Survival, Reproduction and Calcification of Three Benthic Foraminiferal Species in Response to Experimentally Induced Hypoxia

An experiment was conducted to test the survival rates, growth (calcification), and reproduction capacities of three benthic foraminiferal species (Ammonia tepida, Melonis barleeanus and Bulimina marginata) under strongly oxygen-depleted conditions alternating with short periods of anoxia. Protocols were determined to use accurate methods (1) to follow oxygen concentrations in the aquaria (continuously recorded using microsensors), (2) to distinguish live foraminifera (fluorogenic probe), (3) to determine foraminiferal growth (calcein-marked shells and automatic measurement of the shell size). Our results show a very high survival rate, and growth of A. tepida and M. barleeanus in all experimental conditions, suggesting that survival and growth are not negatively impacted by hypoxia. Unfortunately, no reproduction was observed for these species, so that we cannot draw firm conclusions on their ability to reproduce under hypoxic/anoxic conditions. The survival rates of Bulimina marginata are much lower than for the other two species. In the oxic treatments, the presence of juveniles is indicative of reproductive events, which can explain an important part of the mortality. The absence of juveniles in the hypoxic/anoxic treatments could indicate that these conditions inhibit reproduction. Alternatively, the perceived absence of juveniles could also be due to the fact that the juveniles resulting from reproduction (causing similar mortality rates as in the oxic treatments) were not able to calcify, and remained at a propagule stage. Additional experiments are needed to distinguish these two options

Tapping culture collections for fungal endophytes: first genome assemblies for three genera and five species in the Ascomycota

The Ascomycota form the largest phylum in the fungal kingdom and show a wide diversity of lifestyles, some involving associations with plants. Genomic data are available for many ascomycetes that are pathogenic to plants, but endophytes, which are asymptomatic inhabitants of plants, are relatively understudied. Here, using short- and long-read technologies, we have sequenced and assembled genomes for 15 endophytic ascomycete strains from CABI’s culture collections. We used phylogenetic analysis to refine the classification of taxa, which revealed that 7 of our 15 genome assemblies are the first for the genus and/or species. We also demonstrated that cytometric genome size estimates can act as a valuable metric for assessing assembly “completeness”, which can easily be overestimated when using BUSCOs alone and has broader implications for genome assembly initiatives. In producing these new genome resources, we emphasise the value of mining existing culture collections to produce data that can help to address major research questions relating to plant–fungal interactions

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

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM

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

Le pelecinum de Doumet sur la commune de Châteauvert

National audienc

Le pelecinum de Doumet sur la commune de Châteauvert

National audienc

Mobile Wireless Middleware, Operating Systems, and Applications, Second International Conference, Mobilware 2009

The advances in wireless communication technologies and the proliferation of mobile devices have enabled the realization of intelligent environments for people to communicate with each other, interact with information processing devices, and receive a wide range of mobile wireless services through various types of networks and systems everywhere, anytime. This «Internet of Things» will dramatically modify our lives allowing progress in various domain such as health, security, and ITS (Intelligent Transportation Systems). A key enabler of this pervasive and ubiquitous connectivity environment is the advancement of software technology in various communication sectors, ranging from communication middleware and operating systems to networking protocols and applications. The international conference series on Mobile Wireless Middleware, Operating Systems, and Applications (MOBILWARE) is dedicated to address emerging topics and challenges in various mobile wireless software-related areas. The scope of the conference includes the design, implementation, deployment, and evaluation of middleware, operating systems, and applications for computing and communications in mobile wireless systems