The role of cell death and myofibrillar damage in contractile dysfunction of long-term cultured adult cardiomyocytes exposed to doxorubicin

In failing hearts cardiomyocytes undergo alterations in cytoskeleton structure, contractility and viability. It is not known presently, how stress-induced changes of myofibrils correlate with markers for cell death and contractile function in cardiomyocytes. Therefore, we have studied the progression of contractile dysfunction, myofibrillar damage and cell death in cultured adult cardiomyocytes exposed to the cancer therapy doxorubicin. We demonstrate, that long-term cultured adult cardiomyocytes, a well-established model for the study of myofibrillar structure and effects of growth factors, can also be used to assess contractility and calcium handling. Adult rat ventricular myocytes (ARVM) were isolated and cultured for a total of 14 days in serum containing medium. The organization of calcium-handling proteins and myofibrillar structure in freshly isolated and in long-term cultured adult cardiomyocytes was studied by immunofluorescence and electron microscopy. Excitation contraction-coupling was analyzed by fura 2 and video edge detection in electrically paced cardiomyocytes forming a monolayer, and cell death and viability was measured by TUNEL assay, LDH release, MTT assay, and Western blot for LC3. Adult cardiomyocytes treated with Doxo showed apoptosis and necrosis only at supraclinical concentrations. Treated cells displayed merely alterations in cytoskeleton organization and integrity concomitant with contractile dysfunction and up-regulation of autophagosome formation, but no change in total sarcomeric protein content. We propose, that myofibrillar damage contributes to contractile dysfunction prior to cell death in adult cardiomyocytes exposed to clinically relevant concentrations of anthracyclines.

Quantification of dental erosions in patients with GERD using optical coherence tomography before and after double-blind, randomized treatment with esomeprazole or placebo

OBJECTIVES: Dental erosion, the chemical dissolution of enamel without bacterial involvement, is a rarely reported manifestation of gastroesophageal reflux disease (GERD), as well as of recurrent vomiting and dietary habits. It leads to loss of tooth substance, hypersensitivity, functional impairment, and even tooth fracture. To date, dental erosions have been assessed using only very basic visual methods, and no evidence-based guidelines or studies exist regarding the prevention or treatment of GERD-related dental erosions. METHODS: In this randomized, double-blind study, we used optical coherence tomography (OCT) to quantify dental tissue demineralization and enamel loss before and after 3 weeks of acid-suppressive treatment with esomeprazole 20 mg b.i.d. or placebo in 30 patients presenting to the Berne University Dental Clinic with advanced dental erosions and abnormal acid exposure by 24-h esophageal pH manometry (defined as >4% of the 24-h period with pH<4). Enamel thickness, reflectivity, and absorbance as measures of demineralization were quantified by OCT before and after therapy at identical localizations on teeth with most severe visible erosions as well as several other predefined changes in teeth. RESULTS: The mean+/-s.e.m. decrease of enamel thickness of all teeth before and after treatment at the site of maximum exposure was 7.2+/-0.16 black trianglem with esomeprazole and 15.25+/-0.17black trianglem with placebo (P=0.013), representing a loss of 0.3% and 0.8% of the total enamel thickness, respectively. The change in optical reflectivity to a depth of 25 black trianglem after treatment was-1.122 +/-0.769 dB with esomeprazole and +2.059+/-0.534 dB with placebo (P 0.012), with increased reflectivity signifying demineralization. CONCLUSIONS: OCT non-invasively detected and quantified significantly diminished progression of dental tissue demineralization and enamel loss after only 3 weeks of treatment with esomeprazole 20 mg b.i.d. vs. placebo. This suggests that esomeprazole may be useful in counteracting progression of GERD-related dental erosions. Further validation of preventative treatment regimens using this sensitive detection method is required, including longer follow-up and correlation with quantitative reflux measures.

Quantification of global DNA methylation with infrared fluorescence in liver and muscle tissues of differentially fed boars

Methylation of cytosine residues at CpG sites is involved in various biological processes to control gene regulation and gene expression. Global DNA methylation is changed in different tumors and in cloned animals. Global DNA methylation can be accurately quantified by dot blot analysis with infrared (IR) fluorophores. Methylated lambda DNA was used as model DNA to develop and validate an immunochemical assay with IR fluorescence detection. Two different IR fluorophores were used, one to detect 5-methylcytosine and another to account for DNA loading. A sensitive infrared detection method was established which is suitable for accurate and reproducible quantification of global DNA methylation across a wide dynamic range. This method was subsequently employed to quantify global DNA methylation in liver and in muscle tissues of boars which have received either a control diet or a methyl supplemented diet in an ongoing study. A significant difference in global DNA methylation is indicated in muscle but not in liver tissue between the two groups of boars.

Detecting outlying studies in meta-regression models using a forward search algorithm.

When considering data from many trials, it is likely that some of them present a markedly different intervention effect or exert an undue influence on the summary results. We develop a forward search algorithm for identifying outlying and influential studies in meta-analysis models. The forward search algorithm starts by fitting the hypothesized model to a small subset of likely outlier-free studies and proceeds by adding studies into the set one-by-one that are determined to be closest to the fitted model of the existing set. As each study is added to the set, plots of estimated parameters and measures of fit are monitored to identify outliers by sharp changes in the forward plots. We apply the proposed outlier detection method to two real data sets; a meta-analysis of 26 studies that examines the effect of writing-to-learn interventions on academic achievement adjusting for three possible effect modifiers, and a meta-analysis of 70 studies that compares a fluoride toothpaste treatment to placebo for preventing dental caries in children. A simple simulated example is used to illustrate the steps of the proposed methodology, and a small-scale simulation study is conducted to evaluate the performance of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.

CHEOPS Performance for Exomoons: The Detectability of Exomoons by Using Optimal Decision Algorithm

Many attempts have already been made to detect exomoons around transiting exoplanets, but the first confirmed discovery is still pending. The experiences that have been gathered so far allow us to better optimize future space telescopes for this challenge already during the development phase. In this paper we focus on the forthcoming CHaraterising ExOPlanet Satellite (CHEOPS), describing an optimized decision algorithm with step-by-step evaluation, and calculating the number of required transits for an exomoon detection for various planet moon configurations that can be observable by CHEOPS. We explore the most efficient way for such an observation to minimize the cost in observing time. Our study is based on PTV observations (photocentric transit timing variation) in simulated CHEOPS data, but the recipe does not depend on the actual detection method, and it can be substituted with, e.g., the photodynamical method for later applications. Using the current state-of-the-art level simulation of CHEOPS data we analyzed transit observation sets for different star planet moon configurations and performed a bootstrap analysis to determine their detection statistics. We have found that the detection limit is around an Earth-sized moon. In the case of favorable spatial configurations, systems with at least a large moon and a Neptune-sized planet, an 80% detection chance requires at least 5-6 transit observations on average. There is also a nonzero chance in the case of smaller moons, but the detection statistics deteriorate rapidly, while the necessary transit measurements increase quickly. After the CoRoT and Kepler spacecrafts, CHEOPS will be the next dedicated space telescope that will observe exoplanetary transits and characterize systems with known Doppler-planets. Although it has a smaller aperture than Kepler (the ratio of the mirror diameters is about 1/3) and is mounted with a CCD that is similar to Kepler's, it will observe brighter stars and operate with larger sampling rate; therefore, the detection limit for an exomoon can be the same as or better, which will make CHEOPS a competitive instruments in the quest for exomoons.

Identification of micro-RNAs targeting genes of PI3K/AKT pathway in ovarian cancer

Ovarian cancer is the leading cause of cancer-related death for females due to lack of specific early detection method. It is of great interest to find molecular-based biomarkers which are sensitive and specific to ovarian cancer for early diagnosis, prognosis and therapeutics. miRNAs have been proposed to be potential biomarkers that could be used in cancer prevention and therapeutics. The current study analyzed the miRNA and mRNA expression data extracted from the Cancer Genome Atlas (TCGA) database. Using simple linear regression and multiple regression models, we found 71 miRNA-mRNA pairs which were negatively associated between 56 miRNAs and 24 genes of PI3K/AKT pathway. Among these miRNA and mRNA target pairs, 9 of them were in agreement with the predictions from the most commonly used target prediction programs including miRGen, miRDB, miRTarbase and miR2Disease. These shared miRNA-mRNA pairs were considered to be the most potential genes that were involved in ovarian cancer. Furthermore, 4 of the 9 target genes encode cell cycle or apoptosis related proteins including Cyclin D1, p21, FOXO1 and Bcl2, suggesting that their regulator miRNAs including miR-16, miR-96 and miR-21 most likely played important roles in promoting tumor growth through dysregulated cell cycle or apoptosis. miR-96 was also found to directly target IRS-1. In addition, the results showed that miR-17 and miR-9 may be involved in ovarian cancer through targeting JAK1. This study might provide evidence for using miRNA or miRNA profile as biomarker.^

Mapping decadal land cover changes in the woodlands of north eastern Namibia using the Landsat satellite archive (1975-2014)

Woodland savannahs provide essential ecosystem functions and services to communities. On the African continent, they are widely utilized and converted to intensive land uses. This study investigates the land cover changes of 108,038 km**2 in NE Namibia using multi-temporal, multi-sensor Landsat imagery, at decadal intervals from 1975 to 2014, with a post-classification change detection method and supervised Regression Tree classifiers. We discuss likely impacts of land tenure and reforms over the past four decades on changes in land use and land cover. These changes included losses, gains and exchanges between predominant land cover classes. Exchanges comprised logical conversions between woodland and agricultural classes, implying woodland clearing for arable farming, cropland abandonment and vegetation succession. The most dominant change was a reduction in the area of the woodland class due to the expansion of the agricultural class, specifically, small-scale cereal and pastoral production. Woodland area decreased from 90% of the study area in 1975 to 83% in 2014, while cleared land increased from 9% to 14%. We found that the main land cover changes are conversion from woodland to agricultural and urban land uses, driven by urban expansion and woodland clearing for subsistence-based agriculture and pastoralism.

Identificación y reconocimiento de matrículas de automóviles con MATLAB

Este Proyecto Fin de Carrera trata sobre el reconocimiento e identificación de caracteres de matrículas de automóviles. Este tipo de sistemas de reconocimiento también se los conoce mundialmente como sistemas ANPR ("Automatic Number Plate Recognition") o LPR ("License Plate Recognition"). La gran cantidad de vehículos y logística que se mueve cada segundo por todo el planeta, hace necesaria su registro para su tratamiento y control. Por ello, es necesario implementar un sistema que pueda identificar correctamente estos recursos, para su posterior procesado, construyendo así una herramienta útil, ágil y dinámica. El presente trabajo ha sido estructurado en varias partes. La primera de ellas nos muestra los objetivos y las motivaciones que se persiguen con la realización de este proyecto. En la segunda, se abordan y desarrollan todos los diferentes procesos teóricos y técnicos, así como matemáticos, que forman un sistema ANPR común, con el fin de implementar una aplicación práctica que pueda demostrar la utilidad de estos en cualquier situación. En la tercera, se desarrolla esa parte práctica en la que se apoya la base teórica del trabajo. En ésta se describen y desarrollan los diversos algoritmos, creados con el fin de estudiar y comprobar todo lo planteado hasta ahora, así como observar su comportamiento. Se implementan varios procesos característicos del reconocimiento de caracteres y patrones, como la detección de áreas o patrones, rotado y transformación de imágenes, procesos de detección de bordes, segmentación de caracteres y patrones, umbralización y normalización, extracción de características y patrones, redes neuronales, y finalmente el reconocimiento óptico de caracteres o comúnmente conocido como OCR. La última parte refleja los resultados obtenidos a partir del sistema de reconocimiento de caracteres implementado para el trabajo y se exponen las conclusiones extraídas a partir de éste. Finalmente se plantean las líneas futuras de mejora, desarrollo e investigación, para poder realizar un sistema más eficiente y global. This Thesis deals about license plate characters recognition and identification. These kinds of systems are also known worldwide as ANPR systems ("Automatic Number Plate Recognition") or LPR ("License Plate Recognition"). The great number of vehicles and logistics moving every second all over the world, requires a registration for treatment and control. Thereby, it’s therefore necessary to implement a system that can identify correctly these resources, for further processing, thus building a useful, flexible and dynamic tool. This work has been structured into several parts. The first one shows the objectives and motivations attained by the completion of this project. In the second part, it’s developed all the different theoretical and technical processes, forming a common ANPR system in order to implement a practical application that can demonstrate the usefulness of these ones on any situation. In the third, the practical part is developed, which is based on the theoretical work. In this one are described and developed various algorithms, created to study and verify all the questions until now suggested, and complain the behavior of these systems. Several recognition of characters and patterns characteristic processes are implemented, such as areas or patterns detection, image rotation and transformation, edge detection processes, patterns and character segmentation, thresholding and normalization, features and patterns extraction, neural networks, and finally the optical character recognition or commonly known like OCR. The last part shows the results obtained from the character recognition system implemented for this thesis and the outlines conclusions drawn from it. Finally, future lines of improvement, research and development are proposed, in order to make a more efficient and comprehensive system.

Tracking recurrent concepts using context

The problem of recurring concepts in data stream classification is a special case of concept drift where concepts may reappear. Although several existing methods are able to learn in the presence of concept drift, few consider contextual information when tracking recurring concepts. Nevertheless, in many real-world scenarios context information is available and can be exploited to improve existing approaches in the detection or even anticipation of recurring concepts. In this work, we propose the extension of existing approaches to deal with the problem of recurring concepts by reusing previously learned decision models in situations where concepts reappear. The different underlying concepts are identified using an existing drift detection method, based on the error-rate of the learning process. A method to associate context information and learned decision models is proposed to improve the adaptation to recurring concepts. The method also addresses the challenge of retrieving the most appropriate concept for a particular context. Finally, to deal with situations of memory scarcity, an intelligent strategy to discard models is proposed. The experiments conducted so far, using synthetic and real datasets, show promising results and make it possible to analyze the trade-off between the accuracy gains and the learned models storage cost.

Atmospheric attenuation at 100 and 300 GHz estimated with radiosonde data

The study of atmospheric propagation impairments at submillimeter and THz frequencies is becoming increasingly relevant due to the strong effects caused by the composition of the troposphere and the phenomena occurring in it. The present paper is devoted to the estimation of total attenuation at 100 GHz and 300 GHz under non-rainy scenarios. With this purpose, 4 years of meteorological data from Madrid have been collected, including radiosoundings from Madrid-Barajas Airport and co-site SYNOP observations. This volume of data has been analyzed with the aim of also introducing a detection method of rain conditions, which cannot be easily identified in radiosounding profiles. Finally, the method has been used to discard several probable events which would be responsible of scattering conditions and, hence, yearly CDFs of total attenuation have been obtained. It is expected that the statistics would be closest to the ones obtained by experimental techniques under similar atmospheric conditions.

New analysis and estimations of atmospheric attenuation at 100 GHz using meteorological data in Madrid

Atmospheric propagation at frequencies within the THz domain are deeply affected by the influence of the composition and phenomena of the troposphere. This paper is focused on the estimation of first order statistics of total attenuation under non-rainy conditions at 100 GHz. With this purpose, a yearly meteorological database from Madrid, including radiosoundings, SYNOP observations and co-site rain gauge, have been used in order to calculate attenuation due to atmospheric gases and clouds, as well as to introduce and evaluate a rain detection method. This method allows to filter out rain events and refine the statistics of total attenuation under the scenarios under study. It is expected that the behavior of the statistics would be closest to the ones obtained by experimental techniques under similar conditions.

Multiobjective structural damage identification in uncertain environments

Evolutionary algorithms are suitable to solve damage identification problems in a multiobjective context. However, the performance of these methods can deteriorate quickly with increasing noise intensities originating numerous uncertainties. In this paper, a statistic structural damage detection method formulated in a multiobjective context is proposed. The statistic analysis is implemented to take into account the uncertainties existing in the structural model and measured structural modal parameters. The presented method is verified by a number of simulated damage scenarios. The effects of noise and damage levels on damage detection are investigated.