• Neuroinformatics
• 2013-2022close
• Open Access close

BACKGROUND Pediatric obstructive sleep apnea (OSA) is associated with neurocognitive deficits. However, the neural substrates underlying such deficits remain unknown. METHODS To examine executive control and emotional processing in OSA, 10 children age 7 to 11 y with polysomnographically diagnosed OSA and 7 age- and sex-matched controls underwent a color-word Stroop task and an empathy task consisting of dynamic visual scenarios depicting interpersonal harm or neutral actions in a magnetic resonance imaging (MRI) scanner. Functional MRI data were processed using MATLAB 7.12 with SPM8 for region of interest (ROI) analyses, and a general linear model was used with regressors for each trial type in each task. RESULTS For the Stroop task, accuracy was similar in the two groups, with no differences in the effect of incongruency on success rates. OSA showed greater neural activity than controls in eight ROI clusters for incongruent versus congruent trials (P < 0.001). Within the a priori ROIs, the anterior cingulate cortex was significantly different between groups (P < 0.05). For perceiving harm versus neutral actions, ROI analysis revealed a significant correlation between apnea-hypopnea index and left amygdala activity in harm versus neutral actions (r = -0.71, P < 0.05). CONCLUSIONS These results provide the first functional MRI evidence that cognitive and empathetic processing is influenced by obstructive sleep apnea (OSA) in children. Children with OSA show greater neural recruitment of regions implicated in cognitive control, conflict monitoring, and attentional allocation in order to perform at the same level as children without OSA. When viewing empathy-eliciting scenarios, the severity of OSA predicted less sensitivity to harm in the left amygdala.

Brain metastases, including prevalent breast-to-brain metastasis (B2BM), represent an urgent unmet medical need in the care of cancer due to a lack of effective therapies. Immune evasion is essential for cancer cells to metastasize to the brain tissue for brain metastasis. However, the intrinsic genetic circuits that enable cancer cells to avoid immune-mediated killing in the brain microenvironment remain poorly understood. Here, we report that a brain-enriched long noncoding RNA (BMOR) expressed in B2BM cells is required for brain metastasis development and is both necessary and sufficient to drive cancer cells to colonize the brain tissue. Mechanistically, BMOR enables cancer cells to evade immune-mediated killing in the brain microenvironment for the development of brain metastasis by binding and inactivating IRF3. In preclinical brain metastasis murine models, locked nucleic acid-BMOR, a designed silencer targeting BMOR, is effective in suppressing the metastatic colonization of cancer cells in the brain for brain metastasis. Taken together, our study reveals a mechanism underlying B2BM immune evasion during cancer cell metastatic colonization of brain tissue for brain metastasis, where B2BM cells evade immune-mediated killing in the brain microenvironment by acquiring a brain-enriched long noncoding RNA genetic feature.

Head circumference (HC), the anthropometric index of both brain development and nutritional background, has been described to be significantly associated with scholastic achievement (SA). The aim of this study was to determine the impact of nutritional background and current nutritional status parameters on SA in the Education Quality Measurement System (SIMCE) tests. A representative sample of 33 schools was randomly chosen in the Metropolitan Region of Chile. The sample consisted of 1,353 school-aged children of both sexes, from the fifth grade of elementary school and from the first grade of high school who in 2009 took the SIMCE tests. Nutritional status was assessed through anthropometric parameters. Brain development was measured through the HC expressed as HC-for-age Z-score (Z-HC). Students with Z-HC 2 SD obtained low and high SA, respectively, both in the language and the mathematics tests (P < 0.001). In general, in both grades, those students with Z-HC ≥0 SD increase more than double the probability to obtain language and mathematics SA scores ≥ the median (P < 0.0001). We confirm the hypothesis that HC is the most relevant physical index associated with SA; therefore, children with the lowest scores in the SIMCE tests probably have lower brain development.

In this paper, we propose a multi-view learning method using Magnetic Resonance Imaging (MRI) data for Alzheimer’s Disease (AD) diagnosis. Specifically, we extract both Region-Of-Interest (ROI) features and Histograms of Oriented Gradient (HOG) features from each MRI image, and then propose mapping HOG features onto the space of ROI features to make them comparable and to impose high intra-class similarity with low inter-class similarity. Finally, both mapped HOG features and original ROI features are input to the support vector machine for AD diagnosis. The purpose of mapping HOG features onto the space of ROI features is to provide complementary information so that features from different views can not only be comparable (i.e., homogeneous) but also be interpretable. For example, ROI features are robust to noise, but lack of reflecting small or subtle changes, while HOG features are diverse but less robust to noise. The proposed multi-view learning method is designed to learn the transformation between two spaces and to separate the classes under the supervision of class labels. The experimental results on the MRI images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset show that the proposed multi-view method helps enhance disease status identification performance, outperforming both baseline methods and state-of-the-art methods.

Un modèle de prédiction du bruit de jet de mélange est développé dans l'objectif d'obtenir une estimation précise des effets de l'installation du moteur sur l'aile tout en maintenant un temps de calcul faible. Le modèle de prédiction de Tam et Auriault est utilisé comme point de départ. L'écoulement est simplifié en assimilant le jet à un milieu uniforme connecté au milieu ambiant, lui aussi uniforme, par une couche de mélange infiniment mince. La propagation des ondes sonore depuis le jet jusqu'à un observateur situé en champ lointain est ici simulée grâce à l'acoustique géométrique, utilisée dans ce milieu homogène par morceau. Le nouveau modèle est nommé TAGA pour Tam Auriault - Geometrical Acoustics.Le modèle TAGA est d'abord appliqué sur un cas académique, un jet simple sans gradient de température, placé à proximité d'une plaque plane. Le bruit de jet est prédit sur toute la gamme d'azimut, à un plan axial coïncidant avec la sortie de la tuyère. Moyennant une correction sur le niveau absolu, les résultats obtenus pour les microphones situés sous la plaque correspondent aux données expérimentales. Pour des observateurs positionnés au dessus de la plaque, les prédictions sont proches des mesures pour la gamme de fréquence correspondant au maximum du spectre. L'effet de masquage de la plaque est surestimé pour les plus hautes fréquences. Les résultats avec TAGA sont ensuite présentés d'une manière différente. La différence entre les spectres installés et isolés est ajoutée au spectre isolé mesuré. Cette méthode de mise à l'échelle permet d'obtenir une forme de spectre plus fidèle aux mesures. Un écart maximal, entre les prédictions et les données expérimentales, de 1 dB pour toutes les fréquences au-dessus de 1 kHz est obtenu. L'étude permet aussi la compréhension d'un pic secondaire observé dans les mesures. Ce phénomène est effectivement expliqué par l'interférence entre des rayons réfractés et réfléchis. Une seconde étude est menée sur un jet coaxial. Le cône de silence dû aux effets de réfraction est observé à une valeur proche de sa position théorique. Malgré les différences entre l'écoulement réel et sa modélisation dans TAGA, des résultats encourageants sont observés pour une large partie de la plage d'angles polaires. La méthode de mise à l'échelle est aussi utilisée pour la prédiction des effets de chevrons. L'augmentation du bruit à haute fréquence est bien estimée par le modèle TAGA. La réduction à basse fréquence n'est pas obtenue avec la formulation actuelle du modèle. A jet mixing noise prediction model is developed with the objective of obtaining an accurate estimate of installation effects while maintaining a low computing time. The Tam and Auriault prediction model is used as a starting point for the source term of the new formulation. The base flow is simplified by modelling the jet as a uniform medium connected to a uniform external medium through an infinitely thin mixing layer. The propagation of sound waves from the jet to an observer located in the far field is here simulated using geometrical acoustics. The new model developed is called TAGA for Tam Auriault - Geometrical Acoustics.The TAGA model is first applied to an academic configuration, a single jet without temperature gradient placed near a flat plate. Jet noise is predicted over the entire azimuth range, at an axial plane coinciding with the nozzle outlet. With an absolute level correction, the results obtained for the microphones under the plate match the experimental data. For observer positions above the plate, the predictions are close to measurements for the frequency range corresponding to the maximum of the spectrum. The shielding effect of the plate is however overestimated for the highest frequencies. The TAGA results are then reported in a different way. The difference between the installed and isolated spectra is added to the measured isolated spectrum. This scaling method allows a more accurate spectrum shape to be obtained. A maximum deviation, between predictions and experimental data, of 1 dB for all frequencies above 1 kHz is then obtained. The study also allows to understand a secondary peak observed in the measurements. This phenomenon is indeed explained by the interference between refracted and reflected rays. A second study is conducted on a coaxial jet. The cone of silence due to refraction effects is observed at a value close to its theoretical position. Despite the differences between the jet flow and its modelling in TAGA, encouraging results are observed for a large part of the polar angle range. The scaling method is also used to predict chevrons effects. The increase in high frequency noise is well estimated by the TAGA model. The reduction at low frequency is not found by the current formulation of the model.

The organization of sensory maps in the cerebral cortex depends on experience, which drives homeostatic and long-term synaptic plasticity of cortico-cortical circuits. In the mouse primary somatosensory cortex (S1) afferents from the higher-order, posterior medial thalamic nucleus (POm) gate synaptic plasticity in layer (L) 2/3 pyramidal neurons via disinhibition and the production of dendritic plateau potentials. Here we address whether these thalamocortically mediated responses play a role in whisker map plasticity in S1. We find that trimming all but two whiskers causes a partial fusion of the representations of the two spared whiskers, concomitantly with an increase in the occurrence of POm-driven N-methyl-D-aspartate receptor-dependent plateau potentials. Blocking the plateau potentials restores the archetypical organization of the sensory map. Our results reveal a mechanism for experience-dependent cortical map plasticity in which higher-order thalamocortically mediated plateau potentials facilitate the fusion of normally segregated cortical representations. Significance Here we describe a mechanism for cortical map plasticity. Classically, representational map changes are thought to be driven by changes within cortico-cortical circuits, e.g., Hebbian plasticity of synaptic circuits that lost vs. maintained an excitatory drive from the first-order thalamus, possibly steered by neuromodulatory forces from deep brain regions. Our work provides evidence for an additional gating mechanism, provided by plateau potentials, which are driven by higher-order thalamic feedback. Higher-order thalamic neurons are characterized by broad receptive fields, and the plateau potentials that they evoke strongly facilitate long-term potentiation and elicit spikes. We show that these features combined constitute a powerful driving force for the fusion or expansion of sensory representations within cortical maps.

Mood and anxiety disorders are complex heterogeneous syndromes that manifest in dysfunctions across multiple brain regions, cell types, and circuits. Biomarkers using brain-wide activity patterns in humans have proven useful in distinguishing between disorder subtypes and identifying effective treatments. In order to improve biomarker identification, it is crucial to understand the basic circuitry underpinning brain-wide activity patterns. Leveraging a large repertoire of techniques, animal studies have examined roles of specific cell types and circuits in driving maladaptive behavior. Recent advances in multiregion recording techniques, data-driven analysis approaches, and machine-learning-based behavioral analysis tools can further push the boundary of animal studies and bridge the gap with human studies, to assess how brain-wide activity patterns encode and drive emotional behavior. Together, these efforts will allow identifying more precise biomarkers to enhance diagnosis and treatment.