Utilizando el modelo satelital GL 1.2 en escala diaria como referencia para calibración provisoria de la red EEAOC - Tucumán

En Tucumán, la Estación Experimental Agroindustrial "Obispo Colombres" (EEAOC) dispone de una red de estaciones meteorológicas automáticas con generación continua de datos de irradiancia solar. En este trabajo se contrastan las irradiancias medias diarias de 18 estaciones (período 2017-2021) con los valores obtenidos por el modelo satelital GL1.2 desarrollado en la División de Satélites e Sensores Meteorológicos (DISSM/CGCT/INPE, Brasil). Este modelo ya mostró un buen desempeño en la comparación con datos de piranómetros Kipp & Zonen CM6B y CMP6 de la red automática del INMET (Instituto Nacional de meteorología, Brasil). Se realizó un análisis preliminar de la calidad del GL1.2, comparándolo con datos diarios (primer semestre de 2018) de la red del INMET en una región relativamente homogénea del Brasil en latitud semejante a la de Tucumán, obteniéndose un buen ajuste, por lo que se adoptó el GL1.2 como "piranómetro de referencia" para una calibración provisoria de los datos solarimétricos diarios de la red EEAOC. Los resultados de los estadísticos utilizados para juzgar el ajuste lineal EEAOC vs. GL 1.2 sugieren que el modelo satelital puede utilizarse para la calibración provisoria de la red de Tucumán, con dispersión típica (desviación estándar) de 20 W/m2

Algunas características del régimen de radiación solar global en el Noroeste Argentino, período 2017-2021

El modelo satelital GL1.2 evalúa irradiancia solar global con alta resolución espacial y error relativamente reducido al considerar promedios mensuales. En este trabajo es aplicado a la región Noroeste de Argentina en el quinquenio 2017-2021 para describir detalles del régimen regional de radiación solar difícilmente discernibles por la poco densa red de solarimetría. El análisis en componentes principales (ACP) muestra que la primera componente (CP1) describe la serie temporal normalizada de 5 años con más de 70% de contribución a la variancia local, excepto en la transición llanura-montaña (piedemonte). En esa región, las componentes CP2 a CP5 acumuladas responden por 95% de la variancia regional. En términos generales, la secuencia normalizada de irradiancia media mensual es adecuadamente descripta por las cinco primeras CPs en toda la región. Los resultados implican en que un número reducido de archivos digitales puede ser utilizado para describir la serie temporal de promedios mensuales con resolución espacial de 0,04° y errores de estimación del orden de 20% del desvío estándar de la serie, o sea, unos 12 W m-2

Radiación solar en la provincia de Tucumán: una comparación entre valores estimados por satélite y medidos por una red solarimétrica

El modelo GL/CPTEC de estimación de radiación solar utiliza imágenes del satélite GOES (canal VIS) para América del Sur, procesándolas en régimen operacional. Los valores estimados para el área del Noroeste Argentino fueron comparados con medidas realizadas en 17 estaciones de la red de estaciones automáticas de la Estación Experimental Agroindustrial Obispo Colombres (EEAOC). Los valores diarios de GL en el trimestre octubre-diciembre de 2010 presentan elevada linealidad (R2>0,93) al comparar con mediciones de la red. En general, promedios trimestrales difieren en menos de 4% en la llanura tucumana y en la región montañosa, y en 4-7% en la región del pedemonte, cercana a la cadena del Aconquija. La desviación estándar de valores diarios en torno del desvío sistemático es de 20-35 W.m-2. Los campos de radiación mensual permiten discernir variaciones espaciales significativas en escala de algunas decenas de kilómetros. Son analizadas algunas fuentes de error y métodos de perfeccionamiento.Model GL/CPTEC assesses solar irradiance using GOES-VIS imagery for South America, being run in a operational scheme. Resultant GL values for Argentine Northwest region were compared with measurements at 17 automatic stations operated by Estación Experimental Agroindustrial Obispo Colombres. Daily GL values during three-month period October-December 2010 exhibit high linearity (R2>0.93) when compared with EEAOC network. Three-month mean values differ fom EEAOC means by less than 4% over eastern Tucumán and by 4-7% nearby mountainous Aconquija slope. Standard deviation of daily values around mean deviation is about 20-35 W.m-2. Monthly mean fields allow discern for space variability meaningful in a several ten-kilometers scale. Some error sources and quality improvements are analyzed.Asociación Argentina de Energías Renovables y Medio Ambiente (ASADES

A 3D Pancreatic Cancer Model with Integrated Optical Sensors for Noninvasive Metabolism Monitoring and Drug Screening

A distinct feature of pancreatic ductal adenocarcinoma (PDAC) is a prominent tumor microenvironment (TME) with remarkable cellular and spatial heterogeneity that meaningfully impacts disease biology and treatment resistance. The dynamic crosstalk between cancer cells and the dense stromal compartment leads to spatially and temporally heterogeneous metabolic alterations, such as acidic pH that contributes to drug resistance in PDAC. Thus, monitoring the extracellular pH metabolic fluctuations within the TME is crucial to predict and to quantify anticancer drug efficacy. Here, a simple and reliable alginate-based 3D PDAC model embedding ratiometric optical pH sensors and cocultures of tumor (AsPC-1) and stromal cells for simultaneously monitoring metabolic pH variations and quantify drug response is presented. By means of time-lapse confocal laser scanning microscopy (CLSM) coupled with a fully automated computational analysis, the extracellular pH metabolic variations are monitored and quantified over time during drug testing with gemcitabine, folfirinox, and paclitaxel, commonly used in PDAC therapy. In particular, the extracellular acidification is more pronounced after drugs treatment, resulting in increased antitumor effect correlated with apoptotic cell death. These findings highlight the importance of studying the influence of cellular metabolic mechanisms on tumor response to therapy in 3D tumor models, this being crucial for the development of personalized medicine approaches

Emergent behaviour and phase transitions in spatially distributed multi-cellular metabolic networks

Overflow metabolism is a ubiquitous phenomenon whereby cells in aerobic conditions excrete byproducts of glycolysis, such as lactate or acetate, into the medium in a seemingly wasteful and polluting fashion. Whilst overflow may confer microbes a fitness advantage by allowing them to overcome a finite oxidative capacity, its occurrence in higher organisms is harder to assess. Important insight was however obtained in recent experiments conducted at single-cell resolution, which revealed that accumulation of overflow products in tumor cell cultures known as the Warburg effect arises from imbalances in the dynamic and heterogeneous inter-cellular exchange network through which cells collectively regulate the microenvironment. Here we provide a quantitative characterization of this scenario by integrating metabolic network modeling with diffusion constraints, statistical physics theory and single-cell experimental flux data. On the theoretical side, we clarify how diffusion-limited exchanges shape the space of viable metabolic states of a multi-cellular system. Specifically, a phase transition from a balanced network of exchanges to an unbalanced overflow regime occurs as the mean cellular glucose and oxygen uptakes vary while single-cell metabolic phenotypes are highly heterogeneous around this transition. We then show that time-resolved data from human tumor-stroma cell co-cultures consistently map to this crossover region, supporting the idea that environmental deterioration reflects a failure of coordination among recurrently interacting cells. In summary, our findings suggest that, rather than deriving from multiple independent cell-autonomous processes, environmental control is an emergent feature of multi-cellular systems.Comment: Main(14 pages)+ supporting information(14 pages). Comments are welcom

Highly Sensitive Ratiometric Fluorescent Fiber Matrixes for Oxygen Sensing with Micrometer-Spatial Resolution

Oxygen (O2)-sensing matrices are promising tools for the live monitoring of extracellular O2 consumption levels in long-term cell cultures. In this study, ratiometric O2-sensing membranes were prepared by electrospinning, an easy, low-cost, scalable, and robust method for fabricating nanofibers. Poly({\epsilon}-caprolactone) and poly(dimethyl)siloxane polymers were blended with tris(4,7-diphenyl-1,10-phenanthroline) ruthenium(II) dichloride, which was used as the O2-sensing probe, and rhodamine B isothiocyanate, which was used as the reference dye. The functionalized scaffolds were morphologically characterized by scanning electron microscopy, and their physicochemical profiles were obtained by Fourier transform infrared spectroscopy, thermogravimetric analysis, and water contact angle measurement. The sensing capabilities were investigated by confocal laser scanning microscopy, performing photobleaching, reversibility, and calibration curve studies toward different dissolved O2 (DO) concentrations. Electrospun sensing nanofibers showed a high response to changes in DO concentrations in the physiological-pathological range from 0.5 to 20% and good stability under ratiometric imaging. In addition, the sensing systems were highly biocompatible for cell growth promoting adhesiveness and growth of three cancer cell lines, namely metastatic melanoma cell line SK-MEL2, breast cancer cell line MCF-7, and pancreatic ductal adenocarcinoma cell line Panc-1, thus recreating a suitable biological environment in vitro. These O2-sensing biomaterials can potentially measure alterations in cell metabolism caused by changes in ambient O2 content during drug testing/validation and tissue regeneration processes.Comment: 15 pages, 4 figure

The Effectiveness of NIV and CPAP Training on the Job in COVID-19 Acute Care Wards: A Nurses’ Self-Assessment of Skills

Background: Noninvasive ventilation (NIV) in COVID-19 patients outside of intensive care unit (ICU) settings was a feasible support during the pandemic outbreak. The aim of this study was to assess the effectiveness of an “on the job” NIV training program provided to 66 nurses working in 3 COVID-19 wards in an Italian university hospital. Methods: A quasi-experimental longitudinal before–after study was designed. The NIV Team education program, provided by expert ICU nurses, included: 3 h sessions of training on the job during work-shifts about the management of helmet-continuous positive airway pressure (CPAP) Venturi systems, and NIV with oronasal and full-face masks. An eleven-item “brief skills self-report tool” was administered before and after the program to explore the perception of NIV education program attendees about their level of skills. Results: In total, 59 nurses responded to the questionnaire. There was an improvement in the skill levels of the management of Helmet-CPAP (median before training 2, inter-quartile range (IQR) 0–6; median after training 8, IQR 3–9; p < 0.0001), and mask-NIV (median before training 2, IQR 0–6; median after training 8, IQR 3–9; p < 0.0001). Conclusions: Training on the job performed by expert ICU nurses can be a valuable and fast means to implement new Helmet-CPAP and mask-NIV skills outside of ICUs

Radiación solar en la provincia de Tucumán: una comparación entre valores estimados por satélite y medidos por una red solarimétrica

El modelo GL/CPTEC de estimación de radiación solar utiliza imágenes del satélite GOES (canal VIS) para América del Sur, procesándolas en régimen operacional. Los valores estimados para el área del Noroeste Argentino fueron comparados con medidas realizadas en 17 estaciones de la red de estaciones automáticas de la Estación Experimental Agroindustrial Obispo Colombres (EEAOC). Los valores diarios de GL en el trimestre octubre-diciembre de 2010 presentan elevada linealidad (R2>0,93) al comparar con mediciones de la red. En general, promedios trimestrales difieren en menos de 4% en la llanura tucumana y en la región montañosa, y en 4-7% en la región del pedemonte, cercana a la cadena del Aconquija. La desviación estándar de valores diarios en torno del desvío sistemático es de 20-35 W.m-2. Los campos de radiación mensual permiten discernir variaciones espaciales significativas en escala de algunas decenas de kilómetros. Son analizadas algunas fuentes de error y métodos de perfeccionamiento.Model GL/CPTEC assesses solar irradiance using GOES-VIS imagery for South America, being run in a operational scheme. Resultant GL values for Argentine Northwest region were compared with measurements at 17 automatic stations operated by Estación Experimental Agroindustrial Obispo Colombres. Daily GL values during three-month period October-December 2010 exhibit high linearity (R2>0.93) when compared with EEAOC network. Three-month mean values differ fom EEAOC means by less than 4% over eastern Tucumán and by 4-7% nearby mountainous Aconquija slope. Standard deviation of daily values around mean deviation is about 20-35 W.m-2. Monthly mean fields allow discern for space variability meaningful in a several ten-kilometers scale. Some error sources and quality improvements are analyzed.Asociación Argentina de Energías Renovables y Medio Ambiente (ASADES

Probing Single-Cell Fermentation Fluxes and Exchange Networks via pH-Sensing Hybrid Nanofibers

The homeostatic control of their environment is an essential task of living cells. It has been hypothesized that, when microenvironmental pH inhomogeneities are induced by high cellular metabolic activity, diffusing protons act as signaling molecules, driving the establishment of exchange networks sustained by the cell-to-cell shuttling of overflow products such as lactate. Despite their fundamental role, the extent and dynamics of such networks is largely unknown due to the lack of methods in single-cell flux analysis. In this study, we provide direct experimental characterization of such exchange networks. We devise a method to quantify single-cell fermentation fluxes over time by integrating high-resolution pH microenvironment sensing via ratiometric nanofibers with constraint-based inverse modeling. We apply our method to cell cultures with mixed populations of cancer cells and fibroblasts. We find that the proton trafficking underlying bulk acidification is strongly heterogeneous, with maximal single-cell fluxes exceeding typical values by up to 3 orders of magnitude. In addition, a crossover in time from a networked phase sustained by densely connected "hubs" (corresponding to cells with high activity) to a sparse phase dominated by isolated dipolar motifs (i.e., by pairwise cell-to-cell exchanges) is uncovered, which parallels the time course of bulk acidification. Our method addresses issues ranging from the homeostatic function of proton exchange to the metabolic coupling of cells with different energetic demands, allowing for real-time noninvasive singlecell metabolic flux analysis