Neural Connectivity with Hidden Gaussian Graphical State-Model

The noninvasive procedures for neural connectivity are under questioning. Theoretical models sustain that the electromagnetic field registered at external sensors is elicited by currents at neural space. Nevertheless, what we observe at the sensor space is a superposition of projected fields, from the whole gray-matter. This is the reason for a major pitfall of noninvasive Electrophysiology methods: distorted reconstruction of neural activity and its connectivity or leakage. It has been proven that current methods produce incorrect connectomes. Somewhat related to the incorrect connectivity modelling, they disregard either Systems Theory and Bayesian Information Theory. We introduce a new formalism that attains for it, Hidden Gaussian Graphical State-Model (HIGGS). A neural Gaussian Graphical Model (GGM) hidden by the observation equation of Magneto-encephalographic (MEEG) signals. HIGGS is equivalent to a frequency domain Linear State Space Model (LSSM) but with sparse connectivity prior. The mathematical contribution here is the theory for high-dimensional and frequency-domain HIGGS solvers. We demonstrate that HIGGS can attenuate the leakage effect in the most critical case: the distortion EEG signal due to head volume conduction heterogeneities. Its application in EEG is illustrated with retrieved connectivity patterns from human Steady State Visual Evoked Potentials (SSVEP). We provide for the first time confirmatory evidence for noninvasive procedures of neural connectivity: concurrent EEG and Electrocorticography (ECoG) recordings on monkey. Open source packages are freely available online, to reproduce the results presented in this paper and to analyze external MEEG databases

Exploiting graphic processing units parallelism to improve intelligent data acquisition system performance in JET's correlation reflectometer

The performance of intelligent data acquisition systems relies heavily on their processing capabilities and local bus bandwidth, especially in applications with high sample rates or high number of channels. This is the case of the self adaptive sampling rate data acquisition system installed as a pilot experiment in KG8B correlation reflectometer at JET. The system, which is based on the ITMS platform, continuously adapts the sample rate during the acquisition depending on the signal bandwidth. In order to do so it must transfer acquired data to a memory buffer in the host processor and run heavy computational algorithms for each data block. The processing capabilities of the host CPU and the bandwidth of the PXI bus limit the maximum sample rate that can be achieved, therefore limiting the maximum bandwidth of the phenomena that can be studied. Graphic processing units (GPU) are becoming an alternative for speeding up compute intensive kernels of scientific, imaging and simulation applications. However, integrating this technology into data acquisition systems is not a straight forward step, not to mention exploiting their parallelism efficiently. This paper discusses the use of GPUs with new high speed data bus interfaces to improve the performance of the self adaptive sampling rate data acquisition system installed on JET. Integration issues are discussed and performance evaluations are presente

The texture development of ECAP processed AA1050aluminum, before and after a final anneal: effect of the initial texture

Equal Channel Angular Pressing (ECAP) can be used to control deformation and annealing textures. The initial texture has a significant role on texture development and intensity after deformation and anneal. In this work AA 1050 Al samples with different initial textures and initial strain of 0.3 were deformed in a I20° ECAP die. Deformation followed route A, yielding equivalents strains of 1 and 3 above the initial. After ECAP one of the samples was rolled to a thickness reduction of 70%. Texture evaluation was performed by x-ray analysis in the as deformed state and after annealing at 350°C for 1 h, by calculating orientation distribution functions. The microstructure was observed by optical and scanning electron microscopy.Fil: Vega, M. C. V.. Universidade Federal Do Sao Carlos. Departamento de Engenharia de Mteriales; BrasilFil: Piva, B. H.. Universidade Federal Do Sao Carlos. Departamento de Engenharia de Mteriales; BrasilFil: Bolmaro, Raul Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Física de Rosario (i); ArgentinaFil: Ferrante, M.. Universidade Federal Do Sao Carlos. Departamento de Engenharia de Mteriales; BrasilFil: Kliauga, A. M.. Universidade Federal Do Sao Carlos. Departamento de Engenharia de Mteriales; Brasi

Prevalence of Depressive Disorder in the Adult population of Latin America: a systematic review and meta-analysis

Background: Depressive disorder is one of the leading causes of disability worldwide; however its prevalence and association with inequality and crime is poorly characterised in Latin America. This study aimed to: i. systematically review population-based studies of prevalence of ICD/DSM depressive disorder in Latin America, ii. report pooled regional, country, and sex-specific prevalence estimates, and iii. test its association with four country-level development indicators: human development (HDI), income (Gini) and gender inequality (GII), and intentional homicide rate (IHR). Methods: We conducted a systematic review and meta-analysis of population-based studies reporting primary data on the prevalence of ICD/DSM depressive disorder in Latin America from 1990 to 2023, irrespective of language. We searched PubMed, PsycINFO, Cochrane Library, SciELO (regional database), LILAC (regional database), and available grey literature. Study quality was assessed using JBI’s critical appraisal tools. We generated pooled estimates using random-effects meta-analysis; heterogeneity was assessed using the I2 statistic. Meta-regression analyses were used to test associations of depression prevalence with indicators of inequality and human development. The study was registered with PROSPERO (CRD42019143054). Findings: Using data from 40 studies in Latin America, lifetime, 12-month, and current prevalence of ICD/DSM depressive disorder were calculated at 12.58% (95% CI 11.00%–14.16%); 5.30% (4.55–6.06%), and 3.12% (2.22–4.03), respectively. Heterogeneity was high across lifetime, 12-month, and current prevalence, sex, and countries. 12-month and current prevalence was associated with higher Gini and GII, 12-month prevalence with lower HDI, and current prevalence with higher IHR. Interpretation We found a high prevalence of ICD/DSM depressive disorders in Latin America, and a statistically significant association with inequality and development indicators. The high heterogeneity found across prevalence periods and the major gaps in country representation underscore the need to escalate efforts to improve mental health access and research capabilities in Latin America. Systematic, comparable prevalence estimates would inform more effective decision-making in the region

Closing the dark photon window to thermal dark matter

The nature of dark matter remains a central question in particle physics, cosmology, and astrophysics. The prevailing hypothesis postulates that dark matter consists of particles that interact only weakly with Standard Model particles. However, the knowledge of dark matter properties beyond these interactions is limited. This study explores a scenario involving a dark photon as a mediator between dark matter and the Standard Model, akin to the photon's role in electromagnetism. Recent cosmological and experimental evidence impose constraints on this scenario, focusing on results from direct detection experiments such as PICO-60, XENON-1T, and PANDAX-4T. The results reveal severe constraints, effectively closing the window for laboratory searches for dark photons as mediators between the Standard Model and the dark sector (dark electrons) in the secluded dark matter scenario. The findings underscore the need for alternative explanations and offer fresh perspectives on the ongoing quest to understand dark matter and its interactions since they are nearly independent of the dark electron fraction content for the total dark matter. This analysis significantly narrows down the parameter space for thermal dark matter scenarios involving a dark photon portal, reinforcing the urgency of exploring alternative models and designing new experiments to unravel the mysteries surrounding the nature of dark matter.Comment: 11 pages, 5 figure

Phosphorylation-dependent regulation of the NOTCH1 intracellular domain by dual-specificity tyrosine-regulated kinase 2

NOTCH proteins constitute a receptor family with a widely conserved role in cell cycle, growing and development regulation. NOTCH1, the best characterised member of this family, regulates the expression of key genes in cell growth and angiogenesis, playing an essential role in cancer development. These observations provide a relevant rationale to propose the inhibition of the intracellular domain of NOTCH1 (Notch1-IC) as a strategy for treating various types of cancer. Notch1-IC stability is mainly controlled by post-translational modifications. FBXW7 ubiquitin E3 ligase-mediated degradation is considered one of the most relevant, being the previous phosphorylation at Thr-2512 residue required. In the present study, we describe for the first time a new regulation mechanism of the NOTCH1 signalling pathway mediated by DYRK2. We demonstrate that DYRK2 phosphorylates Notch1-IC in response to chemotherapeutic agents and facilitates its proteasomal degradation by FBXW7 ubiquitin ligase through a Thr-2512 phosphorylation-dependent mechanism. We show that DYRK2 regulation by chemotherapeutic agents has a relevant effect on the viability, motility and invasion capacity of cancer cells expressing NOTCH1. In summary, we reveal a novel mechanism of regulation for NOTCH1 which might help us to better understand its role in cancer biology

Estimación de distribución de tamaños de partículas de coloides a partir de mediciones de luz dinámica a múltiples ángulos con optimización por enjambre de partículas

In this paper particle Swarm Optimization (PSO) algorithms are applied to estimate the particle size distribution (PSD) of a colloidal system from the average PSD diameters, which are measured by multi-angle dynamic light scattering. The system is considered a nonlinear inverse problem, and for this reason the estimation procedure requires a Tikhonov regularization method. The inverse problem is solved through several PSO strategies. The evaluated PSOs are tested through three simulated examples corresponding to polystyrene (PS) latexes with different PSDs, and two experimental examples obtained by simply mixing 2 PS standards. In general, the evaluation results of the PSOs are excellent; and particularly, the PSO with the Trelea’s parameter set shows a better performance than other implemented PSOs.En este artículo se presenta una aplicación del algoritmo de optimización por Enjambre de Partículas (PSO) para estimar la distribución de tamaños de partículas (DTP) de un sistema coloidal a partir de los diámetros medios obtenidos por dispersión de luz dinámica a múltiples ángulos. Dado que se trata de un problema inverso no lineal en el proceso de estimación el problema es regularizado por medio del método de regularización de Tikhonov y finalmente se soluciona con diferentes estrategias del algoritmo de PSO. La evaluación del algoritmo de PSO es realizada a través de tres ejemplos simulados correspondientes a látex de poliestireno con diferentes DTP y dos ejemplos experimentales obtenidos a partir de una simple mezcla de dos estándares de poliestirenos. En general todos los resultados de estimación del algoritmo de PSO son excelentes, en particular, el algoritmo con definición de parámetros de Trelea que presenta mejor desempeño que las otras implementaciones de PSO.Facultad de Ingenierí