Multi-aspect testing and ranking inference to quantify dimorphism in the cytoarchitecture of cerebellum of male, female and intersex individuals: a model applied to bovine brains.

The dimorphism among male, female and freemartin intersex bovines, focusing on the vermal lobules VIII and IX, was analyzed using a novel data analytics approach to quantify morphometric differences in the cytoarchitecture of digitalized sections of the cerebellum. This methodology consists of multivariate and multi-aspect testing for cytoarchitecture-ranking, based on neuronal cell complexity among populations defined by factors, such as sex, age or pathology. In this context, we computed a set of shape descriptors of the neural cell morphology, categorized them into three domains named size, regularity and density, respectively. The output and results of our methodology are multivariate in nature, allowing an in-depth analysis of the cytoarchitectonic organization and morphology of cells. Interestingly, the Purkinje neurons and the underlying granule cells revealed the same morphological pattern: female possessed larger, denser and more irregular neurons than males. In the Freemartin, Purkinje neurons showed an intermediate setting between males and females, while the granule cells were the largest, most regular and dense. This methodology could be a powerful instrument to carry out morphometric analysis providing robust bases for objective tissue screening, especially in the field of neurodegenerative pathologies

Non-responsive Dihydropteridine Reductase Deficiency

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Multi-aspect testing and ranking inference to quantify dimorphism in the cytoarchitecture of cerebellum of male, female and intersex individuals: a model applied to bovine brains

The dimorphism among male, female and freemartin intersex bovines, focusing on the vermal lobules VIII and IX, was analyzed using a novel data analytics approach to quantify morphometric differences in the cytoarchitecture of digitalized sections of the cerebellum. This methodology consists of multivariate and multi-aspect testing for cytoarchitecture-ranking, based on neuronal cell complexity among populations defined by factors, such as sex, age or pathology. In this context, we computed a set of shape descriptors of the neural cell morphology, categorized them into three domains named size, regularity and density, respectively. The output and results of our methodology are multivariate in nature, allowing an in-depth analysis of the cytoarchitectonic organization and morphology of cells. Interestingly, the Purkinje neurons and the underlying granule cells revealed the same morphological pattern: female possessed larger, denser and more irregular neurons than males. In the Freemartin, Purkinje neurons showed an intermediate setting between males and females, while the granule cells were the largest, most regular and dense. This methodology could be a powerful instrument to carry out morphometric analysis providing robust bases for objective tissue screening, especially in the field of neurodegenerative pathologies

Protein multi-scale organization through graph partitioning and robustness analysis: Application to the myosin-myosin light chain interaction

Despite the recognized importance of the multi-scale spatio-temporal organization of proteins, most computational tools can only access a limited spectrum of time and spatial scales, thereby ignoring the effects on protein behavior of the intricate coupling between the different scales. Starting from a physico-chemical atomistic network of interactions that encodes the structure of the protein, we introduce a methodology based on multi-scale graph partitioning that can uncover partitions and levels of organization of proteins that span the whole range of scales, revealing biological features occurring at different levels of organization and tracking their effect across scales. Additionally, we introduce a measure of robustness to quantify the relevance of the partitions through the generation of biochemically-motivated surrogate random graph models. We apply the method to four distinct conformations of myosin tail interacting protein, a protein from the molecular motor of the malaria parasite, and study properties that have been experimentally addressed such as the closing mechanism, the presence of conserved clusters, and the identification through computational mutational analysis of key residues for binding.Comment: 13 pages, 7 Postscript figure

Reproducibility of Ablated Volume Measurement Is Higher with Contrast-Enhanced Ultrasound than with B-Mode Ultrasound after Benign Thyroid Nodule Radiofrequency Ablation—A Preliminary Study

The reproducibility of contrast-enhanced ultrasound (CEUS) and standard B-mode ultrasound in the assessment of radiofrequency-ablated volume of benign thyroid nodules was compared. A preliminary study was conducted on consecutive patients who underwent radiofrequency ablation (RFA) of benign thyroid nodules between 2014 and 2016, with available CEUS and B-mode post-ablation checks. CEUS and B-mode images were retrospectively evaluated by two radiologists to assess inter- and intra-observer agreement in the assessment of ablated volume (Bland-Altman test). For CEUS, the mean inter-observer difference (95% limits of agreement) was 0.219 mL (-0.372-0.809 mL); for B-mode, the mean difference was 0.880 mL (-1.655-3.414 mL). Reproducibility was significantly higher for CEUS (85%) than for B-mode (27%). Mean intra-observer differences (95% limits of agreement) were 0.013 mL (0.803-4.097 mL) for Reader 1 and 0.031 mL (0.763-3.931 mL) for Reader 2 using CEUS, while they were 0.567 mL (-2.180-4.317 mL, Reader 1) and 0.759 mL (-2.584-4.290 mL, Reader 2) for B-mode. Intra-observer reproducibility was significantly higher for CEUS (96% and 95%, for the two readers) than for B-mode (21% and 23%). In conclusion, CEUS had higher reproducibility and inter- and intra-observer agreement compared to conventional B-mode in the assessment of radiofrequency-ablated volume of benign thyroid nodules

CT-derived pulmonary vascular metrics and clinical outcome in COVID-19 patients

To assess pulmonary vascular metrics on chest CT of COVID-19 patients, and their correlation with pneumonia extent (PnE) and outcome, we analyzed COVID-19 patients with an available previous chest CT, excluding those performed for cardiovascular disease. From February 21 to March 21, 2020, of 672 suspected COVID-19 patients from two centers who underwent CT, 45 RT-PCR-positives (28 males, median age 75, IQR 66-81 years) with previous CTs performed a median 36 months before (IQR 12-72 months) were included. We assessed PnE, pulmonary artery (PA) diameter, ascending aorta (Ao) diameter, and PA/Ao ratio. Most common presentations were fever and dyspnea (15/45) and fever alone (13/45). Outcome was available for 41/45 patients, 15/41 dead and 26/41 discharged. Ground-glass opacities (GGOs) alone were found in 29/45 patients, GGOs with consolidations in 15/45, consolidations alone in 1/45. All but one patient had bilateral pneumonia, 9/45 minimal, 22/45 mild, 9/45 moderate, and 5/45 severe PnE. PA diameter (median 31 mm, IQR 28-33 mm) was larger than before (26 mm, IQR 25-29 mm) (P<0.001), PA/Ao ratio (median 0.83, IQR 0.76-0.92) was higher than before (0.76, IQR 0.72-0.82) (P<0.001). Patients with adverse outcome (death) had higher PA diameter (P=0.001), compared to discharged ones. Only weak correlations were found between Delta PA or Delta PA/Ao and PnE (rho <= 0.453, P <= 0.032), with 4/45 cases with moderate-severe PnE and minimal increase in PA metrics. In conclusion, enlarged PA diameter was associated to death in COVID-19 patients, a finding deserving further investigation as a potential driver of therapy decision-making

The anti-apoptotic effect of ASC-exosomes in an in vitro ALS model and their proteomic analysis

Stem cell therapy represents a promising approach in the treatment of several neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS). The beneficial effect of stem cells is exerted by paracrine mediators, as exosomes, suggesting a possible potential use of these extracellular vesicles as non-cell based therapy. We demonstrated that exosomes isolated from adipose stem cells (ASC) display a neuroprotective role in an in vitro model of ALS. Moreover, the internalization of ASC-exosomes by the cells was shown and the molecules and the mechanisms by which exosomes could exert their beneficial effect were addressed. We performed for the first time a comprehensive proteomic analysis of exosomes derived from murine ASC. We identified a total of 189 proteins and the shotgun proteomics analysis revealed that the exosomal proteins are mainly involved in cell adhesion and negative regulation of the apoptotic process. We correlated the protein content to the anti-apoptotic effect of exosomes observing a downregulation of pro-apoptotic proteins Bax and cleaved caspase-3 and upregulation of anti-apoptotic protein Bcl-2 \u3b1, in an in vitro model of ALS after cell treatment with exosomes. Overall, this study shows the neuroprotective effect of ASC-exosomes after their internalization and their global protein profile, that could be useful to understand how exosomes act, demonstrating that they can be employed as therapy in neurodegenerative diseases

Herramienta de testing para visualización de información basada en interacciones de usuario

Decision-making has become a vital process in any organization, evolving from a process based on experience and intuition to one increasingly established in data analysis. One type of specialized software for data analysis is that of visual representations for large data sets. Visual representations are critically important today as they enable effective exploration of a data set and facilitate the task of identifying patterns and drawing conclusions. Every day more decisions are made based on visual analysis through visual representations of large data sets. It is not only a quantitative but also a qualitative increase. Decisions are more critical and with more impact on society, the environment, and individuals. In this context, it is essential to develop new and better methodologies and tools that allow the visualization developer to ensure the correct functioning of visual representations and their interactions. To achieve this goal, we present Test Suite Editor, a platform that assists in visualization testing. This platform facilitates the generation of test cases based on user interactions. This contribution is based on a previously published black box testing technique for information visualizations that uses regular expressions to represent the sequence of user interactions.La toma de decisiones se ha convertido en un proceso vital en cualquier organización, evolucionando de un proceso basado en la experiencia y la intuición a uno basado en el análisis de datos. La visualización es un tipo de software especializado para el análisis de grandes conjuntos de datos. La visualización de información es de vital importancia hoy en día, ya que permite la exploración efectiva de un conjunto de datos y facilita la tarea de identificar patrones y sacar conclusiones. Cada día se toman más decisiones basadas en el análisis visual a través de representaciones visuales de grandes conjuntos de datos. No es solo un aumento cuantitativo, sino también cualitativo. Las decisiones son más críticas y tienen más impacto en la sociedad, el medio ambiente y las personas. En este contexto, es fundamental desarrollar nuevas y mejores metodologías y herramientas que permitan al desarrollador de la visualización asegurar el correcto funcionamiento de las representaciones visuales y sus interacciones. Para lograr este objetivo, presentamos Test Suite Editor, una plataforma que ayuda en el testing de visualizaciones. Esta plataforma facilita la generación de casos de prueba basados en las interacciones del usuario. Esta contribución se basa en una técnica de prueba de caja negra publicada anteriormente para visualizaciones de información que utiliza expresiones regulares para representar la secuencia de interacciones del usuario.Facultad de Informátic