Tráfego veicular e mortalidade por doenças do aparelho circulatório em homens adultos

OBJETIVO: Analisar a associação entre indicadores de exposição à poluição por tráfego veicular e mortalidade por doenças do aparelho circulatório em homens adultos. MÉTODOS: Foram analisadas informações sobre vias e volume de tráfego no ano de 2007 fornecidas pela companhia de engenharia de tráfego local. Mortalidade por doenças do aparelho circulatório no ano de 2005 entre homens ≥ 40 anos foram obtidas do registro de mortalidade do Programa de Aprimoramento de Informações de Mortalidade do Município de São Paulo, SP. Dados socioeconômicos do Censo 2000 e informações sobre a localização dos serviços de saúde também foram coletados. A exposição foi avaliada pela densidade de vias e volume de tráfego para cada distrito administrativo. Foi calculada regressão (α = 5%) entre esses indicadores de exposição e as taxas de mortalidade padronizadas, ajustando os modelos para variáveis socioeconômicas, número de serviços de saúde nos distritos e autocorrelação espacial. RESULTADOS: A correlação entre densidade de vias e volume de tráfego foi modesta (r² = 0,28). Os distritos do centro apresentaram os maiores valores de densidade de vias. O modelo de regressão espacial de densidade de vias indicou associação com mortalidade por doenças do aparelho circulatório (p = 0,017). Não se observou associação no modelo de volume de tráfego. Em ambos os modelos – vias e volume de tráfego (veículos leves/pesados) – a variável socioeconômica foi estatisticamente signifi cante. CONCLUSÕES: A associação entre mortalidade por doenças do aparelho circulatório e densidade de vias converge com a literatura e encoraja a realização de mais estudos epidemiológicos em nível individual e com métodos mais acurados de avaliação da exposição.

An in-depth analysis of the HIV-1/AIDS dynamics by comprehensive mathematical modeling

This work presents major results from a novel dynamic model intended to deterministically represent the complex relation between HIV-1 and the human immune system. The novel structure of the model extends previous work by representing different host anatomic compartments under a more in-depth cellular and molecular immunological phenomenology. Recently identified mechanisms related to HIV-1 infection as well as other well known relevant mechanisms typically ignored in mathematical models of HIV-1 pathogenesis and immunology, such as cell-cell transmission, are also addressed. (C) 2011 Elsevier Ltd. All rights reserved.

Vehicle emissions and PM2.5 mass concentrations in six Brazilian cities

In Brazil, the principal source of air pollution is the combustion of fuels (ethanol, gasohol, and diesel). In this study, we quantify the contributions that vehicle emissions make to the urban fine particulate matter (PM2.5) mass in six state capitals in Brazil, collecting data for use in a larger project evaluating the impact of air pollution on human health. From winter 2007 to winter 2008, we collected 24-h PM2.5 samples, employing gravimetry to determine PM2.5 mass concentrations; reflectance to quantify black carbon concentrations; X-ray fluorescence to characterize elemental composition; and ion chromatography to determine the composition and concentrations of anions and cations. Mean PM2.5 concentrations in the cities of Sao Paulo, Rio de Janeiro, Belo Horizonte, Curitiba, Porto Alegre, and Recife were 28, 17.2, 14.7, 14.4, 13.4, and 7.3 mu g/m(3), respectively. In Sao Paulo and Rio de Janeiro, black carbon explained approximately 30% of the PM2.5 mass. We used receptor models to identify distinct source-related PM2.5 fractions and correlate those fractions with daily mortality rates. Using specific rotation factor analysis, we identified the following principal contributing factors: soil and crustal material; vehicle emissions and biomass burning (black carbon factor); and fuel oil combustion in industries (sulfur factor). In all six cities, vehicle emissions explained at least 40% of the PM2.5 mass. Elemental composition determination with receptor modeling proved an adequate strategy to identify air pollution sources and to evaluate their short- and long-term effects on human health. Our data could inform decisions regarding environmental policies vis-a-vis health care costs.

Impact of urban atmospheric environment on hospital admissions in the elderly

OBJECTIVE: To analyze the impact of intra-urban atmospheric conditions on circulatory and respiratory diseases in elder adults. METHODS: Cross-sectional study based on data from 33,212 hospital admissions in adults over 60 years in the city of São Paulo, southeastern Brazil, from 2003 to 2007. The association between atmospheric variables from Congonhas airport and bioclimatic index, Physiological Equivalent Temperature, was analyzed according to the district's socioenvironmental profile. Descriptive statistical analysis and regression models were used. RESULTS: There was an increase in hospital admissions due to circulatory diseases as average and lowest temperatures decreased. The likelihood of being admitted to the hospital increased by 12% with 1ºC decrease in the bioclimatic index and with 1ºC increase in the highest temperatures in the group with lower socioenvironmental conditions. The risk of admission due to respiratory diseases increased with inadequate air quality in districts with higher socioenvironmental conditions. CONCLUSIONS: The associations between morbidity and climate variables and the comfort index varied in different groups and diseases. Lower and higher temperatures increased the risk of hospital admission in the elderly. Districts with lower socioenvironmental conditions showed greater adverse health impacts.

Models for the Study of Cortical Activity During Cognitive ans Motor Tasks

This thesis is mainly devoted to show how EEG data and related phenomena can be reproduced and analyzed using mathematical models of neural masses (NMM). The aim is to describe some of these phenomena, to show in which ways the design of the models architecture is influenced by such phenomena, point out the difficulties of tuning the dozens of parameters of the models in order to reproduce the activity recorded with EEG systems during different kinds of experiments, and suggest some strategies to cope with these problems. In particular the chapters are organized as follows: chapter I gives a brief overview of the aims and issues addressed in the thesis; in chapter II the main characteristics of the cortical column, of the EEG signal and of the neural mass models will be presented, in order to show the relationships that hold between these entities; chapter III describes a study in which a NMM from the literature has been used to assess brain connectivity changes in tetraplegic patients; in chapter IV a modified version of the NMM is presented, which has been developed to overcomes some of the previous version’s intrinsic limitations; chapter V describes a study in which the new NMM has been used to reproduce the electrical activity evoked in the cortex by the transcranial magnetic stimulation (TMS); chapter VI presents some preliminary results obtained in the simulation of the neural rhythms associated with memory recall; finally, some general conclusions are drawn in chapter VII.

Quantifying and modeling ecosystem services provided by urban greening in cities of the Southern Alps, N Italy

Population growth in urban areas is a world-wide phenomenon. According to a recent United Nations report, over half of the world now lives in cities. Numerous health and environmental issues arise from this unprecedented urbanization. Recent studies have demonstrated the effectiveness of urban green spaces and the role they play in improving both the aesthetics and the quality of life of its residents. In particular, urban green spaces provide ecosystem services such as: urban air quality improvement by removing pollutants that can cause serious health problems, carbon storage, carbon sequestration and climate regulation through shading and evapotranspiration. Furthermore, epidemiological studies with controlled age, sex, marital and socio-economic status, have provided evidence of a positive relationship between green space and the life expectancy of senior citizens. However, there is little information on the role of public green spaces in mid-sized cities in northern Italy. To address this need, a study was conducted to assess the ecosystem services of urban green spaces in the city of Bolzano, South Tyrol, Italy. In particular, we quantified the cooling effect of urban trees and the hourly amount of pollution removed by the urban forest. The information was gathered using field data collected through local hourly air pollution readings, tree inventory and simulation models. During the study we quantified pollution removal for ozone, nitrogen dioxide, carbon monoxide and particulate matter (<10 microns). We estimated the above ground carbon stored and annually sequestered by the urban forest. Results have been compared to transportation CO2 emissions to determine the CO2 offset potential of urban streetscapes. Furthermore, we assessed commonly used methods for estimating carbon stored and sequestered by urban trees in the city of Bolzano. We also quantified ecosystem disservices such as hourly urban forest volatile organic compound emissions.

Water-soluble organic compounds in air particulate matter analyzed by HPLC-DAD-MS and HPLC-MS/MS: abundance, sources and transformation of carboxylic acids, nitrophenols and nitrated proteins

Wasserlösliche organische Verbindungen (WSOCs) sind Hauptbestandteile atmosphärischer Aerosole, die bis zu ~ 50% und mehr der organischen Aerosolfraktion ausmachen. Sie können die optischen Eigenschaften sowie die Hygroskopizität von Aerosolpartikeln und damit deren Auswirkungen auf das Klima beeinflussen. Darüber hinaus können sie zur Toxizität und Allergenität atmosphärischer Aerosole beitragen.In dieser Studie wurde Hochleistungsflüssigchromatographie gekoppelt mit optischen Diodenarraydetektion und Massenspektrometrie (HPLC-DAD-MS und HPLC-MS/MS) angewandt, um WSOCs zu analysieren, die für verschiedene Aerosolquellen und -prozesse charakteristisch sind. Niedermolekulare Carbonsäuren und Nitrophenole wurden als Indikatoren für die Verbrennung fossiler Brennstoffe und die Entstehung sowie Alterung sekundärer organischer Aerosole (SOA) aus biogenen Vorläufern untersucht. Protein-Makromoleküle wurden mit Blick auf den Einfluss von Luftverschmutzung und Nitrierungsreaktionen auf die Allergenität primärer biologischer Aerosolpartikel – wie Pollen und Pilzsporen – untersucht.rnFilterproben von Grob- und Feinstaubwurden über ein Jahr hinweg gesammelt und auf folgende WSOCs untersucht: die Pinen-Oxidationsprodukte Pinsäure, Pinonsäure und 3-Methyl-1,2,3-Butantricarbonsäure (3-MBTCA) sowie eine Vielzahl anderer Dicarbonsäuren und Nitrophenole. Saisonale Schwankungen und andere charakteristische Merkmale werden mit Blick auf Aerosolquellen und -senken im Vergleich zu Daten anderen Studien und Regionen diskutiert. Die Verhätlnisse von Adipinsäure und Phthalsäure zu Azelainsäure deuten darauf hin, dass die untersuchten Aerosolproben hauptsächlich durch biogene Quellen beeinflusst werden. Eine ausgeprägte Arrhenius-artige Korrelation wurde zwischen der 3-MBTCA-¬Konzentration und der inversen Temperatur beobachtet (R2 = 0.79, Ea = 126±10 kJ mol-1, Temperaturbereich 275–300 K). Modellrechnungen zeigen, dass die Temperaturabhängigkeit auf eine Steigerung der photochemischen Produktionsraten von 3-MBTCA durch erhöhte OH-Radikal-Konzentrationen bei erhöhten Temperaturen zurückgeführt werden kann. Im Vergleich zur chemischen Reaktionskinetik scheint der Einfluss von Gas-Partikel-Partitionierungseffekten nur eine untergeordnete Rolle zu spielen. Die Ergebnisse zeigen, dass die OH-initiierte Oxidation von Pinosäure der geschwindigkeitsbestimmende Schritt der Bildung von 3-MBTCA ist. 3-MBTCA erscheint somit als Indikator für die chemische Alterung von biogener sekundärer organischer Aerosole (SOA) durch OH-Radikale geeignet. Eine Arrhenius-artige Temperaturabhängigkeit wurde auch für Pinäure beobachtet und kann durch die Temperaturabhängigkeit der biogenen Pinen-Emissionen als geschwindigkeitsbestimmender Schritt der Pinsäure-Bildung erklärt werden (R2 = 0.60, Ea = 84±9 kJ mol-1).rn rnFür die Untersuchung von Proteinnitrierungreaktionen wurde nitrierte Protein¬standards durch Flüssigphasenreaktion von Rinderserumalbumin (BSA) und Ovalbumin (OVA) mit Tetranitromethan (TNM) synthetisiert.Proteinnitrierung erfolgt vorrangig an den Resten der aromatischen Aminosäure Tyrosin auf, und mittels UV-Vis-Photometrie wurde der Proteinnnitrierungsgrad (ND) bestimmt. Dieser ist definiert als Verhältnis der mittleren Anzahl von Nitrotyrosinresten zur Tyrosinrest-Gesamtzahl in den Proteinmolekülen. BSA und OVA zeigten verschiedene Relationen zwischen ND und TNM/Tyrosin-Verhältnis im Reaktionsgemisch, was vermutlich auf Unterschiede in den Löslichkeiten und den molekularen Strukturen der beiden Proteine zurück zu führen ist.rnDie Nitrierung von BSA und OVA durch Exposition mit einem Gasgemisch aus Stickstoffdioxid (NO2) und Ozon (O3) wurde mit einer neu entwickelten HPLC-DAD-¬Analysemethode untersucht. Diese einfache und robuste Methode erlaubt die Bestimmung des ND ohne Hydrolyse oder Verdau der untersuchten Proteine und ernöglicht somit eine effiziente Untersuchung der Kinetik von Protein¬nitrierungs-Reaktionen. Für eine detaillierte Produktstudien wurden die nitrierten Proteine enzymatisch verdaut, und die erhaltenen Oligopeptide wurden mittels HPLC-MS/MS und Datenbankabgleich mit hoher Sequenzübereinstimmung analysiert. Die Nitrierungsgrade individueller Nitrotyrosin-Reste (NDY) korrelierten gut mit dem Gesamt-Proteinnitrierungsgrad (ND), und unterschiedliche Verhältnisse von NDY zu ND geben Aufschluss über die Regioselektivität der Reaktion. Die Nitrierungmuster von BSA und OVA nach Beahndlung mit TNM deuten darauf hin, dass die Nachbarschaft eines negativ geladenen Aminosäurerestes die Tyrosinnitrierung fördert. Die Behandlung von BSA durch NO2 und O3 führte zu anderend Nitrierungemustern als die Behandlung mit TNM, was darauf hindeutet, dass die Regioselektivität der Nitrierung vom Nitrierungsmittel abhängt. Es zeigt sich jedoch, dass Tyrosinreste in Loop-Strukturen bevorzugt und unabhängig vom Reagens nitriert werden.Die Methoden und Ergebnisse dieser Studie bilden eine Grundlage für weitere, detaillierte Untersuchungen der Reaktionskinetik sowie der Produkte und Mechanismen von Proteinnitrierungreaktionen. Sie sollen helfen, die Zusammenhänge zwischen verkehrsbedingten Luftschadstoffen wie Stickoxiden und Ozon und der Allergenität von Luftstaub aufzuklären.rn

Bayesian space-time data fusion for real-time forecasting and map uncertainty

Environmental computer models are deterministic models devoted to predict several environmental phenomena such as air pollution or meteorological events. Numerical model output is given in terms of averages over grid cells, usually at high spatial and temporal resolution. However, these outputs are often biased with unknown calibration and not equipped with any information about the associated uncertainty. Conversely, data collected at monitoring stations is more accurate since they essentially provide the true levels. Due the leading role played by numerical models, it now important to compare model output with observations. Statistical methods developed to combine numerical model output and station data are usually referred to as data fusion. In this work, we first combine ozone monitoring data with ozone predictions from the Eta-CMAQ air quality model in order to forecast real-time current 8-hour average ozone level defined as the average of the previous four hours, current hour, and predictions for the next three hours. We propose a Bayesian downscaler model based on first differences with a flexible coefficient structure and an efficient computational strategy to fit model parameters. Model validation for the eastern United States shows consequential improvement of our fully inferential approach compared with the current real-time forecasting system. Furthermore, we consider the introduction of temperature data from a weather forecast model into the downscaler, showing improved real-time ozone predictions. Finally, we introduce a hierarchical model to obtain spatially varying uncertainty associated with numerical model output. We show how we can learn about such uncertainty through suitable stochastic data fusion modeling using some external validation data. We illustrate our Bayesian model by providing the uncertainty map associated with a temperature output over the northeastern United States.

Origin and variability of PM10 and atmospheric radiotracers at the WMO-GAW station of Mt. Cimone (1998-2011) and in the central Po Valley

Particulate matter is one of the main atmospheric pollutants, with a great chemical-environmental relevance. Improving knowledge of the sources of particulate matter and of their apportionment is needed to handle and fulfill the legislation regarding this pollutant, to support further development of air policy as well as air pollution management. Various instruments have been used to understand the sources of particulate matter and atmospheric radiotracers at the site of Mt. Cimone (44.18° N, 10.7° E, 2165 m asl), hosting a global WMO-GAW station. Thanks to its characteristics, this location is suitable investigate the regional and long-range transport of polluted air masses on the background Southern-Europe free-troposphere. In particular, PM10 data sampled at the station in the period 1998-2011 were analyzed in the framework of the main meteorological and territorial features. A receptor model based on back trajectories was applied to study the source regions of particulate matter. Simultaneous measurements of atmospheric radionuclides Pb-210 and Be-7 acquired together with PM10 have also been analysed to acquire a better understanding of vertical and horizontal transports able to affect atmospheric composition. Seasonal variations of atmospheric radiotracers have been studied both analysing the long-term time series acquired at the measurement site as well as by means of a state-of-the-art global 3-D chemistry and transport model. Advection patterns characterizing the circulation at the site have been identified by means of clusters of back-trajectories. Finally, the results of a source apportionment study of particulate matter carried on in a midsize town of the Po Valley (actually recognised as one of the most polluted European regions) are reported. An approach exploiting different techniques, and in particular different kinds of models, successfully achieved a characterization of the processes/sources of particulate matter at the two sites, and of atmospheric radiotracers at the site of Mt. Cimone.

Spatio-temporal models of the functional architecture of the visual cortex

In this work I tried to explore many aspects of cognitive visual science, each one based on different academic fields, proposing mathematical models capable to reproduce both neuro-physiological and phenomenological results that were described in the recent literature. The structure of my thesis is mainly composed of three chapters, corresponding to the three main areas of research on which I focused my work. The results of each work put the basis for the following, and their ensemble form an homogeneous and large-scale survey on the spatio-temporal properties of the architecture of the visual cortex of mammals.

Kinetic modeling and experiments on gas uptake and chemical transformation of organic aerosol in the atmosphere

Aerosolpartikel beeinflussen das Klima durch Streuung und Absorption von Strahlung sowie als Nukleations-Kerne für Wolkentröpfchen und Eiskristalle. Darüber hinaus haben Aerosole einen starken Einfluss auf die Luftverschmutzung und die öffentliche Gesundheit. Gas-Partikel-Wechselwirkunge sind wichtige Prozesse, weil sie die physikalischen und chemischen Eigenschaften von Aerosolen wie Toxizität, Reaktivität, Hygroskopizität und optische Eigenschaften beeinflussen. Durch einen Mangel an experimentellen Daten und universellen Modellformalismen sind jedoch die Mechanismen und die Kinetik der Gasaufnahme und der chemischen Transformation organischer Aerosolpartikel unzureichend erfasst. Sowohl die chemische Transformation als auch die negativen gesundheitlichen Auswirkungen von toxischen und allergenen Aerosolpartikeln, wie Ruß, polyzyklische aromatische Kohlenwasserstoffe (PAK) und Proteine, sind bislang nicht gut verstanden.rn Kinetische Fluss-Modelle für Aerosoloberflächen- und Partikelbulk-Chemie wurden auf Basis des Pöschl-Rudich-Ammann-Formalismus für Gas-Partikel-Wechselwirkungen entwickelt. Zunächst wurde das kinetische Doppelschicht-Oberflächenmodell K2-SURF entwickelt, welches den Abbau von PAK auf Aerosolpartikeln in Gegenwart von Ozon, Stickstoffdioxid, Wasserdampf, Hydroxyl- und Nitrat-Radikalen beschreibt. Kompetitive Adsorption und chemische Transformation der Oberfläche führen zu einer stark nicht-linearen Abhängigkeit der Ozon-Aufnahme bezüglich Gaszusammensetzung. Unter atmosphärischen Bedingungen reicht die chemische Lebensdauer von PAK von wenigen Minuten auf Ruß, über mehrere Stunden auf organischen und anorganischen Feststoffen bis hin zu Tagen auf flüssigen Partikeln. rn Anschließend wurde das kinetische Mehrschichtenmodell KM-SUB entwickelt um die chemische Transformation organischer Aerosolpartikel zu beschreiben. KM-SUB ist in der Lage, Transportprozesse und chemische Reaktionen an der Oberfläche und im Bulk von Aerosol-partikeln explizit aufzulösen. Es erforder im Gegensatz zu früheren Modellen keine vereinfachenden Annahmen über stationäre Zustände und radiale Durchmischung. In Kombination mit Literaturdaten und neuen experimentellen Ergebnissen wurde KM-SUB eingesetzt, um die Effekte von Grenzflächen- und Bulk-Transportprozessen auf die Ozonolyse und Nitrierung von Protein-Makromolekülen, Ölsäure, und verwandten organischen Ver¬bin-dungen aufzuklären. Die in dieser Studie entwickelten kinetischen Modelle sollen als Basis für die Entwicklung eines detaillierten Mechanismus für Aerosolchemie dienen sowie für das Herleiten von vereinfachten, jedoch realistischen Parametrisierungen für großskalige globale Atmosphären- und Klima-Modelle. rn Die in dieser Studie durchgeführten Experimente und Modellrechnungen liefern Beweise für die Bildung langlebiger reaktiver Sauerstoff-Intermediate (ROI) in der heterogenen Reaktion von Ozon mit Aerosolpartikeln. Die chemische Lebensdauer dieser Zwischenformen beträgt mehr als 100 s, deutlich länger als die Oberflächen-Verweilzeit von molekularem O3 (~10-9 s). Die ROIs erklären scheinbare Diskrepanzen zwischen früheren quantenmechanischen Berechnungen und kinetischen Experimenten. Sie spielen eine Schlüsselrolle in der chemischen Transformation sowie in den negativen Gesundheitseffekten von toxischen und allergenen Feinstaubkomponenten, wie Ruß, PAK und Proteine. ROIs sind vermutlich auch an der Zersetzung von Ozon auf mineralischem Staub und an der Bildung sowie am Wachstum von sekundären organischen Aerosolen beteiligt. Darüber hinaus bilden ROIs eine Verbindung zwischen atmosphärischen und biosphärischen Mehrphasenprozessen (chemische und biologische Alterung).rn Organische Verbindungen können als amorpher Feststoff oder in einem halbfesten Zustand vorliegen, der die Geschwindigkeit von heterogenen Reaktionenen und Mehrphasenprozessen in Aerosolen beeinflusst. Strömungsrohr-Experimente zeigen, dass die Ozonaufnahme und die oxidative Alterung von amorphen Proteinen durch Bulk-Diffusion kinetisch limitiert sind. Die reaktive Gasaufnahme zeigt eine deutliche Zunahme mit zunehmender Luftfeuchte, was durch eine Verringerung der Viskosität zu erklären ist, bedingt durch einen Phasenübergang der amorphen organischen Matrix von einem glasartigen zu einem halbfesten Zustand (feuchtigkeitsinduzierter Phasenübergang). Die chemische Lebensdauer reaktiver Verbindungen in organischen Partikeln kann von Sekunden bis zu Tagen ansteigen, da die Diffusionsrate in der halbfesten Phase bei niedriger Temperatur oder geringer Luftfeuchte um Größenordnungen absinken kann. Die Ergebnisse dieser Studie zeigen wie halbfeste Phasen die Auswirkung organischeer Aerosole auf Luftqualität, Gesundheit und Klima beeinflussen können. rn

Mathematical Optimization Applied to Thermal and Electrical Energy Systems

This Thesis aims at building and discussing mathematical models applications focused on Energy problems, both on the thermal and electrical side. The objective is to show how mathematical programming techniques developed within Operational Research can give useful answers in the Energy Sector, how they can provide tools to support decision making processes of Companies operating in the Energy production and distribution and how they can be successfully used to make simulations and sensitivity analyses to better understand the state of the art and convenience of a particular technology by comparing it with the available alternatives. The first part discusses the fundamental mathematical background followed by a comprehensive literature review about mathematical modelling in the Energy Sector. The second part presents mathematical models for the District Heating strategic network design and incremental network design. The objective is the selection of an optimal set of new users to be connected to an existing thermal network, maximizing revenues, minimizing infrastructure and operational costs and taking into account the main technical requirements of the real world application. Results on real and randomly generated benchmark networks are discussed with particular attention to instances characterized by big networks dimensions. The third part is devoted to the development of linear programming models for optimal battery operation in off-grid solar power schemes, with consideration of battery degradation. The key contribution of this work is the inclusion of battery degradation costs in the optimisation models. As available data on relating degradation costs to the nature of charge/discharge cycles are limited, we concentrate on investigating the sensitivity of operational patterns to the degradation cost structure. The objective is to investigate the combination of battery costs and performance at which such systems become economic. We also investigate how the system design should change when battery degradation is taken into account.

Closed-loop investigation of the dynamical properties of cardiomyocyte electrophysiology by means of Dynamic clamp and Mathematical modelling

The research field of my PhD concerns mathematical modeling and numerical simulation, applied to the cardiac electrophysiology analysis at a single cell level. This is possible thanks to the development of mathematical descriptions of single cellular components, ionic channels, pumps, exchangers and subcellular compartments. Due to the difficulties of vivo experiments on human cells, most of the measurements are acquired in vitro using animal models (e.g. guinea pig, dog, rabbit). Moreover, to study the cardiac action potential and all its features, it is necessary to acquire more specific knowledge about single ionic currents that contribute to the cardiac activity. Electrophysiological models of the heart have become very accurate in recent years giving rise to extremely complicated systems of differential equations. Although describing the behavior of cardiac cells quite well, the models are computationally demanding for numerical simulations and are very difficult to analyze from a mathematical (dynamical-systems) viewpoint. Simplified mathematical models that capture the underlying dynamics to a certain extent are therefore frequently used. The results presented in this thesis have confirmed that a close integration of computational modeling and experimental recordings in real myocytes, as performed by dynamic clamp, is a useful tool in enhancing our understanding of various components of normal cardiac electrophysiology, but also arrhythmogenic mechanisms in a pathological condition, especially when fully integrated with experimental data.

Nanotoxicology: a perspective and discussion of whether or not in vitro testing is a valid alternative

Despite the many proposed advantages related to nanotechnology, there are increasing concerns as to the potential adverse human health and environmental effects that the production of, and subsequent exposure to nanoparticles (NPs) might pose. In regard to human health, these concerns are founded upon the plethora of knowledge gained from research relating to the effects observed following exposure to environmental air pollution. It is known that increased exposure to environmental air pollution can cause reduced respiratory health, as well as exacerbate pre-existing conditions such as cardiovascular disease and chronic obstructive pulmonary disease. Such disease states have also been associated with exposure to the NP component contained within environmental air pollution, raising concerns as to the effects of NP exposure. It is not only exposure to accidentally produced NPs however, which should be approached with caution. Over the past decades, NPs have been specifically engineered for a wide range of consumer, industrial and technological applications. Due to the inevitable exposure of NPs to humans, owing to their use in such applications, it is therefore imperative that an understanding of how NPs interact with the human body is gained. In vivo research poses a beneficial model for gaining immediate and direct knowledge of human exposure to such xenobiotics. This research outlook however, has numerous limitations. Increased research using in vitro models has therefore been performed, as these models provide an inexpensive and high-throughput alternative to in vivo research strategies. Despite such advantages, there are also various restrictions in regard to in vitro research. Therefore, the aim of this review, in addition to providing a short perspective upon the field of nanotoxicology, is to discuss (1) the advantages and disadvantages of in vitro research and (2) how in vitro research may provide essential information pertaining to the human health risks posed by NP exposure.

Effect of pulsatility on the mathematical modeling of rotary blood pumps

In this study, the effect of time derivatives of flow rate and rotational speed was investigated on the mathematical modeling of a rotary blood pump (RBP). The basic model estimates the pressure head of the pump as a dependent variable using measured flow and speed as predictive variables. Performance of the model was evaluated by adding time derivative terms for flow and speed. First, to create a realistic working condition, the Levitronix CentriMag RBP was implanted in a sheep. All parameters from the model were physically measured and digitally acquired over a wide range of conditions, including pulsatile speed. Second, a statistical analysis of the different variables (flow, speed, and their time derivatives) based on multiple regression analysis was performed to determine the significant variables for pressure head estimation. Finally, different mathematical models were used to show the effect of time derivative terms on the performance of the models. In order to evaluate how well the estimated pressure head using different models fits the measured pressure head, root mean square error and correlation coefficient were used. The results indicate that inclusion of time derivatives of flow and speed can improve model accuracy, but only minimally.