that food animals are responsible for transfer of AMR to humans. We searched PubMed, Web of Science, and EMBASE for literature published between 1940 and 2016. Our results show that eight studies (18%) suggested evidence of transmission of AMR from food animals to humans, 25 studies (56%) suggested transmission between animals and humans with no direction specified and 12 studies (26%) did not support transmission. Quality of evidence was variable among the included studies; one study (2%) used high resolution typing tools, 36 (80%) used intermediate resolution typing tools, six (13%) relied on low resolution typing tools, and two (5%) based conclusions on co-occurrence of resistance. While some studies suggested to provide evidence that transmission of AMR from food animals to humans may occur, robust conclusions on the directionality of transmission cannot be drawn due to limitations in study methodologies. Our findings highlight the need to combine high resolution genomic data analysis with systematically collected epidemiological evidence to reconstruct patterns of AMR transmission between food animals and humans

Virtual Ontogeny of Cortical Growth Preceding Mental Illness

Background: Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life. Methods: Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed. Results: Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth. Conclusions: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy

Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group.

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47-67.00, ROC-AUC = 71.49%, 95% CI = 69.39-73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70-60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen's Kappa = 0.83, 95% CI = 0.829-0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data

Subcortical volumes across the lifespan: data from 18,605 healthy individuals aged 3-90 years

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.Education and Child Studie

High genetic differentiation and cross-shelf patterns of genetic diversity among Great Barrier Reef populations of Symbiodinium

The resilience of Symbiodinium harboured by corals is dependent on the genetic diversity and extent of connectivity among reef populations. This study presents\ud genetic analyses of Great Barrier Reef (GBR) populations\ud of clade C Symbiodinium hosted by the alcyonacean coral,\ud Sinularia Xexibilis. Allelic variation at four newly developed microsatellite loci demonstrated that Symbiodinium\ud populations are genetically diVerentiated at all spatial\ud scales from 16 to 1,360 km (pairwise ST = 0.01–0.47,\ud mean = 0.22); the only exception being two neighbouring\ud populations in the Cairns region separated by 17 km. This\ud indicates that gene Xow is restricted for Symbiodinium C\ud hosted by S. Xexibilis on the GBR. Patterns of population\ud structure reXect longshore circulation patterns and limited cross-shelf mixing, suggesting that passive transport by currents is the primary mechanism of dispersal in Symbiodinium types that are acquired horizontally. There\ud was no correlation between the genetic structure of Symbiodinium populations and their host S. Xexibilis, most likely because diVerent factors aVect the dispersal and recruitment of each partner in the symbiosis. The genetic diversity of these Symbiodinium reef populations is on average 1.5 times lower on inshore reefs than on oVshore reefs. Lower inshore diversity may reXect the impact of recent bleaching events on Sinularia assemblages, which have been more widespread and severe on inshore reefs, but may also have been shaped by historical sea level Xuctuations or recent migration patterns

Microsatellite allele sizes alone are insufficient to delineate species boundaries in Symbiodinium

Symbiodinium are a diverse group of unicellular dinoflagellates that are important nutritional symbionts of reef-building corals. Symbiodinium putative species ('types') are commonly identified with genetic markers, mostly nuclear and chloroplast encoded ribosomal DNA regions. Population genetic analyses using microsatellite loci have provided insights into Symbiodinium biogeography, connectivity and phenotypic plasticity, but are complicated by: (i) a lack of consensus criteria used to delineate inter- vs. intragenomic variation within species; and (ii) the high density of Symbiodinium in host tissues, which results in single samples comprising thousands of individuals. To address this problem, Wham & LaJeunesse (2016) present a method for identifying cryptic Symbiodinium species from microsatellite data based on correlations between allele size distributions and nongeographic genetic structure. Multilocus genotypes that potentially do not recombine in sympatry are interpreted as secondary 'species' to be discarded from downstream population genetic analyses. However, Symbiodinium species delineations should ideally incorporate multiple physiological, ecological and molecular criteria. This is because recombination tests may be a poor indicator of species boundaries in Symbiodinium due to their predominantly asexual mode of reproduction. Furthermore, discontinuous microsatellite allele sizes in sympatry may be explained by secondary contact between previously isolated populations and by mutations that occur in a nonstepwise manner. Limitations of using microsatellites alone to delineate species are highlighted in earlier studies that demonstrate occasional bimodal distributions of allele sizes within Symbiodinium species and considerable allele size sharing among Symbiodinium species. We outline these issues and discuss the validity of reinterpretations of our previously published microsatellite data from Symbiodinium populations on the Great Barrier Reef (Howells et al. 2013)

Understanding first year university students: personal epistemology and learning

Whilst participation in higher education has increased dramatically over the last two decades, many universities are only now beginning to pay more attention to the learning experiences of first year students. It is important for universities to understand how first year students conceive of learning and knowing in order to promote effective approaches to learning. Even though an extensive body of research demonstrates that beliefs about learning and knowing influence student approaches to learning and learning outcomes, there has been no Australian research that has investigated this critical learner characteristic across first year university students. This paper reports on preliminary data from an ongoing longitudinal study designed to investigate first year students’ beliefs about knowing and learning (epistemological beliefs). Students from teacher education and creative industry faculties in two Australian universities completed the Epistemological Beliefs Survey (EBS) in the first week of their first semester of study. A series of one-way ANOVA using key demographics as independent variables and the EBS factor scores as dependent variables showed that epistemological beliefs were related to the course of study, previous post-school education experience, family experience at University, gender and age. These data help us to understand students’ beliefs about learning and knowing with a view to informing effective learning in higher education

Toward a Soft X-Ray Fourier-Transform Spectrometer

The use of Fourier transform spectroscopy (FTS) in the soft x-ray region is advocated as a possible route to spectral resolution superior to that attainable with a grating system. A technical plan is described for applying FTS to the study of the absorption spectrum of helium in the region of double ionization around 60--80 eV. The proposed scheme includes a Mach-Zehnder interferometer deformed into a rhombus shape to provide grazing incidence reflections. The path difference between the interfering beams is to be tuned by translation of a table carrying four mirrors over a range {+-}1 cm which, in the absence of errors generating relative tilts of the wave fronts, would provide a resolving power equal to the number of waves of path difference: half a million at 65 eV, for example. The signal-to-noise ratio of the spectrum is analyzed and for operation on an Advanced Light Source bending magnet beam line should be about 330