A Myc-regulated transcriptional network controls B-cell fate in response to BCR triggering

BACKGROUND: The B cell antigen receptor (BCR) is a signaling complex that mediates the differentiation of stage-specific cell fate decisions in B lymphocytes. While several studies have shown differences in signal transduction components as being key to contrasting phenotypic outcomes, little is known about the differential BCR-triggered gene transcription downstream of the signaling cascades. RESULTS: Here we define the transcriptional changes that underlie BCR-induced apoptosis and proliferation of immature and mature B cells, respectively. Comparative genome-wide expression profiling identified 24 genes that discriminated between the early responses of the two cell types to BCR stimulation. Using mice with a conditional Myc-deletion, we validated the microarray data by demonstrating that Myc is critical to promoting BCR-triggered B-cell proliferation. We further investigated the Myc-dependent molecular mechanisms and found that Myc promotes a BCR-dependent clonal expansion of mature B cells by inducing proliferation and inhibiting differentiation. CONCLUSION: This work provides the first comprehensive analysis of the early transcriptional events that lead to either deletion or clonal expansion of B cells upon antigen recognition, and demonstrates that Myc functions as the hub of a transcriptional network that control B-cell fate in the periphery

Multiscale structure description of positon Emission tomography difference images

A method is presented here which aims at analyzing Positon Emission Tomography difference images . This method is based on a explicit description of the structure of the images. Positon Emission Tomography images are used to investigate the functional organisation of the brain, looking at the cerebral blood flow . The differences between two images from the same subject lead to th e changes of activity between two particular states . These differences, called "functional activations", are supposed to be specific o f a particular task . The aim is then to detect functional activations while preserving individual information, unlike classical statistica l methods which look mainly for the average information across several subjects . We then build a 3-dimensional linear scale-spac e from the original image. Objects are extracted at each level of scale in a fully-automatic way. Then they are linked across th e scales to get multi-scale objects in the scale-space . A vector of measures is associated to each of these multi-scale objects in order to characterize functional activations . We present a short study to determine the relevancy of these measures and the way the y can be used .Nous présentons ici une méthode d'analyse d'images de différence issues de la Tomographie par Emission de Positons (TEP) qui repose sur une description explicite de la structure de ces images. Les images TEP permettent, par l'intermédiaire du débit sanguin cérébral, de rendre compte de l'état fonctionnel du cerveau. En utilisant la différence entre deux images d'un même sujet, on essaye de déterminer les différences d'activité cérébrale entre deux états. Ces différences sont supposées être spécifiques d'une tâche isolée par la différence entre les deux états, et nous les appellerons « activations fonctionnelles ». L'objectif est donc de caractériser les activations fonctionnelles dans ces images de différence, tout en préservant l'information individuelle propre au sujet, ce qui n'est pas le cas des méthodes statistiques classiques, qui s'intéressent surtout à l'information moyenne sur l'ensemble des sujets. Un espace d'échelles (« scale-space ») linéaire tri-dimensionnel est d'abord construit à partir de l'image de différence originale, puis des objets sont extraits à chaque niveau d'échelle de manière entièrement automatique. ces objets sont ensuites liés dans les échelles pour former d'autres objets dans le scale-space. Des mesures sont alors définies et associées à chacun d'eux, afin de caractériser les activations fonctionnelles. Une étude sur la pertinence des objets définis et l'utilisation possible des mesures associées est présentée

Nonsupervised Ranking of Different Segmentation Approaches: Application to the Estimation of the Left Ventricular Ejection Fraction From Cardiac Cine MRI Sequences

International audienceA statistical methodology is proposed to rank several estimation methods of a relevant clinical parameter when no gold standard is available. Based on a regression without truth method, the proposed approach was applied to rank eightmethods without using any a priori information regarding the reliability of each method and its degree of automation. It was only based on a prior concerning the statistical distribution of the parameter of interest in the database. The ranking of the methods relies on figures of merit derived from the regression and computed using a bootstrap process. The methodology was applied to the estimation of the left ventricular ejection fraction derived from cardiac magnetic resonance images segmented using eight approaches with different degrees of automation: three segmentations were entirely manually performed and the others were variously automated. The ranking of methods was consistent with the expected performance of the estimation methods: the most accurate estimates of the ejection fraction were obtained using manual segmentations. The robustness of the ranking was demonstrated when at least three methods were compared. These results suggest that the proposed statistical approach might be helpful to assess the performance of estimation methods on clinical data for which no gold standard is available

Cytokine Signature in Schnitzler Syndrome: Proinflammatory Cytokine Production Associated to Th Suppression

Background: Schnitzler syndrome (SchS) is a rare autoinflammatory disease characterized by urticarial exanthema, bone and joint alterations, fever and monoclonal IgM gammopathy. Overactivation of the interleukin(IL)-1 system is reported, even though the exact pathophysiological pathways remain unknown. Objective: To determine ex vivo cytokine profiles of Peripheral Blood Mononuclear Cells (PBMCs) from SchS patients prior to treatment and after initiation of anti-IL-1 therapy (anakinra). The sera cytokine profile was studied in parallel. Methods: We collected blood samples from thirty-six untreated or treated SchS. PBMCs were cultured with and without LPS or anti-CD3/CD28. Cytokine levels were evaluated in serum and cell culture supernatants using Luminex technology. Results: Spontaneous TNFα, IL-6, IL-1β, IL-1α, and IL-1RA release by PBMCs of SchS patients were higher than in controls. LPS-stimulation further induced the secretion of these cytokines. In contrast, after T-cell stimulation, TNFα, IL-10, IFNγ, IL-17A, and IL-4 production decreased in SchS patients compared to healthy controls, but less in treated patients. Whereas IL-1β serum level was not detected in most sera, IL-6, IL-10, and TNFα serum levels were higher in patients with SchS and IFNγ and IL-4 levels were lower. Of note, IL-6 decreased after treatment in SchS (p = 0.04). Conclusion: Our data strengthen the hypothesis of myeloid inflammation in SchS, mediated in particular by IL-1β, TNFα, and IL-6, associated with overproduction of the inhibitors IL-1RA and IL-10. In contrast, we observed a loss of Th1, Th2, and Th17 cell functionalities that tends to be reversed by anakinra

Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia.

Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = -0.71 to -1.37; P < 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = -0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10-6, 1.7 × 10-9, 3.5 × 10-12 and 1.0 × 10-4, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes

Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset

<p>Abstract</p> <p>Background</p> <p>Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interactions may be modelled by a Bayesian Network (BN) that represents the presence of direct interactions from regulators to regulees by conditional probability distributions. We used enhanced evolutionary algorithms to stochastically evolve a set of candidate BN structures and found the model that best fits data without prior knowledge.</p> <p>Results</p> <p>We proposed various evolutionary strategies suitable for the task and tested our choices using simulated data drawn from a given bio-realistic network of 35 nodes, the so-called insulin network, which has been used in the literature for benchmarking. We assessed the inferred models against this reference to obtain statistical performance results. We then compared performances of evolutionary algorithms using two kinds of recombination operators that operate at different scales in the graphs. We introduced a niching strategy that reinforces diversity through the population and avoided trapping of the algorithm in one local minimum in the early steps of learning. We show the limited effect of the mutation operator when niching is applied. Finally, we compared our best evolutionary approach with various well known learning algorithms (MCMC, K2, greedy search, TPDA, MMHC) devoted to BN structure learning.</p> <p>Conclusion</p> <p>We studied the behaviour of an evolutionary approach enhanced by niching for the learning of gene regulatory networks with BN. We show that this approach outperforms classical structure learning methods in elucidating the original model. These results were obtained for the learning of a bio-realistic network and, more importantly, on various small datasets. This is a suitable approach for learning transcriptional regulatory networks from real datasets without prior knowledge.</p

Satellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecological Applications 28 (2018): 749-760, doi: 10.1002/eap.1682.The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite‐based sensors can repeatedly record the visible and near‐infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100‐m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short‐wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14‐bit digitization, absolute radiometric calibration <2%, relative calibration of 0.2%, polarization sensitivity <1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3‐d repeat low‐Earth orbit could sample 30‐km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications.National Center for Ecological Analysis and Synthesis (NCEAS); National Aeronautics and Space Administration (NASA) Grant Numbers: NNX16AQ34G, NNX14AR62A; National Ocean Partnership Program; NOAA US Integrated Ocean Observing System/IOOS Program Office; Bureau of Ocean and Energy Management Ecosystem Studies program (BOEM) Grant Number: MC15AC0000

Preference for biological motion is reduced in ASD: implications for clinical trials and the search for biomarkers

Background: The neurocognitive mechanisms underlying autism spectrum disorder (ASD) remain unclear. Progress has been largely hampered by small sample sizes, variable age ranges and resulting inconsistent findings. There is a pressing need for large definitive studies to delineate the nature and extent of key case/control differences to direct research towards fruitful areas for future investigation. Here we focus on perception of biological motion, a promising index of social brain function which may be altered in ASD. In a large sample ranging from childhood to adulthood, we assess whether biological motion preference differs in ASD compared to neurotypical participants (NT), how differences are modulated by age and sex and whether they are associated with dimensional variation in concurrent or later symptomatology. Methods: Eye-tracking data were collected from 486 6-to-30-year-old autistic (N = 282) and non-autistic control (N = 204) participants whilst they viewed 28 trials pairing biological (BM) and control (non-biological, CTRL) motion. Preference for the biological motion stimulus was calculated as (1) proportion looking time difference (BM-CTRL) and (2) peak look duration difference (BM-CTRL). Results: The ASD group showed a present but weaker preference for biological motion than the NT group. The nature of the control stimulus modulated preference for biological motion in both groups. Biological motion preference did not vary with age, gender, or concurrent or prospective social communicative skill within the ASD group, although a lack of clear preference for either stimulus was associated with higher social-communicative symptoms at baseline. Limitations: The paired visual preference we used may underestimate preference for a stimulus in younger and lower IQ individuals. Our ASD group had a lower average IQ by approximately seven points. 18% of our sample was not analysed for various technical and behavioural reasons. Conclusions: Biological motion preference elicits small-to-medium-sized case–control effects, but individual differences do not strongly relate to core social autism associated symptomatology. We interpret this as an autistic difference (as opposed to a deficit) likely manifest in social brain regions. The extent to which this is an innate difference present from birth and central to the autistic phenotype, or the consequence of a life lived with ASD, is unclear

Saccade dysmetria indicates attenuated visual exploration in autism spectrum disorder

Background: Visual exploration in autism spectrum disorder (ASD) is characterized by attenuated social attention. The underlying oculomotor function during visual exploration is understudied, whereas oculomotor function during restricted viewing suggested saccade dysmetria in ASD by altered pontocerebellar motor modulation. Methods: Oculomotor function was recorded using remote eye tracking in 142 ASD participants and 142 matched neurotypical controls during free viewing of naturalistic videos with and without human content. The sample was heterogenous concerning age (6–30&nbsp;years), cognitive ability (60–140 IQ), and male/female ratio (3:1). Oculomotor function was defined as saccade, fixation, and pupil-dilation features that were compared between groups in linear mixed models. Oculomotor function was investigated as ASD classifier and features were correlated with clinical measures. Results: We observed decreased saccade duration (∆M&nbsp;=&nbsp;−0.50, CI [−0.21, −0.78]) and amplitude (∆M&nbsp;=&nbsp;−0.42, CI [−0.12, −0.72]), which was independent of human video content. We observed null findings concerning fixation and pupil-dilation features (POWER&nbsp;=.81). Oculomotor function is a valid ASD classifier comparable to social attention concerning discriminative power. Within ASD, saccade features correlated with measures of restricted and repetitive behavior. Conclusions: We conclude saccade dysmetria as ASD oculomotor phenotype relevant to visual exploration. Decreased saccade amplitude and duration indicate spatially clustered fixations that attenuate visual exploration and emphasize endogenous over exogenous attention. We propose altered pontocerebellar motor modulation as underlying mechanism that contributes to atypical (oculo-)motor coordination and attention function in ASD

Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes:findings from the ENIGMA Epigenetics Working Group

DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)-three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions