Marcadores patobiológicos y supervivencia en el cáncer colo-rectal. Estudio molecular y topográfico de la beta-catenina, p53 y proteínas reparadoras

El cáncer colo-rectal (CCR) no obedece a una única alteración génica, sino que coexisten varias de ellas en el mismo paciente y el pronóstico/evolución pueden variar dependiendo de las alteraciones detectadas. Existe un elevado número de alteraciones genéticas puntuales, muchas de las cuales se sitúan en la vía de Wnt y afectan a su principal efector: la ß-catenina. Estos tumores son heterogéneos, de tipo morfológico y de carácter biológico ( las variaciones cinéticas propias del componente superficial y zona profunda del tumor). Se ha evaluado el comportamiento biológico de la ß-catenina, y su interacción con p53 y las proteínas reparadoras de errores en la transcripción de ADN, desde un enfoque topográfico, correlacionándolo con otros datos histopatológicos y pronóstico/evolutivos.El CCR es un tumor heterogéneo, advirtiéndose grandes variaciones entre los compartimentos tumorales superficial y profundo.La inmunoexpresión de ß-catenina en el CCR es muy variable, pero, debido a su papel oncogénico y a su relación con otras vías moleculares, juega un papel importante en el pronóstico de los pacientes. Existe mayor relación con el resto de variables -histopatológicas e inmunohistoquímicas- en el compartimento tumoral profundo que en el superficial. La inmunoexpresión de ßcatenina nuclear en el compartimento profundo se ha asociado a peor pronóstico. Las neoplasias con doble negatividad para p53 y ß-catenina en el compartimento profundo son las de peor supervivencia . El mejor pronóstico lo presentan las neoplasias con positividad para p53 y ß-catenina negativa, que sugiere la existencia de un bucle regulador entre p53 y ß-catenina. Concluimos que el análisis combinado de ß-catenina y p53 podría tener importancia pronóstica, como marcadores predictores de la progresión de la enfermedad, e identificar pacientes con alto riesgo de mortalidad

Industrial process monitoring by means of recurrent neural networks and Self Organizing Maps

Industrial manufacturing plants often suffer from reliability problems during their day-to-day operations which have the potential for causing a great impact on the effectiveness and performance of the overall process and the sub-processes involved. Time-series forecasting of critical industrial signals presents itself as a way to reduce this impact by extracting knowledge regarding the internal dynamics of the process and advice any process deviations before it affects the productive process. In this paper, a novel industrial condition monitoring approach based on the combination of Self Organizing Maps for operating point codification and Recurrent Neural Networks for critical signal modeling is proposed. The combination of both methods presents a strong synergy, the information of the operating condition given by the interpretation of the maps helps the model to improve generalization, one of the drawbacks of recurrent networks, while assuring high accuracy and precision rates. Finally, the complete methodology, in terms of performance and effectiveness is validated experimentally with real data from a copper rod industrial plant.Postprint (published version

Alkane-grown Beauveria bassiana produce mycelial pellets displaying peroxisome proliferation, oxidative stress, and cell surface alterations

The entomopathogenic fungus Beauveria bassiana is able to grow on insect cuticle18 hydrocarbons as the sole carbon source, inducing several enzymes involved in alkane19 assimilation and concomitantly increasing virulence against insect hosts. In this study, we20 describe some physiological and molecular processes implicated in growth, nutritional21 stress response, and cellular alterations found in alkane-grown fungi. The fungal cytology22 was investigated using light and transmission electron microscopy (TEM) while the surface23 topography was examined using atomic force microscopy (AFM). Fungal hydrophobicity24 was also measured on the cell surface. Additionally, the expression pattern of several genes25 associated with oxidative stress, peroxisome biogenesis, and hydrophobicity were analysed26 by qPCR. We found a novel type of growth in alkane-cultured B. bassiana similar to27 mycelial pellets described in other alkane-free fungi, which were able to germinate and28 produce viable conidia in media without a carbon source and to be pathogenic against29 larvae of the beetles Tenebrio molitor and Tribolium castaneum. Optical microscopy and30 TEM showed that pellets were formed by hyphae cumulates with high peroxidase activity,31 exhibiting peroxisome proliferation and an apparent surface thickening. Alkane-grown32 conidia appeared to be more hydrophobic and cell surfaces displayed different topography33 than glucose-grown cells, as it was observed by AFM. We also found a significant34 induction in several genes encoding for peroxins, catalases, superoxide dismutases, and35 hydrophobins. These results show that both morphological and metabolic changes are36 triggered in mycelial pellets derived from alkane-grown B. bassiana.Fil: Huarte Bonnet, Carla. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Bioquímicas de La Plata ; ArgentinaFil: Santos Da Paixao, Flavia Regina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Bioquímicas de La Plata ; ArgentinaFil: Ponce, Juan C. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Bioquímicas de La Plata ; ArgentinaFil: Santana, Marianela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Bioquímicas de La Plata ; ArgentinaFil: Prieto, Eduardo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; ArgentinaFil: Pedrini, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Bioquímicas de La Plata ; Argentin

Producto ecológico, sostenible y práctico que busca suplementar las bolsas plásticas

El Objetivo principal de esta tesis es la propuesta de un carro biodegradable que permita suplir las bolsas plásticas en las grandes cadenas de superficie, buscamos que por medio de este producto innovador podamos mejorar las compras para los consumidores y ayudar al medio ambiente en el que vivimos. Por ello pensamos en este producto, mirando primero que todo todas las ventajas que pudieran obtener los consumidores de las grandes cadenas de superficie y por ello nos realizamos ciertas preguntas necesarias y después de ello una investigación muy concreta.Administrador (a) de EmpresasPregrad

Spectroscopy transmittance by LED calibration

Local administrations demand real-time and continuous pollution monitoring in sewer networks. Spectroscopy is a non-destructive technique that can be used to continuously monitor quality in sewers. Covering a wide range of wavelengths can be useful for improving pollution characterization in wastewater. Cost-effective and in-sewer spectrophotometers would contribute to accomplishing discharge requirements. Nevertheless, most available spectrometers are based on incandescent lamps, which makes it unfeasible to place them in a sewerage network for real-time monitoring. This research work shows an innovative calibration procedure that allows (Light-Emitting Diode) LED technology to be used as a replacement for traditional incandescent lamps in the development of spectrophotometry equipment. This involves firstly obtaining transmittance values similar to those provided by incandescent lamps, without using any optical components. Secondly, this calibration process enables an increase in the range of wavelengths available (working range) through a better use of the LED's spectral width, resulting in a significant reduction in the number of LEDs required. Thirdly, this method allows important reductions in costs, dimensions and consumptions to be achieved, making its implementation in a wide variety of environments possible.This research was funded by Seneca Foundation of the Región de Murcia (Spain) and “Hidrogea, Gestión Integral de Aguas de Murcia S.A”. Authors wish to thank the financial support received from the Seneca Foundation of the Región de Murcia (Spain) through the program devoted for training of novel researchers in areas of specific interest for the industry and with a high capacity to transfer the results of the research generate entitled: “Subprograma Regional de Contratos de Formación de Personal Investigador en Universidades y OPIs” (Mod. B, Ref. 20320/FPI/17).Authors wish to thank the financial support received from the Seneca Foundation of the Región de Murcia (Spain) through the program devoted for training of novel researchers in areas of specific interest for the industry and with a high capacity to transfer the results of the research generate entitled: “Subprograma Regional de Contratos de Formación de Personal Investigador en Universidades y OPIs” (Mod. B, Ref. 20320/FPI/17)

Wastewater quality estimation through spectrophotometry-based statistical models

Local administrations are increasingly demanding real-time continuous monitoring of pollution in the sanitation system to improve and optimize its operation, to comply with EU environmental policies and to reach European Green Deal targets. The present work shows a full-scale Wastewater Treatment Plant field-sampling campaign to estimate COD, BOD5, TSS, P, TN and NO3-N in both influent and effluent, in the absence of pre-treatment or chemicals addition to the samples, resulting in a reduction of the duration and cost of analysis. Different regression models were developed to estimate the pollution load of sewage systems from the spectral response of wastewater samples measured at 380-700 nm through multivariate linear regressions and machine learning genetic algorithms. The tests carried out concluded that the models calculated by means of genetic algorithms can estimate the levels of five of the pollutants under study (COD, BOD5, TSS, TN and NO3-N), including both raw and treated wastewater, with an error rate below 4%. In the case of the multilinear regression models, these are limited to raw water and the estimate is limited to COD and TSS, with less than a 0.5% error rateThe authors wish to thank the financial support received from the Seneca Foundation of the Región de Murcia (Spain) through the program devoted to training novel researchers in areas of specific interest for the industry and with a high capacity to transfer the results of the research generated, entitled: “Subprograma Regional de Contratos de Formación de Personal Investigador en Universidades y OPIs” (Mod. B, Ref. 20320/FPI/17)

Performing calibration of transmittance by single rgb-led within the visible spectrum

Spectrophotometry has proven to be an effective non-invasive technique for the characterization of the pollution load of sewer systems, enabling compliance with new environmental protection regulations. This type of equipment has costs and an energy consumption which make it difficult to place it inside a sewer network for real-time and massive monitoring. These shortcomings are mainly due to the use of incandescent lamps to generate the working spectrum as they often require the use of optical elements, such as diffraction gratings, to work. The search for viable alternatives to incandescent lamps is key to the development of portable equipment that is cheaper and with a lower consumption that can be used in different points of the sewer network. This research work achieved the following results in terms of the measured samples: First, the development a calibration procedure that enables the use of RGB-LED technology as a viable alternative to incandescent lamps, within the range of 510 to 645 nm, with high accuracy. Secondly, demonstration of a simple method to model the transmittance value of a specific wavelength without the need for optical elements, achieving a cost-effective equipment. Thirdly, it provides a simple method to obtain the transmittance based on the combination of RGB colors. Finally its viability is demonstrated for the spectral analysis of wastewater.The authors are grateful for the financial support received from the Seneca Foundation of the Región de Murcia (Spain) through the program devoted to training novel researchers in areas of specific interest for the industry and with a high capacity to transfer the results of the research generated, entitled: “Subprograma Regional de Contratos de Formación de Personal Investigador en Universidades y OPIs” (Mod. B, Ref. 20320/FPI/17)

Enhanced Industrial Machinery Condition Monitoring Methodology based on Novelty Detection and Multi-Modal Analysis

This paper presents a condition-based monitoring methodology based on novelty detection applied to industrial machinery. The proposed approach includes both, the classical classification of multiple a priori known scenarios, and the innovative detection capability of new operating modes not previously available. The development of condition-based monitoring methodologies considering the isolation capabilities of unexpected scenarios represents, nowadays, a trending topic able to answer the demanding requirements of the future industrial processes monitoring systems. First, the method is based on the temporal segmentation of the available physical magnitudes, and the estimation of a set of time-based statistical features. Then, a double feature reduction stage based on Principal Component Analysis and Linear Discriminant Analysis is applied in order to optimize the classification and novelty detection performances. The posterior combination of a Feed-forward Neural Network and One-Class Support Vector Machine allows the proper interpretation of known and unknown operating conditions. The effectiveness of this novel condition monitoring scheme has been verified by experimental results obtained from an automotive industry machine.Postprint (published version

Vibration-based adaptive novelty detection method for monitoring faults in a kinematic chain

Postprint (published version