Integrating quantitative proteomics and metabolomics in a cellular model of diabetic retinopathy

Diabetic retinopathy is the leading cause of visual loss in individuals under the age of 55. Most investigations into the pathogenesis of diabetic retinopathy have been concentrated on the neural retina since this is where clinical lesions are manifested. Recently, however, various abnormalities in the structural and secretory functions of retinal pigment epithelium that are essential for neuroretina survival, have been found in diabetic retinopathy. In this context, here we study the effect of hyperglycemic and hypoxic conditions on the metabolism of a human retinal pigment epithelial cell line (ARPE-19) by integrating quantitative proteomics using tandem mass tagging (TMT), untargeted metabolomics using MS and NMR, and 13C-glucose isotopic labeling for metabolic tracking. We observed a remarkable metabolic diversification under our simulated in vitro hyperglycemic conditions of diabetes, characterized increased flux through polyol pathways and inhibition of the Krebs cycle and oxidative phosphorylation. Importantly, under low oxygen supply RPE cells seem to consume rapidly glycogen storages and stimulate anaerobic glycolysis. Our results therefore pave the way to future scenarios involving new therapeutic strategies addressed to modulating RPE metabolic impairment, with the aim of regulating structural and secretory alterations of RPE. Finally, this study shows the importance of tackling biomedical problems by integrating metabolomic and proteomics results.

Quantitative analysis of image factors in a cultural heritage tourist destination

The tourism consumer’s purchase decision process is, to a great extent, conditioned by the image the tourist has of the different destinations that make up his or her choice set. In a highly competitive international tourist market, those responsible for destinations’ promotion and development policies seek differentiation strategies so that they may position the destinations in the most suitable market segments for their product in order to improve their attractiveness to visitors and increase or consolidate the economic benefits that tourism activity generates in their territory. To this end, the main objective we set ourselves in this paper is the empirical analysis of the factors that determine the image formation of Tarragona city as a cultural heritage destination. Without a doubt, UNESCO’s declaration of Tarragona’s artistic and monumental legacies as World Heritage site in the year 2000 meant important international recognition of the quality of the cultural and patrimonial elements offered by the city to the visitors who choose it as a tourist destination. It also represents a strategic opportunity to boost the city’s promotion of tourism and its consolidation as a unique destination given its cultural and patrimonial characteristics. Our work is based on the use of structured and unstructured techniques to identify the factors that determine Tarragona’s tourist destination image and that have a decisive influence on visitors’ process of choice of destination. In addition to being able to ascertain Tarragona’s global tourist image, we consider that the heterogeneity of its visitors requires a more detailed study that enables us to segment visitor typology. We consider that the information provided by these results may prove of great interest to those responsible for local tourism policy, both when designing products and when promoting the destination.

Study and implementation of some quantitative trading models

Quantitative or algorithmic trading is the automatization of investments decisions obeying a fixed or dynamic sets of rules to determine trading orders. It has increasingly made its way up to 70% of the trading volume of one of the biggest financial markets such as the New York Stock Exchange (NYSE). However, there is not a signi cant amount of academic literature devoted to it due to the private nature of investment banks and hedge funds. This projects aims to review the literature and discuss the models available in a subject that publications are scarce and infrequently. We review the basic and fundamental mathematical concepts needed for modeling financial markets such as: stochastic processes, stochastic integration and basic models for prices and spreads dynamics necessary for building quantitative strategies. We also contrast these models with real market data with minutely sampling frequency from the Dow Jones Industrial Average (DJIA). Quantitative strategies try to exploit two types of behavior: trend following or mean reversion. The former is grouped in the so-called technical models and the later in the so-called pairs trading. Technical models have been discarded by financial theoreticians but we show that they can be properly cast into a well defined scientific predictor if the signal generated by them pass the test of being a Markov time. That is, we can tell if the signal has occurred or not by examining the information up to the current time; or more technically, if the event is F_t-measurable. On the other hand the concept of pairs trading or market neutral strategy is fairly simple. However it can be cast in a variety of mathematical models ranging from a method based on a simple euclidean distance, in a co-integration framework or involving stochastic differential equations such as the well-known Ornstein-Uhlenbeck mean reversal ODE and its variations. A model for forecasting any economic or financial magnitude could be properly defined with scientific rigor but it could also lack of any economical value and be considered useless from a practical point of view. This is why this project could not be complete without a backtesting of the mentioned strategies. Conducting a useful and realistic backtesting is by no means a trivial exercise since the \laws" that govern financial markets are constantly evolving in time. This is the reason because we make emphasis in the calibration process of the strategies' parameters to adapt the given market conditions. We find out that the parameters from technical models are more volatile than their counterpart form market neutral strategies and calibration must be done in a high-frequency sampling manner to constantly track the currently market situation. As a whole, the goal of this project is to provide an overview of a quantitative approach to investment reviewing basic strategies and illustrating them by means of a back-testing with real financial market data. The sources of the data used in this project are Bloomberg for intraday time series and Yahoo! for daily prices. All numeric computations and graphics used and shown in this project were implemented in MATLAB^R scratch from scratch as a part of this thesis. No other mathematical or statistical software was used.

The European Union in North Korea: Current Realities and Paths for Future Engagement – A Qualitative and Quantitative Study

Malgrat la rellevància estratègica i el paper desestabilitzador de Corea del Nord a la regió econòmicament més dinàmica del món, la UE no compta amb cap estratègia clara per involucrar-se amb aquest país. Combinant tècniques d’anàlisi qualitatives i quantitatives, aquest treball pretén descobrir possibles contradiccions internes que impedeixin la definició d'una política exterior europea coherent i efectiva amb respecte a Corea del Nord, així com discrepàncies entre les percepcions d’actors interns de la UE i les d’actors externs. S'han detectat importants diferències d’expectatives i mancances en termes de coherència, tant entre les visions expressades pels actors interns com entre les opinions d’aquests actors i les dels futurs líders sudcoreans enquestats – diferències que fins i tot afecten la promoció dels drets humans

Biased quantitative measurement of interval ordered homothetic preferences

We represent interval ordered homothetic preferences with a quantitative homothetic utility function and a multiplicative bias. When preferences are weakly ordered (i.e. when indifference is transitive), such a bias equals 1. When indifference is intransitive, the biasing factor is a positive function smaller than 1 and measures a threshold of indifference. We show that the bias is constant if and only if preferences are semiordered, and we identify conditions ensuring a linear utility function. We illustrate our approach with indifference sets on a two dimensional commodity space.

On the quantitative importance of wage bargaining models

Four general equilibrium search models are compared quantitatively. Thebaseline framework is a calibrated macroeconomic model of the US economydesigned for a welfare analysis of unemployment insurance policy. Theother models make three simple and natural specification changes,regarding tax incidence, monopsony power in wage determination, and therelevant threat point. These specification changes have a major impacton the equilibrium and on the welfare implications of unemploymentinsurance, partly because search externalities magnify the effects ofwage changes. The optimal level of unemployment insurance dependsstrongly on whether raising benefits has a larger impact on searcheffort or on hiring expenditure.

Quantifying quantitative literacy: Age heaping and the history of human capital

Age data frequently display excess frequencies at round or attractive ages, such as even numbers and multiples of five. This phenomenon of age heaping has been viewed as a problem in previous research, especially in demography and epidemiology. We see it as an opportunity and propose its use as a measure of human capital that can yield comparable estimates across a wide range of historical contexts. A simulation study yields methodological guidelines for measuring and interpreting differences in ageheaping, while analysis of contemporary and historical datasets demonstrates the existence of a robust correlation between age heaping and literacy at both the individual and aggregate level. To illustrate the method, we generate estimates of human capital in Europe over the very long run, which support the hypothesis of a major increase in human capital preceding the industrial revolution.

Nonlinear inverse dynamic models of gas sensing systems based on chemical sensor arrays for quantitative measurements

Gas sensing systems based on low-cost chemical sensor arrays are gaining interest for the analysis of multicomponent gas mixtures. These sensors show different problems, e.g., nonlinearities and slow time-response, which can be partially solved by digital signal processing. Our approach is based on building a nonlinear inverse dynamic system. Results for different identification techniques, including artificial neural networks and Wiener series, are compared in terms of measurement accuracy.

The work of Spanish men. A quantitative analysis based on census data, 1900-1970

This paper presents a historical examination of employment in old age in Spain, in order to characterize this labour segment and identify and analyse its specific problems. One of these problems is the life-cycle deskilling process, already shown for certain national cases. This study explores whether this hypothesis also holds in Spain. The perspective used is essentially quantitative, as our analysis is based on the age-profession tables in Spanish population censuses from 1900 to 1970.

Quantitative x-ray photoelectron spectroscopy study of Al/AlOx bilayers

An x-ray photoelectron spectroscopy (XPS) analysis of Nb/Al wedge bilayers, oxidized by both plasma and natural oxidation, is reported. The main goal is to show that the oxidation state¿i.e., O:(oxidize)Al ratio¿, structure and thickness of the surface oxide layer, as well as the thickness of the metallic Al leftover, as functions of the oxidation procedure, can be quantitatively evaluated from the XPS spectra. This is relevant to the detailed characterization of the insulating barriers in (magnetic) tunnel junctions

A proteomics approach to decipher the molecular nature of planarian stem cells.

Background In recent years, planaria have emerged as an important model system for research into stem cells and regeneration. Attention is focused on their unique stem cells, the neoblasts, which can differentiate into any cell type present in the adult organism. Sequencing of the Schmidtea mediterranea genome and some expressed sequence tag projects have generated extensive data on the genetic profile of these cells. However, little information is available on their protein dynamics. Results We developed a proteomic strategy to identify neoblast-specific proteins. Here we describe the method and discuss the results in comparison to the genomic high-throughput analyses carried out in planaria and to proteomic studies using other stem cell systems. We also show functional data for some of the candidate genes selected in our proteomic approach. Conclusions We have developed an accurate and reliable mass-spectra-based proteomics approach to complement previous genomic studies and to further achieve a more accurate understanding and description of the molecular and cellular processes related to the neoblasts.

The work of Spanish men. A quantitative analysis based on census data, 1900-1970

This paper presents a historical examination of employment in old age in Spain, in order to characterize this labour segment and identify and analyse its specific problems. One of these problems is the life-cycle deskilling process, already shown for certain national cases. This study explores whether this hypothesis also holds in Spain. The perspective used is essentially quantitative, as our analysis is based on the age-profession tables in Spanish population censuses from 1900 to 1970.

Analyzing peptides and proteins by mass spectrometry: principles and applications in proteomics

The study of proteins has been a key element in biomedicine and biotechnology because of their important role in cell functions or enzymatic activity. Cells are the basic unit of living organisms, which are governed by a vast range of chemical reactions. These chemical reactions must be highly regulatedin order to achieve homeostasis. Proteins are polymeric molecules that havetaken on the evolutionary process the role, along with other factors, of controlthese chemical reactions. Learning how proteins interact and control their up anddown regulations can teach us how living cells regulate their functions, as well asthe cause of certain anomalies that occur in different diseases where proteins areinvolved. Mass spectrometry (MS) is an analytical widely used technique to studythe protein content inside the cells as a biomarker point, which describesdysfunctions in diseases and increases knowledge of how proteins are working.All the methodologies involved in these descriptions are integrated in the fieldcalled Proteomics.