Des connections du cerveau qui se redessinent

Affiche présentée dans le cadre du Colloque de l'ARC, «Pour que la formation de la relève scientifique soit sur toutes les lèvres», dans le cadre du 87e Congrès de l'Acfas, Université du Québec en Outaouais (UQO), Gatineau, le 28 mai 2019.Quand un sens est inopérant de façon prolongée en raison d’une pathologie, la section du cerveau qui lui serait normalement dédiée est plutôt utilisée pour traiter les stimuli provenant d’autres sens. Ceci donne probablement lieu à une réorganisation des connections complexes entre les structures du cerveau. C’est ce que nous cherchons à mettre en évidence. Nous comparons à cette fin la connectivité structurelle de cerveaux sourds à celle de cerveaux percevant les stimuli auditifs, en particulier là où il y a traitement auditif, langagier, somatosensoriel et visuel. Pour ce faire, nous avons analysé les images de diffusion en résonance magnétique (DW-IRM) de deux groupes : 17 personnes non entendantes et 17 personnes entendantes.  Nous avons d’abord appliqué une méthode standard qui consiste à comparer l’anisotropie fractionnelle (AF) des fibres principales des deux groupes. Une AF de 0 indique un milieu de diffusion isotrope alors qu’une AF près de 1 indique un milieu où la diffusion est restreinte à une dimension. Nous avons obtenu des résultats préliminaires prometteurs, mais insuffisants pour indiquer une différence significative entre les deux groupes. Nous avons donc poussé plus loin et tracé le trajet des fibres reliant des structures cérébrales clés en utilisant des outils plus sophistiqués. Nous appliquons maintenant des méthodes statistiques puissantes pouvant détecter des différences subtiles de connectivité entre nos deux groupes cibles

Manganese Superoxide Dismutase Gene Expression Is Induced by Nanog and Oct4, Essential Pluripotent Stem Cells? Transcription Factors

Pluripotent stem cells possess complex systems that protect them from oxidative stress and ensure genomic stability, vital for their role in development. Even though it has been reported that antioxidant activity diminishes along stem cell differentiation, little is known about the transcriptional regulation of the involved genes. The reported modulation of some of these genes led us to hypothesize that some of them could be regulated by the transcription factors critical for self-renewal and pluripotency in embryonic stem cells (ESCs) and in induced pluripotent stem cells (iPSCs). In this work, we studied the expression profile of multiple genes involved in antioxidant defense systems in both ESCs and iPSCs. We found that Manganese superoxide dismutase gene (Mn-Sod/Sod2) was repressed during diverse differentiation protocols showing an expression pattern similar to Nanog gene. Moreover, Sod2 promoter activity was induced by Oct4 and Nanog when we performed a transactivation assay using two different reporter constructions. Finally, we studied Sod2 gene regulation by modulating the expression of Oct4 and Nanog in ESCs by shRNAs and found that downregulation of any of them reduced Sod2 expression. Our results indicate that pluripotency transcription factors positively modulate Sod2 gene transcription.Fil: Solari, Claudia María. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; ArgentinaFil: Vazquez Echegaray, Camila. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Cosentino, María Soledad. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Petrone Parcero, María Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; ArgentinaFil: Waisman, Ariel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Luzzani, Carlos Daniel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Francia, Marcos Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; ArgentinaFil: Villodre, Emilly. Universidade Federal do Rio Grande do Sul; BrasilFil: Lenz, Guido. Universidade Federal do Rio Grande do Sul; BrasilFil: Miriuka, Santiago Gabriel. Laboratorio de Investigaciones en Neurociencias Aplicadas; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Barañao, Lino. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Guberman, Alejandra Sonia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; Argentin

Tractostorm 2 : Optimizing tractography dissection reproducibility with segmentation protocol dissemination

The segmentation of brain structures is a key component of many neuroimaging studies. Consistent anatomical definitions are crucial to ensure consensus on the position and shape of brain structures, but segmentations are prone to variation in their interpretation and execution. White-matter (WM) pathways are global structures of the brain defined by local landmarks, which leads to anatomical definitions being difficult to convey, learn, or teach. Moreover, the complex shape of WM pathways and their representation using tractography (streamlines) make the design and evaluation of dissection protocols difficult and time-consuming. The first iteration of Tractostorm quantified the variability of a pyramidal tract dissection protocol and compared results between experts in neuroanatomy and nonexperts. Despite virtual dissection being used for decades, in-depth investigations of how learning or practicing such protocols impact dissection results are nonexistent. To begin to fill the gap, we evaluate an online educational tractography course and investigate the impact learning and practicing a dissection protocol has on interrater (groupwise) reproducibility. To generate the required data to quantify reproducibility across raters and time, 20 independent raters performed dissections of three bundles of interest on five Human Connectome Project subjects, each with four timepoints. Our investigation shows that the dissection protocol in conjunction with an online course achieves a high level of reproducibility (between 0.85 and 0.90 for the voxel-based Dice score) for the three bundles of interest and remains stable over time (repetition of the protocol). Suggesting that once raters are familiar with the software and tasks at hand, their interpretation and execution at the group level do not drastically vary. When compared to previous work that used a different method of communication for the protocol, our results show that incorporating a virtual educational session increased reproducibility. Insights from this work may be used to improve the future design of WM pathway dissection protocols and to further inform neuroanatomical definitions.Peer reviewe

A prospective study of childhood predictors of traumatic brain injuries sustained in adolescence and adulthood.

OBJECTIVE: Traumatic brain injuries (TBIs) are sustained by approximately 17% of males in the general population, many of whom subsequently present mental disorders, cognitive, and physical problems. Little is known about predictors of TBIs and how to prevent them. The present study aimed to determine whether inattention-hyperactivity and/or all externalizing problems presented by boys at age 10 predict subsequent TBIs to age 34 after taking account of previous TBIs and family social status (FSS). METHOD: 742 Canadian males were followed, prospectively, from age 6 to 34. Diagnoses of TBIs were extracted from health files, parents-reported sociodemographic and family characteristics at participants' age 6, and teachers-rated participants' behaviors at age 10. Separate logistic regression models predicted TBIs sustained from age 11 to 17 and from age 18 to 34. For each age period, two models were computed, one included previous TBIs, inattention-hyperactivity, FSS, and interaction terms, the second included previous TBIs, externalizing problems, FSS, and interaction terms. RESULTS: In models that included inattention-hyperactivity, TBIs sustained from age 11 to 17 were predicted by age 10 inattention-hyperactivity and by TBIs prior to age 11; TBIs sustained from age 18 to 34 were predicted by age 10 inattention-hyperactivity. In models that included all externalizing problems, TBIs from age 11 to 17 were predicted by prior TBIs; TBIs sustained from age 18 to 34 were predicted by age 10 externalizing problems. Neither FSS nor interaction terms predicted TBIs in any of the models. CONCLUSIONS: Among males, using evidence-based treatments to reduce inattention-hyperactivity and externalizing problems among boys could, potentially, decrease the risk of TBIs to age 34. Further, boys who sustain TBIs in childhood require monitoring to prevent recurrence in adolescence

Structural Connectivity Alterations in Operculo-Insular Epilepsy

Operculo-insular epilepsy (OIE) is an under-recognized condition that can mimic temporal and extratemporal epilepsies. Previous studies have revealed structural connectivity changes in the epileptic network of focal epilepsy. However, most reports use the debated streamline-count to quantify 'connectivity strength' and rely on standard tracking algorithms. We propose a sophisticated cutting-edge method that is robust to crossing fibers, optimizes cortical coverage, and assigns an accurate microstructure-reflecting quantitative conectivity marker, namely the COMMIT (Convex Optimization Modeling for Microstructure Informed Tractography)-weight. Using our pipeline, we report the connectivity alterations in OIE. COMMIT-weighted matrices were created in all participants (nine patients with OIE, eight patients with temporal lobe epilepsy (TLE), and 22 healthy controls (HC)). In the OIE group, widespread increases in 'connectivity strength' were observed bilaterally. In OIE patients, 'hyperconnections' were observed between the insula and the pregenual cingulate gyrus (OIE group vs. HC group) and between insular subregions (OIE vs. TLE). Graph theoretic analyses revealed higher connectivity within insular subregions of OIE patients (OIE vs. TLE). We reveal, for the first time, the structural connectivity distribution in OIE. The observed pattern of connectivity in OIE likely reflects a diffuse epileptic network incorporating insular-connected regions and may represent a structural signature and diagnostic biomarker

Oct4 and Nanog induce pSod2-Luc constructions.

<p><b>(A)</b> Scheme of pSod2.1-Luc and pSod2.2-Luc constructions showing the putative binding sites for Oct4 and Nanog. <b>(B)</b> NIH/3T3 cells were transfected with pSod2.1-Luc or pSod2.2-Luc and with the indicated amounts of pMXs-Nanog, pMXs-Oct4 or both. Luciferase activities were measured as described in Material and Methods. Values were normalized to <i>Renilla</i>’s luciferase and referred to the basal condition (without the addition of any transcription factor). Results are shown as mean ± SEM of at least three independent experiments. Different letters indicate statistically significant differences between treatments (p < 0.05).</p

Sod2 is repressed in ESCs subjected to distinct differentiation protocols.

<p>ESCs were cultured as described in each case. Then, RNA was extracted and the expression of the indicated genes was measured by RT-qPCR. Gene expression was normalized to the geometrical mean of Gapdh and Pgk1 expression and referred to the control condition. Results are shown as mean ± SEM of three independent experiments. <b>(A)</b> R1 ESCs were cultured under standard conditions in the presence of LIF (control, shown as a dashed line) or in the absence of LIF, for 4 days. * p < 0.05. <b>(B)</b> 46C ESCs were subjected to a neural progenitor differentiation protocol. Expression of the indicated genes was analyzed at days 0 (D0, control), 3 (D3) and 6 (D6) after the induction of differentiation. Different letters (A or B) indicate statistically significant differences between treatments. AB indicates no statistically significant difference either to A or to B (p < 0.05).</p