A novel therapy for breast cancer: implications for treatment access

In 2016, there were 250,000 new cases of invasive cancer and 60,000 of ductal carcinoma in situ. Mammograms are used to screen for cases of disease, but the literature shows that mammograms are highly dependent on patient characteristics and do not majorly impact mortality rates from invasive cancer. Additionally, they are prone to false-positives, false-negatives, and overdiagnosis in cases of in situ cancer, with overdiagnosis exposing patients to the side effects of treatment. Better screening tests are needed, and a potential solution can be to extend molecular screening methods often used in advanced stage 1 and higher cancers to stage 0 ductal carcinoma in situ cases. This new test would prevent overdiagnosis, be more accurate, and prevent unnecessary screening as well as be in line with the future of cancer care in the US

Predicción de caudales en río Colorado, Argentina

The identification of suitable models for predicting daily water flow is important for planning and management of water storage in reservoirs of Argentina. Long-term prediction of water flow is crucial for regulating reservoirs and hydroelectric plants, for assessing environmental protection and sustainable development, for guaranteeing correct operation of public water supply in cities like Catriel, 25 de Mayo, Colorado River and potentially also Bahía Blanca. In this paper, we analyze in Buta Ranquil flow time series upstream reservoir and hydroelectric plant in order to model and predict daily fluctuations. We compare results obtained by using a three-layer artificial neural network (ANN), and an autoregressive (AR) model, using 18 years of data, of which the last 3 years are used for model validation by means of the root mean square error (RMSE), and measure of certainty (Skill). Our results point out to the better performance to predict daily water flow or refill them of the ANN model performance respect to the AR model. La identificación de modelos adecuados para predecir caudales diarios es importante para la planificación y la gestión de almacenamiento de agua en los embalses de la Argentina. La predicción a largo plazo del caudal es crucial para la regulación de los embalses y centrales hidroeléctricas, evaluar la protección del medio ambiente y el desarrollo sostenible, garantizar el correcto funcionamiento del abastecimiento público de agua en ciudades como Catriel, 25 de Mayo, río Colorado y también, eventualmente, en Bahía Blanca. En este trabajo, se analizan series de tiempo de caudales de agua, arriba del embalse y de la planta hidroeléctrica en Buta Ranquil, para modelar y predecir las fluctuaciones diarias. Se comparan los resultados obtenidos mediante el uso de una red neuronal artificial (ANN) de tres capas y un modelo autoregresivo (AR), con 18 años de datos, cuyos últimos 3 años se utilizan para la validación del modelo por medio de la raíz del error cuadrado medio (RMSE) y medida de certeza (Skill). Para predecir o rellenar el caudal diario, los resultados indican que el mejor desempeño es del ANN con respecto al modelo AR.Fil: Pierini, Jorge Omar. Universidad Nacional del Sur; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaFil: Gomez, Eduardo Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. Universidad Tecnologica Nacional; ArgentinaFil: Telesca, Luciano. Istituto di Metodologie per l’Analisi Ambientale; Itali

Synthesis of a metal oxide by forming solvate eutectic mixtures and study of their synthetic performance under hyper- and hypo-eutectic conditions

The synthesis of YBa2Cu3O7−x (YBCO or 123) superconductor was carried out under hyper- and hypo-eutectic conditions with different ammonium compounds, i.e., ammonium nitrate, formate, acetate, carbonate, bicarbonate, and tetramethylammonium nitrate. The aim was to find more affordable synthetic pathways using highly available and cheaper compounds, as well as to study the crystal formation under no-carbon conditions when ammonium nitrate was employed. Best results were obtained when eutectic conditions were achieved, namely by ammonium nitrate and YBaCu nitrates in a 5:1 molar ratio (81% of the superconductor). Ammonium formate, acetate, carbonate, and bicarbonate did not produce eutectic mixes. Temperature analysis of the reaction carried out by ammonium nitrate/YBaCu nitrates indicated the formation of barium carbonate, despite no carbon source being used in this reaction. This phenomenon is further discussed in this work. Consequently, tetramethylammonium nitrate, as a chelator and carbon source, was used, providing >96% of the superconductor

Assessment of Fetal Alcohol Spectrum Disorders

Fetal alcohol spectrum disorders (FASD) represent a range of physical, mental, and behavioral disabilities caused by alcohol use during pregnancy, or prenatal alcohol exposure (PAE). FASDs are considered to be one of the leading preventable causes of developmental disability. Despite its high prevalence, FASD is often misdiagnosed or underdiagnosed, making interventions more challenging or delayed. Earlier diagnosis yields greater benefits for affected children, which include a reduction in secondary disabilities such as substance use disorders and learning and cognitive disabilities leading to school failure, and improved life outcomes. Most importantly, diagnosis provides a context for understanding a child’s behavior. When the environment surrounding a child with an FASD opts to focus on the child’s strengths as a means for intervention, there is a greater likelihood of that child achieving success as an adult. Diagnosis of FASD is further beneficial to the extent that it leads to a reduction of future births of children with FASD. This publication was initially developed for use in Spanish-speaking countries of the Americas and is intended to serve as a training workbook for providers of various disciplines to learn about the fundamentals of diagnosing FASD and to apply them to several case scenarios. It also discusses ethical implications of diagnosing FASD to the mother and child. Target audiences include physicians, psychologists, allied health professionals, social workers, and other providers that may encounter individuals affected by FASD. It is ideally used as a supplement for in-person training by experts in the fields of dysmorphology, epidemiology, and neuropsychology.https://digitalcommons.unmc.edu/mmi_books/1000/thumbnail.jp

Investigating Prediction Performance of an Artificial Neural Network and a Numerical Model of the Tidal Signal at Puerto Belgrano, Bahia Blanca Estuary (Argentina)

In the present study we compare performances of the prediction of hourly tidal level variations at Puerto Belgrano, a coastal site in the Bahia Blanca Estuary (Argentina), by means of the MOHID model, which is a numerical model designed for coastal and estuarine shallow water applications, and of an artificial neural network (ANN). It was shown that the ANN model is able to predict the hourly tidal levels over long term duration with at least seven days of observations and with a better performance in respect to the numerical model. Our findings can be useful to implement ANN-based tools for future studies of the hydrodynamics of Bahía Blanca estuary.Fil: Pierini, Jorge Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto Argentino de Oceanografía (i); ArgentinaFil: Lovallo, Michele. Agenzia Regionale per la Protezione dell’Ambiente; ItaliaFil: Telesca, Luciano. National Research Council, Institute of Methodologies for Environmental Analysis; ItaliaFil: Gomez, Eduardo Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto Argentino de Oceanografía (i); Argentin