A classification approach for heterotic performance prediction based on molecular marker data

A number of statistical methods based on molecular data are currently available for assigning new inbreds to heterotic groups in maize (Zea mays L), with variable results. We conjecture that the main flaw of such models is that they do not capture the non-linear relation between parental data and progeny performance. In this paper, we propose the use of supervised learning methods for handling such non-linearity. Standard and novel multiclassification methods are evaluated. Best results are obtained with the recently introduced class of multiclass, binary based,Recursive ECOC (RECOC) classifiers. RECOC classifiers are inspired in state of art Coding Theory solutions for the problem of transmitting symbols over noisy channels. For molecular marker data the noisy channel abstraction embeds the hardness of learning a classification function from noisy and scarce samples. Field data (top crosses between 26 inbreed lines and four tester populations), processed by cluster analysis in a previous work, was integrated with molecular marker data and used for training RECOC – AdaBoost Support Vector Machines RBF classifiers. A 34.10 % 3-CV error was achieved, clearly improving previously reported results on this task.Sociedad Argentina de Informática e Investigación Operativ

Supervised machine learning and heterotic classification of maize (Zea mays L.) using molecular marker data

The development of molecular techniques for genetic analysis has enabled great advances in cereal breeding. However, their usefulness in hybrid breeding, particularly in assigning new lines to heterotic groups previously established, still remains unsolved. In this work we evaluate the performance of several state-of-art multiclass classifiers onto three molecular marker datasets representing a broad spectrum of maize heterotic patterns. Even though results are variable, they suggest supervised learning algorithms as a valuable complement to traditional breeding programs.Fil: Ornella, Leonardo Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Tapia, Elizabeth. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentin

Satellite Data and Supervised Learning to Prevent Impact of Drought on Crop Production: Meteorological Drought

Reiterated and extreme weather events pose challenges for the agricultural sector. The convergence of remote sensing and supervised learning (SL) can generate solutions for the problems arising from climate change. SL methods build from a training set a function that maps a set of variables to an output. This function can be used to predict new examples. Because they are nonparametric, these methods can mine large quantities of satellite data to capture the relationship between climate variables and crops, or successfully replace autoregressive integrated moving average (ARIMA) models to forecast the weather. Agricultural indices (AIs) reflecting the soil water conditions that influence crop conditions are costly to monitor in terms of time and resources. So, under certain circumstances, meteorological indices can be used as substitutes for AIs. We discuss meteorological indexes and review SL approaches that are suitable for predicting drought based on historical satellite data. We also include some illustrative case studies. Finally, we will survey rainfall products existing at the web and some alternatives to process the data: from high-performance computing systems able to process terabyte-scale datasets to open source software enabling the use of personal computers

A classification approach for heterotic performance prediction based on molecular marker data

A number of statistical methods based on molecular data are currently available for assigning new inbreds to heterotic groups in maize (Zea mays L), with variable results. We conjecture that the main flaw of such models is that they do not capture the non-linear relation between parental data and progeny performance. In this paper, we propose the use of supervised learning methods for handling such non-linearity. Standard and novel multiclassification methods are evaluated. Best results are obtained with the recently introduced class of multiclass, binary based,Recursive ECOC (RECOC) classifiers. RECOC classifiers are inspired in state of art Coding Theory solutions for the problem of transmitting symbols over noisy channels. For molecular marker data the noisy channel abstraction embeds the hardness of learning a classification function from noisy and scarce samples. Field data (top crosses between 26 inbreed lines and four tester populations), processed by cluster analysis in a previous work, was integrated with molecular marker data and used for training RECOC – AdaBoost Support Vector Machines RBF classifiers. A 34.10 % 3-CV error was achieved, clearly improving previously reported results on this task.Sociedad Argentina de Informática e Investigación Operativ

Análisis textural y paragenético de laveta sur del proyecto Cerro Norte, distrito minero Casposo, San Juan

Textural and paragenetic analysis of the Sur vein of the Cerro Norte Project, Casposo Mining District, San Juan. The Casposo mining district is located in the province of San Juan (Argentina) in the eastern sector of the Cordillera Frontal. Within this district epithermal lowsulphidation deposits are hosted by Vega de los Machos Formation (Caballé 1986) of lower Permian age. Cerro Norte has a system of E-O veins with dip between 60 and 85° to the North and the South and form three main outcrops: Norte, Centro and Sur veins. The latter is the reason for the present study. The Sur vein extends more than 400 m and its thickness varies from 0.20 m. up to 3 m. It is characterized by a bifurcation pattern. It comprises 6 events. Event 1 is characterized by crustiform-colloform quartz 1 (Fig. 1a and b) with moss (Fig. 1a) and spherulitic texture (Fig. 1b). This event presents mosaic textures (Fig. 1c) and flaming extinction (Fig. 1d) typical of recrystallization. Recrystallization, although it constitutes another event, could not be temporarily limited. Event 2 is formed by massive microcrystalline quartz of anhedral habit (Fig. 1e). Event 3 is the crystallization of calcite in the form of "blades". Event 4 shows the pseudomorphic replacement of calcite by quartz that forms the lattice-bladed texture (Fig. 1f). Event 5 represents the crystallization of drustiform habit quartz with zoned texture (Fig. 1g). Event 6 constitutes the formation of a hydrothermal breccia that includes clasts from previous events and cement crustiform-colloform quartz 2 (Fig. 1h), calcite, chlorite, freibergite-argentotennantite 1 (?), freibergite-argentotennantite 2 (?), pearceite-polybasite (?), freieslebenite (?), sphalerite, chalcopyrite, pyrite and native silver.Fil: Medrano, Ornella. Universidad Nacional del Sur. Departamento de Geología; ArgentinaFil: D'annunzio, María Celeste. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Geológico del Sur. Universidad Nacional del Sur. Departamento de Geología. Instituto Geológico del Sur; ArgentinaFil: Strazzere, Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Geológico del Sur. Universidad Nacional del Sur. Departamento de Geología. Instituto Geológico del Sur; ArgentinaXIII Congreso de Mineralogía, Petrología Ígnea y Metamórfica, y MetalogénesisCórdobaArgentinaAsociación Mineralógica ArgentinaComisión Científica de Petrología de la Asociación Geológica Argentin

Reference Genes for Real-Time PCR Quantification of MicroRNAs and Messenger RNAs in Rat Models of Hepatotoxicity

Hepatotoxicity is associated with major changes in liver gene expression induced by xenobiotic exposure. Understanding the underlying mechanisms is critical for its clinical diagnosis and treatment. MicroRNAs are key regulators of gene expression that control mRNA stability and translation, during normal development and pathology. The canonical technique to measure gene transcript levels is Real-Time qPCR, which has been successfully modified to determine the levels of microRNAs as well. However, in order to obtain accurate data in a multi-step method like RT-qPCR, the normalization with endogenous, stably expressed reference genes is mandatory. Since the expression stability of candidate reference genes varies greatly depending on experimental factors, the aim of our study was to identify a combination of genes for optimal normalization of microRNA and mRNA qPCR expression data in experimental models of acute hepatotoxicity. Rats were treated with four traditional hepatotoxins: acetaminophen, carbon tetrachloride, D-galactosamine and thioacetamide, and the liver expression levels of two groups of candidate reference genes, one for microRNA and the other for mRNA normalization, were determined by RT-qPCR in compliance with the MIQE guidelines. In the present study, we report that traditional reference genes such as U6 spliceosomal RNA, Beta Actin and Glyceraldehyde-3P-dehydrogenase altered their expression in response to classic hepatotoxins and therefore cannot be used as reference genes in hepatotoxicity studies. Stability rankings of candidate reference genes, considering only those that did not alter their expression, were determined using geNorm, NormFinder and BestKeeper software packages. The potential candidates whose measurements were stable were further tested in different combinations to find the optimal set of reference genes that accurately determine mRNA and miRNA levels. Finally, the combination of MicroRNA-16/5S Ribosomal RNA and Beta 2 Microglobulin/18S Ribosomal RNA were validated as optimal reference genes for microRNA and mRNA quantification, respectively, in rat models of acute hepatotoxicity

Bio y agroInformática en CIFASIS

Las tecnologías de alto rendimiento en proyectos de ciencias de la vida generan cantidades exponenciales de datos cuya naturaleza y complejidad inspira el desarrollo de nuevos métodos computacionales para la extracción y gestión de información biológica relevante con el objetivo de lograr una comprensión más acabada de la vida tanto a nivel molecular como poblacional. Este contexto tecnológico, define un nuevo campo de investigación multidisciplinar conocido como Bioinformática. En nuestro grupo estamos interesados en el desarrollo de algoritmos y herramientas bioinformáticas para el análisis, procesamiento y gestión de datos de espectroscopia, microarreglos, marcadores moleculares y de secuenciación de alto rendimiento en el marco de proyectos de investigación básica y biológica multidisciplinar. Nuestro trabajo en Bioinformática inspira además la introducción de tecnologías de alto rendimiento y procesamiento de datos en Agricultura de Precisión, en el marco de un campo de investigación incipiente conocido como Agroinformática.Eje: Procesamiento de señales y sistemas de tiempo realRed de Universidades con Carreras en Informática (RedUNCI

Chlamydia trachomatis: pathogen-host cell interplay

Chlamydia trachomatis (Ct) is the most prevalent sexually-transmitted bacterium worldwide. It completes its entire life cycle within human cells, inside of a modified vacuole termed inclusion. As an obligate intracellular pathogen, Ct has evolved multiple strategies to bind to, invade and parasite the host cell. In our laboratory, we aim to describe the interaction of the bacterium and the host from various approaches and scales. We have studied the manipulation of intracellular trafficking pathways executed by the bacterium to, conveniently, prevent its degradation, create a favorable niche for replication and evade the immune defense. In this way, we have reported the active recruitment of several Rab proteins and their effectors (Rab14, FIP2, Rab39a, Rab39b) to the membrane inclusion, a process that results in the acquisition of nutrients essential for growth and replication. Moreover, we study the modulation of signaling pathways (Akt, PKC) during the course of infection that may play a role in the development of Ct. To further complete the study of Ct life cycle in our team, we have described how galectin-1 enhanced its attachment to cervical epithelial cells to promote entry and invasion. A thorough understanding of the epidemiology and biology of Ct is crucial for the improvement of therapeutic strategies. For the former, we have dedicated efforts for the development of diagnostic tools of Ct and other sexually-transmitted pathogens; and for the latter, our laboratory has established a murine model of infection of Ct for in vivo assays of new therapeutic targets.Fil: Alonso Bivou, Mariano Ángel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; ArgentinaFil: del Balzo, Diego Damián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Lujan, Agustin Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Buonfigli, Julio Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Capmany, Anahi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Lucchesi, Ornella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Gambarte Tudela, Julian Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Leiva, Natalia Lorena. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas; ArgentinaFil: Sanchez, D.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Losinno, Antonella Denise. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Damiani, M. T.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; ArgentinaArgentina Symposium on Translational MedicineMendozaArgentinaUniversidad Nacional de Cuyo. Facultad de Ciencias MédicasUniversidad de FriburgoCónsul Honorario de la República Federal de Alemani

Evaluation of stirred yogurts enriched with anthocyanins

Este artículo describe el desarrollo de yogures batidos con valor agregado por adición de extractos de moras, ricos en antocianinas, estabilizados con caseinato de sodio (NaCAS) y microencapsulados por liofilización. Se evalúo el efecto de distintas proporciones de extracto sobre la cinética de acidificación y el pH final de los productos y se compararon las características fisicoquímicas y texturales respecto a yogures control (sin adición de extracto). No se observaron alteraciones significativas en la cinética de coagulación ácida durante la elaboración de los yogures. Tampoco se observaron diferencias significativas en el contenido de sólidos totales, cenizas y proteínas ni en la actividad de agua entre las distintas muestras con respecto a los controles ni entre ellas. Se encontraron algunas modificaciones del color y de algunos parámetros texturales, pero estos fueron dentro de los valores esperados para este tipo de productos.This article describes the development of stirred yogurts with added value by adding blackberry extracts, rich in anthocyanins, stabilized with sodium caseinate (NaCAS), and microencapsulated by lyophilization. The effect of different proportions of the extract on the acidification kinetics, and the final pH of the products, was evaluated. Physicochemical and textural characteristics were compared to control yogurts (without extract). No significant differences in the acidification kinetics were observed during the elaboration of the yogurts. Neither were significant differences observed in the content of total solids, ashes, and proteins or in the water activity between the different samples to the controls or between them. Some changes in color and textural parameters were found, but these were within the expected values for this product type.Fil: Ferreyra, Ornella Noemí. Universidad del Centro Educativo Latinoamericano. Facultad de Química; ArgentinaFil: Cortez Latorre, Juan Diego. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas.; ArgentinaFil: Calderon, Leonardo Martín. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Instituto de Tecnología de los Alimentos; ArgentinaFil: Risso, Patricia Hilda. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; ArgentinaFil: Rozicky, Sergio. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Instituto de Tecnología de los Alimentos; ArgentinaFil: Hidalgo, María Eugenia. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentin

From Cell to Symptoms: The Role of SARS-CoV-2 Cytopathic Effects in the Pathogenesis of COVID-19 and Long COVID

Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) infection triggers var-ious events from the molecular to the tissue level, which in turn is given by the intrinsic character-istics of each patient. Given the molecular diversity characteristic of each cellular phenotype, the possible cytopathic, tissue, and clinical effects are difficult to predict, which determines the hetero-geneity of COVID-19 symptoms. The purpose of this article is to provide a comprehensive review of the cytopathic effects of SARS-CoV-2 on various cell types, focusing on the development of COVID-19, which in turn may lead, in some patients, to the persistence of symptoms after recovery from the disease, a condition known as long COVID. We describe the molecular mechanisms un-derlying virus–host interactions, including alterations in protein expression, intracellular signaling pathways, and immune responses. In particular, the article highlights the potential impact of these cytopathies on cellular function and clinical outcomes, such as immune dysregulation, neuropsy-chiatric disorders, and organ damage. The article concludes by discussing future directions for re-search and implications for the management and treatment of COVID-19 and long COVID