Ontological representation of tumor-node-metastasis classification and an ontology-driven classifier: a study on colorectal cancer

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)

An R package for the integrated analysis of metabolomics and spectral data

Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.

Electroquímica de sustancias de interés en los sistemas agroalimentario y de sanidad animal. Desarrollo de biosensores electroquímicos. Aplicaciones analíticas.Electrochemistry of substances of interest in agroalimentary and animal health systems. Development of electrochemical biosensors. Analytical applications.

Se estudiarán los mecanismos de reacción electroquímica de las micotoxinas (metabolitos tóxicos generados por hongos) citrinina (CIT), patulina (PAT) y moniliformina (MON), de los antioxidantes naturales alfa, beta, gama y delta tocoferoles, de los flavonoides fisetina (FIS), morina (MOR), luteolina (LUT), rutina (RUT), buteina (BUT), naringenina (NAR) y miricetina (MIR) y de las hormonas esteroides estradiol (EDIOL), estrona (EONA) y estriol (ETRIOL). Por otra parte, se implementarán técnicas electroanalíticas para la detección y cuantificación de estos sustratos en muestras de matrices naturales que los contengan. Se realizará el diseño y caracterización de biosensores enzimáticos a partir de peroxidasas y/o fosfatasa alcalina para la determinación de la micotoxina CIT y de los flavonoides y, por otro, de inmunosensores para las micotoxinas ocratoxina A (OTA) y PAT y hormonas. Para el anclaje de enzimas y/o anticuerpos, se estudiarán las propiedades de electrodos modificados por monocapas autoensambladas, nanotubos de carbono y partículas magnéticas. Se usarán las técnicas de voltamperometría cíclica, de onda cuadrada y de redisolución con acumulación adsortiva, espectroscopías de impedancia electroquímica, electrólisis a potencial controlado, uv-vis e IR, microbalanza de cristal de cuarzo y microscopías de alta resolución (SEM, TEM, AFM). La importancia de este proyecto apunta a la obtención de nuevos datos electroquímicos de los sustratos indicados y conocimientos relacionados con la aplicación de electrodos modificados en la preparación de biosensores y en el desarrollo de técnicas alternativas para la determinación de los analitos mencionados precedentemente. Electrochemical reaction mechanisms of mycotoxins (toxic metabolites generated by fungi) citrinin (CIT), Patulin (PAT) and moniliformin (MON), natural antioxidants alpha, beta, gamma and delta tocopherols, flavonoids fisetin (FIS), morin (MOR), luteolin (LUT), rutin (RUT), butein (BUT), naringenin (NAR), miricetin (MIR) and steroid hormones estradiol (EDIOL), estrone (EONA) and estriole (ETRIOL) will be explored. On the other hand, electroanalytical techniques for the detection and quantification of these substrates in samples of natural matrices will be implemented. The design and characterization of enzymatic biosensors from peroxidases and/or from alkaline phosphatase for the determination of CIT and flavonoids, and also of inmunosensors for ochratoxin A (OTA) and PAT and hormones will be performed. For the anchor of enzymes and/or antibody, properties of electrodes modified by self assembled monolayers, carbon nanotubes and magnetic particles will be explored. Cyclic, square wave and adsorptive stripping voltammetries, electrochemical impedance spectroscopy, controlled potential electrolysis, uv-vis and IR, quartz crystal microbalance and high-resolution microcopies (SEM, TEM, AFM) will be used. The importance of this project is aimed at obtaining new electrochemical data for the indicated substrates and knowledge on the application of modified electrodes in preparation of biosensors and in the development of alternative techniques for the determination of the above-mentioned analytes.

Ultrasound Blocks for the Anterior Abdominal Wall - Adult and Pediatric Surgery

Somatic post-surgical pain is invalidating and distressing to patients and carries the risk of important complications. The anterior abdominal wall is involved in most surgical procedures in general, gynecologic, obstetric, urological, vascular and pediatric surgery. Combined multimodal strategies involving nerve blocks, opiates, and non-steroidal anti-inflammatory drugs for systemic analgesia are necessary for optimal pain modulation. Anterior abdominal wall blocks, transverse abdominal plexus block, iliohypogastric and ilioinguinal nerveblock, genitofemoral nerve block and rectus sheath block have an important role as components of multimodal analgesia for somatic intraoperative and postoperative pain control. Ultrasound visualization has improved the efficacy and safety of abdominal blocks and implemented the application in the clinical setting. For this reason, they are a very important tool for all anesthesiologists who aim to treat effectively patients’ pain. This guide provides an evidence based comprehensive and necessary overview of anatomical, anesthesiological and technical information needed to safely perform these blocks.

Hypertensives' Knowledge About High-Sodium Foods and Their Behavior

Abstract Background: In Brazil, the prevalence of systemic arterial hypertension (SAH) is approximately 30% of the total population. In 2010, SAH was the cause of death of about 9.4 million people worldwide. A healthy dietary pattern is important to maintain proper blood pressure levels and, consequently, disease control. Objectives: To describe the knowledge and practices of hypertensive patients cared for at a public hypertension outpatient clinic, and its relationship with high-sodium food. Methods: We applied a questionnaire to patients with questions related to sociodemographics, dietary pattern, frequency of ingestion of certain foods, and knowledge about their own disease. Results: We studied 221 patients, 56.1% of whom were women, and 53.8% had only elementary education. Their mean age was 57.7 ±13.5 years, and 75.6% of them reported having high blood pressure, and 11.3%, diabetes mellitus. Regarding dietary pattern, 62% used ready-to-use seasonings, but 94.1% reported not adding extra salt to their ready meals. Regarding patients' knowledge about high-sodium foods and SAH, only 8 patients had 100% of right answers, 37 patients had 73.8%, and 42 patients, 57% of right answers. Conclusion: Knowledge about SAH prevention and high-sodium foods was insufficient. Based on this study's findings, more effective educational strategies targeted at this population can be developed.

Addressing Sea Surface Salinity retrieval at different spatial resolution. Feasibility study using OCCAM data within SEPS simulator and L2 processor tools

Projecte de recerca elaborat a partir d’una estada a la National Oceanography Centre of Southampton (NOCS), Gran Bretanya, entre maig i juliol del 2006. La possibilitat d’obtenir una estimació precissa de la salinitat marina (SSS) és important per a investigar i predir l’extensió del fenòmen del canvi climàtic. La missió Soil Moisture and Ocean Salinity (SMOS) va ser seleccionada per l’Agència Espacial Europea (ESA) per a obtenir mapes de salinitat de la superfície marina a escala global i amb un temps de revisita petit. Abans del llençament de SMOS es preveu l’anàlisi de la variabilitat horitzontal de la SSS i del potencial de les dades recuperades a partir de mesures de SMOS per a reproduir comportaments oceanogràfics coneguts. L’objectiu de tot plegat és emplenar el buit existent entre les fonts de dades d’entrada/auxiliars fiables i les eines desenvolupades per a simular i processar les dades adquirides segons la configuració de SMOS. El SMOS End-to-end Performance Simulator (SEPS) és un simulador adhoc desenvolupat per la Universitat Politècnica de Catalunya (UPC) per a generar dades segons la configuració de SMOS. Es va utilitzar dades d’entrada a SEPS procedents del projecte Ocean Circulation and Climate Advanced Modeling (OCCAM), utilitzat al NOCS, a diferents resolucions espacials. Modificant SEPS per a poder fer servir com a entrada les dades OCCAM es van obtenir dades de temperatura de brillantor simulades durant un mes amb diferents observacions ascendents que cobrien la zona seleccionada. Les tasques realitzades durant l’estada a NOCS tenien la finalitat de proporcionar una tècnica fiable per a realitzar la calibració externa i per tant cancel•lar el bias, una metodologia per a promitjar temporalment les diferents adquisicions durant les observacions ascendents, i determinar la millor configuració de la funció de cost abans d’explotar i investigar les posibiltats de les dades SEPS/OCCAM per a derivar la SSS recuperada amb patrons d’alta resolució.

Innovation sources and productivity in Catalonian firms: a quantile regression analysis

This paper explores the effects of two main sources of innovation -intramural and external R&D- on the productivity level in a sample of 3,267 Catalonian firms. The data set used is based on the official innovation survey of Catalonia which was a part of the Spanish sample of CIS4, covering the years 2002-2004. We compare empirical results by applying usual OLS and quantile regression techniques both in manufacturing and services industries. In quantile regression, results suggest different patterns at both innovation sources as we move across conditional quantiles. The elasticity of intramural R&D activities on productivity decreased when we move up the high productivity levels both in manufacturing and services sectors, while the effects of external R&D rise in high-technology industries but are more ambiguous in low-technology and knowledge-intensive services. JEL codes: O300, C100, O140. Keywords: Innovation sources, R&D, Productivity, Quantile regression

Barriers to innovation and public policy in Catalonia

The present paper analyses the link between firms’ decisions to innovate and the barriers that prevent them from being innovative. The aim is twofold. First, it analyses three groups of barriers to innovation: the cost of innovation projects, lack of knowledge and market conditions. Second, it presents the main steps taken by Catalan Government to promote the creation of new firms and to reduce barriers to innovation. The data set used is based on the 2004 official innovation survey of Catalonia which was taken from the Spanish CIS-4 sample. This sample includes individual information on 2,954 Catalan firms in manufacturing industries and knowledge-intensive services (KIS). The empirical analysis reveals pronounced differences regarding a firm’s propensity to innovate and its perception of barriers. Moreover, the results show that cost and knowledge barriers seem to be the most important and that there are substantial sectoral differences in the way that firms react to barriers. The results of this paper have important implications for the design of future public policy to promote entrepreneurship and innovation together.

Multilayer perceptron with local constraint as an emerging method in spatial data analysis

The use of Geographic Information Systems has revolutionalized the handling and the visualization of geo-referenced data and has underlined the critic role of spatial analysis. The usual tools for such a purpose are geostatistics which are widely used in Earth science. Geostatistics are based upon several hypothesis which are not always verified in practice. On the other hand, Artificial Neural Network (ANN) a priori can be used without special assumptions and are known to be flexible. This paper proposes to discuss the application of ANN in the case of the interpolation of a geo-referenced variable.

Innovation sources and productivity in Catalonian firms: a quantile regression analysis

This paper explores the effects of two main sources of innovation - intramural and external R&D— on the productivity level in a sample of 3,267 Catalonian firms. The data set used is based on the official innovation survey of Catalonia which was a part of the Spanish sample of CIS4, covering the years 2002-2004. We compare empirical results by applying usual OLS and quantile regression techniques both in manufacturing and services industries. In quantile regression, results suggest different patterns at both innovation sources as we move across conditional quantiles. The elasticity of intramural R&D activities on productivity decreased when we move up the high productivity levels both in manufacturing and services sectors, while the effects of external R&D rise in high-technology industries but are more ambiguous in low-technology and knowledge-intensive services. JEL codes: O300, C100, O140 Keywords: Innovation sources, R&D, Productivity, Quantile Regression

Plasma Level of Mmp-9 as Predictive Factor for Response and Progression Free Survival in Patients Treated with Bevacizumab (Bev) and Pegylated Liposomal Doxorubicin (Pld): Sakk 24/06

Background: There is currently no identified marker predicting benefit from Bev in patients with breast cancer (pts). We monitored prospectively 6 angiogenesis-related factors in the blood of advanced stage pts treated with a combination of Bev and PLD in a phase II trial of the Swiss Group for Clinical Cancer Research, SAKK.Methods: Pts received PLD (20 mg/m2) and Bev (10 mg/kg) every 2 weeks for a maximum of 12 administrations, followed by Bev monotherapy until progression or severe toxicity. Blood samples were collected at baseline, during treatment and at treatment discontinuation. Enzyme-linked immunosorbent assays (Quantikine, R&DSystems and Reliatech) were used to measure vascular endothelial growth factor (VEGF), placental growth factor (PlGF), matrix metalloproteinase 9 (MMP-9) and soluble VEGF receptors -1, -2 and -3. The natural log-transformed (ln) data for each factor was analyzed by analysis of variance (ANOVA) model to investigate differences between the mean values of the subgroups of interest (where a = 0.05), based on the best tumor response by RECIST.Results: 132 samples were collected in 41 pts. The mean of baseline ln MMP-9 levels was significantly lower in pts with tumor progression than those with tumor response (p=0.0202, log fold change=0.8786) or disease control (p=0.0035, log fold change=0.8427). Higher MMP-9 level was a significant predictor of superior progression free survival (PFS): p=0.0417, hazard ratio=0.574, 95% CI=0.336-0.979. In a multivariate cox proportional hazards model, containing performance status, disease free interval, number of tumor sites, visceral involvement and prior adjuvant chemotherapy, using stepwise regression baseline MMP-9 was still a statistically 117P Table 1. SOLTI-0701* AC01B07* NU07B1* SOR+CAP N=20 PL+CAP N=33 SOR+ GEM/CAP N=23 PL+ GEM/CAP N=27 SOR+PAC N=48 PL+PAC N=46 Baseline characteristics Age, median (range), y 49 (32-72) 53 (30-78 54 (32-69) 57 (31-82) 50 (27-80) 52 (23-74) AJCC stage, n (%) IIIB/IIIC 3 (15) 6 (18) 0 (0) 3 (11) 8 (17) 9 (20) IV 17 (85) 27 (82) 23 (100) 24 (89) 40 (83) 37 (80) Metastatic site, n (%) Non-visceral 3 (15) 6 (18) 7 (30) 6 (22) 9 (19) 17 (37) Visceral 17 (85) 27 (82) 16 (70) 21 (78) 39 (81) 29 (63) Prior metastatic chemo, n (%) 8 (40) 15 (45) 21 (91) 25 (93) - - Efficacy PFS, median, mo 4.3 2.5 3.1 2.6 5.6 5.5 HR (95% CI)_ 0.60 (0.31, 1.14) 0.57 (0.30, 1.09) 0.86 (0.50, 1.45) 1-sided P value_ 0.055 0.044 0.281 Overall survival, median, mo 17.5 16.1 Pending 14.7 18.2 HR (95% CI)_ 0.98 (0.50, 1.89) 1.11 (0.64, 1.94) 1-sided P value_ 0.476 0.352 Safety N=20 N=33 N=22 N=27 N=46 N=46 Tx-emergent Grade 3/4, n (%) 15 (75) 16 (48) 20 (91) 17 (63) 36 (78) 16 (35) Grade 3§ hand-foot skin reaction/ syndrome 8 (40) 5 (15) 8 (36) 0 (0) 14 (30) 2 (4) *Efficacy results based on intent-to-treat population and safety results based on safety population (pts who received study drug[s]); _Cox regression within each subgroup; _log-rank test within each subgroup; §maximum toxicity grade for hand-foot skin reaction/syndrome; AJCC, American Joint Committee on Cancer mittedabstractsª The Author 2011. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com Downloaded from annonc.oxfordjournals.org at Bibliotheque Cantonale et Universitaire on June 6, 2011 significant factor (p=0.0266). The results of the other measured factors were presented elsewhere.Conclusions: Higher levels of MMP-9 could predict tumor response and superior PFSin pts treated with a combination of Bev and PLD. These exploratory results justify further investigations of MMP-9 in pts treated with Bev combinations in order to assess its role as a prognostic and predictive factor.Disclosure: K. Zaman: Participation in advisory board of Roche; partial sponsoring ofthe study by Roche (the main sponsor was the Swiss Federation against Cancer (Oncosuisse)). B. Thu¨rlimann: stock of Roche; Research grants from Roche. R. vonMoos: Participant of Advisory Board and Speaker honoraria

Consumer populations and nutritional transition in Spain in the 20th century: a methodology for their reconstruction

One feature of the modern nutrition transition is the growing consumption of animal proteins. The most common approach in the quantitative analysis of this change used to be the study of averages of food consumption. But this kind of analysis seems to be incomplete without the knowledge of the number of consumers. Data about consumers are not usually published in historical statistics. This article introduces a methodological approach for reconstructing consumer populations. This methodology is based on some assumptions about the diffusion process of foodstuffs and the modeling of consumption patterns with a log-normal distribution. This estimating process is illustrated with the specific case of milk consumption in Spain between 1925 and 1981. These results fit quite well with other data and indirect sources available showing that this dietary change was a slow and late process. The reconstruction of consumer population could shed a new light in the study of nutritional transitions.

Multimodel inference and multimodel averaging in empirical modeling of occupational exposure levels.

Empirical modeling of exposure levels has been popular for identifying exposure determinants in occupational hygiene. Traditional data-driven methods used to choose a model on which to base inferences have typically not accounted for the uncertainty linked to the process of selecting the final model. Several new approaches propose making statistical inferences from a set of plausible models rather than from a single model regarded as 'best'. This paper introduces the multimodel averaging approach described in the monograph by Burnham and Anderson. In their approach, a set of plausible models are defined a priori by taking into account the sample size and previous knowledge of variables influent on exposure levels. The Akaike information criterion is then calculated to evaluate the relative support of the data for each model, expressed as Akaike weight, to be interpreted as the probability of the model being the best approximating model given the model set. The model weights can then be used to rank models, quantify the evidence favoring one over another, perform multimodel prediction, estimate the relative influence of the potential predictors and estimate multimodel-averaged effects of determinants. The whole approach is illustrated with the analysis of a data set of 1500 volatile organic compound exposure levels collected by the Institute for work and health (Lausanne, Switzerland) over 20 years, each concentration having been divided by the relevant Swiss occupational exposure limit and log-transformed before analysis. Multimodel inference represents a promising procedure for modeling exposure levels that incorporates the notion that several models can be supported by the data and permits to evaluate to a certain extent model selection uncertainty, which is seldom mentioned in current practice.

Underreporting of needlestick and sharps injuries among healthcare workers in a Swiss University Hospital.

OBJECTIVES: To determine 1) rates of needlestick and sharps injuries (NSSIs) not reported to occupational health services, 2) reasons for underreporting and 3) awareness of reporting procedures in a Swiss university hospital. MATERIALS AND METHODS: We surveyed 6,367 employees having close clinical contact with patients or patient specimens. The questionnaire covered age, sex, occupation, years spent in occupation, history of NSSI during the preceding twelve months, NSSI reporting, barriers to reporting and knowledge of reporting procedures. RESULTS: 2,778 questionnaires were returned (43.6%) of which 2,691 were suitable for analysis. 260/2,691 employees (9.7%) had sustained at least one NSSI during the preceding twelve months. NSSIs were more frequent among nurses (49.2%) and doctors performing invasive procedures (IPs) (36.9%). NSSI rate by occupation was 8.6% for nurses, 19% for doctors and 1.3% for domestic staff. Of the injured respondents, 73.1% reported all events, 12.3% some and 14.6% none. 42.7% of doctors performing invasive procedures (IPs) underreported NSSIs and represented 58.6% of underreported events. Estimation that transmission risk was low (87.1%) and perceived lack of time (34.3%) were the most common reasons for non-reporting. Regarding reporting procedures, 80.1% of respondents knew to contact occupational health services. CONCLUSION: Doctors performing IPs have high rates of NSSI and, through self-assessment that infection transmission risk is low or perceived lack of time, high rates of underreporting. If individual risk analyses underestimate the real risk, such underreporting represents a missed opportunity for post-exposure prophylaxis and identification of hazardous procedures. Doctors' training in NSSI reporting merits re-evaluation.

Quantitative genetic modeling and inference in the presence of nonignorable missing data.

Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.