The cytochrome P-450 isoenzyme CYP2E1 in the biological processing of industrial chemicals : consequences for occupational and environmental medicine

The importance of the isoform CYP2E1 of the human cytochrome P-450 superfamily of enzymes for occupational and environmental medicine is derived from its unique substrate spectrum that includes a number of highly important high-production chemicals, such as aliphatic and aromatic hydrocarbons, solvents and industrial monomers (i.a. alkanes, alkenes, aromatic and halogenated hydrocarbons). Many polymorphic genes, such as CYP2E1, show considerable differences in allelic distribution between different human populations. The polymorphic nature of the human CYP2E1 gene is significant for inter-individual differences in toxicity of its substrates. Since the substrate spectrum of CYP2E1 includes many compounds of basic relevance to industrial toxicology, a rationale for metabolic interactions of different CYP2E1 substrates is provided. In-depth research into the inter-individual phenotypic differences of human CYP2E1 enzyme activities was enabled by the recognition that the 6-hydroxylation of the drug chlorzoxazone is mediated by CYP2E1. Studies on CYP2E1 phenotyping have pointed to inter-individual variations in enzyme activities. There are consistent ethnic differences in CYP2E1 enzyme expression, mostly demonstrated between European and Japanese populations, which point to a major impact of genetic factors. The most frequently studied genetic polymorphisms are the restriction fragment length polymorphisms PstI/RsaI (mutant allele: CYP2E1*5B) located in the 5′-flanking region of the gene, as well as the DraI polymorphism (mutant allele: CYP2E1*6) located in intron 6. These polymorphisms are partly related, as they form the common allele designated CYP2E1*5A. Striking inter-ethnic differences between Europeans and Asians appear with respect to the frequencies of the CYP2E1*5A allele (only approximately 5% of Europeans are heterozygous, but 37% of Asians are, whilst 6% of Asians are homozygous). Available studies indicate a wide variation in human CYP2E1 expression, which are very likely based on complex gene-environment interactions. Major inter-ethnic differences are apparent on the genotyping and the phenotyping levels. Selected cases are presented where inter-ethnic variations of CYP2E1 may provide likely explanations for unexplained findings concerning industrial chemicals that are CYP2E1 substrates. Possible consequences of differential inter-individual and inter-ethnic susceptibilities are related to individual expressions of clinical symptoms of chemical toxicity, to results of biological monitoring of exposed workers, and to the interpretation of results of epidemiological or molecular-epidemiological studies.

An evaluation into the potential of biological processing for the removal of metals from sewage sludges

The use of sewage sludge in agricultural land as a means of sludge disposal and recycling has been shown to be economical and suitable because of the presence of nutrients such as nitrogen and phosphorus. However, municipal sludges often contain high quantities of toxic metals and other compounds that must be removed for its safe use in agricultural soils. The biological leaching of metals from sewage sludges has been shown to be a promising technique for metal detoxifying in such complex matrix. The process efficiency is dependent on several physico-chemical parameters, such as total solids concentration, metal forms, pH-ORP, and temperature. Scale-up of the process has not yet been defined and is still pursuing the correct operational design. Current research involving the bioleaching of metals from sewage sludge and its application to land, which affects soil physical properties, are presented and discussed.

Hardware reconfigurável para geração de música harmonizada utilizando autômatos celulares.

Desde os primórdios da humanidade, a descoberta do método de processamento cerebral do som, e consequentemente da música, fazem parte do imaginário humano. Portanto, as pesquisas relacionadas a este processo constituem um dos mais vastos campos de estudos das áreas de ciências. Dentre as inúmeras tentativas para compreensão do processamento biológico do som, o ser humano inventou o processo automático de composição musical, com o intuito de aferir a possibilidade da realização de composições musicais de qualidade sem a imposição sentimental, ou seja, apenas com a utilização das definições e estruturas de música existentes. Este procedimento automático de composição musical, também denominado música aleatória ou música do acaso, tem sido vastamente explorado ao longo dos séculos, já tendo sido utilizado por alguns dos grandes nomes do cenário musical, como por exemplo, Mozart. Os avanços nas áreas de engenharia e computação permitiram a evolução dos métodos utilizados para composição de música aleatória, tornando a aplicação de autômatos celulares uma alternativa viável para determinação da sequência de execução de notas musicais e outros itens utilizados durante a composição deste tipo de música. Esta dissertação propõe uma arquitetura para geração de música harmonizada a partir de intervalos melódicos determinados por autômatos celulares, implementada em hardware reconfigurável do tipo FPGA. A arquitetura proposta possui quatro tipos de autômatos celulares, desenvolvidos através dos modelos de vizinhança unidimensional de Wolfram, vizinhança bidimensional de Neumann, vizinhança bidimensional Moore e vizinhança tridimensional de Neumann, que podem ser combinados de 16 formas diferentes para geração de melodias. Os resultados do processamento realizado pela arquitetura proposta são melodias no formato .mid, compostas através da utilização de dois autômatos celulares, um para escolha das notas e outro para escolha dos instrumentos a serem emulados, de acordo com o protocolo MIDI. Para tal esta arquitetura é formada por três unidades principais, a unidade divisor de frequência, que é responsável pelo sincronismo das tarefas executadas pela arquitetura, a unidade de conjunto de autômatos celulares, que é responsável pelo controle e habilitação dos autômatos celulares, e a unidade máquina MIDI, que é responsável por organizar os resultados de cada iteração corrente dos autômatos celulares e convertê-los conforme a estrutura do protocolo MIDI, gerando-se assim o produto musical. A arquitetura proposta é parametrizável, de modo que a configuração dos dados que influenciam no produto musical gerado, como por exemplo, a definição dos conjuntos de regras para os autômatos celulares habilitados, fica a cargo do usuário, não havendo então limites para as combinações possíveis a serem realizadas na arquitetura. Para validação da funcionalidade e aplicabilidade da arquitetura proposta, alguns dos resultados obtidos foram apresentados e detalhados através do uso de técnicas de obtenção de informação musical.

Upland streamwater nitrate dynamics across decadal to sub-daily timescales: a case study of Plynlimon, Wales

Streamwater nitrate dynamics in the River Hafren, Plynlimon, mid-Wales were investigated over decadal to sub-daily timescales using a range of statistical techniques. Long-term data were derived from weekly grab samples (1984–2010) and high-frequency data from 7-hourly samples (2007–2009) both measured at two sites: a headwater stream draining moorland and a downstream site below plantation forest. This study is one of the first to analyse upland streamwater nitrate dynamics across such a wide range of timescales and report on the principal mechanisms identified. The data analysis provided no clear evidence that the long-term decline in streamwater nitrate concentrations was related to a decline in atmospheric deposition alone, because nitrogen deposition first increased and then decreased during the study period. Increased streamwater temperature and denitrification may also have contributed to the decline in stream nitrate concentrations, the former through increased N uptake rates and the latter resultant from increased dissolved organic carbon concentrations. Strong seasonal cycles, with concentration minimums in the summer, were driven by seasonal flow minimums and seasonal biological activity enhancing nitrate uptake. Complex diurnal dynamics were observed, with seasonal changes in phase and amplitude of the cycling, and the diurnal dynamics were variable along the river. At the moorland site, a regular daily cycle, with minimum concentrations in the early afternoon, corresponding with peak air temperatures, indicated the importance of instream biological processing. At the downstream site, the diurnal dynamics were a composite signal, resultant from advection, dispersion and nitrate processing in the soils of the lower catchment. The diurnal streamwater nitrate dynamics were also affected by drought conditions. Enhanced diurnal cycling in Spring 2007 was attributed to increased nitrate availability in the post-drought period as well as low flow rates and high temperatures over this period. The combination of high-frequency short-term measurements and long-term monitoring provides a powerful tool for increasing understanding of the controls of element fluxes and concentrations in surface waters.

Industrial lab-on-a-chip: design, applications and scale-up for drug discovery and delivery

Microfluidics is an emerging and promising interdisciplinary technology which offers powerful platforms for precise production of novel functional materials (e.g., emulsion droplets, microcapsules, and nanoparticles as drug delivery vehicles- and drug molecules) as well as high-throughput analyses (e.g., bioassays, detection, and diagnostics). In particular, multiphase microfluidics is a rapidly growing technology and has beneficial applications in various fields including biomedicals, chemicals, and foods. In this review, we first describe the fundamentals and latest developments in multiphase microfluidics for producing biocompatible materials that are precisely controlled in size, shape, internal morphology and composition. We next describe some microfluidic applications that synthesize drug molecules, handle biological substances and biological units, and imitate biological organs. We also highlight and discuss design, applications and scale up of droplet- and flow-based microfluidic devices used for drug discovery and delivery.

Some aspects of information processing in biological vision

An attempt is made to present some challenging problems (mainly to the technically minded researchers) in the development of computational models for certain (visual) processes which are executed with, apparently, deceptive ease by the human visual system. However, in the interest of simplicity (and with a nonmathematical audience in mind), the presentation is almost completely devoid of mathematical formalism. Some of the findings in biological vision are presented in order to provoke some approaches to their computational models, The development of ideas is not complete, and the vast literature on biological and computational vision cannot be reviewed here. A related but rather specific aspect of computational vision (namely, detection of edges) has been discussed by Zucker, who brings out some of the difficulties experienced in the classical approaches.Space limitations here preclude any detailed analysis of even the elementary aspects of information processing in biological vision, However, the main purpose of the present paper is to highlight some of the fascinating problems in the frontier area of modelling mathematically the human vision system.

A conceptual matrix model for biological data processing

This paper proposes a conceptual matrix model with algorithms for biological data processing. The required elements for constructing a matrix model are discussed. The representative matrix-based methods and algorithms which have potentials in biological data processing are presented / proposed. Some application cases of the model in biological data processing are studied, which show the applicability of this model in various kinds of biological data processing. This conceptual model established a framework within which biological data processing and mining could be conducted. The model is also heuristic to other applications.

Adaptive multiscale biological signal processing

Biological processes are very complex mechanisms, most of them being accompanied by or manifested as signals that reflect their essential characteristics and qualities. The development of diagnostic techniques based on signal and image acquisition from the human body is commonly retained as one of the propelling factors in the advancements in medicine and biosciences recorded in the recent past. It is a fact that the instruments used for biological signal and image recording, like any other acquisition system, are affected by non-idealities which, by different degrees, negatively impact on the accuracy of the recording. This work discusses how it is possible to attenuate, and ideally to remove, these effects, with a particular attention toward ultrasound imaging and extracellular recordings. Original algorithms developed during the Ph.D. research activity will be examined and compared to ones in literature tackling the same problems; results will be drawn on the base of comparative tests on both synthetic and in-vivo acquisitions, evaluating standard metrics in the respective field of application. All the developed algorithms share an adaptive approach to signal analysis, meaning that their behavior is not dependent only on designer choices, but driven by input signal characteristics too. Performance comparisons following the state of the art concerning image quality assessment, contrast gain estimation and resolution gain quantification as well as visual inspection highlighted very good results featured by the proposed ultrasound image deconvolution and restoring algorithms: axial resolution up to 5 times better than algorithms in literature are possible. Concerning extracellular recordings, the results of the proposed denoising technique compared to other signal processing algorithms pointed out an improvement of the state of the art of almost 4 dB.

Computational modelling of human stem cell-derived cardiomyocytes - Texture descriptors for biological image processing

This thesis investigates two distinct research topics. The main topic (Part I) is the computational modelling of cardiomyocytes derived from human stem cells, both embryonic (hESC-CM) and induced-pluripotent (hiPSC-CM). The aim of this research line lies in developing models of the electrophysiology of hESC-CM and hiPSC-CM in order to integrate the available experimental data and getting in-silico models to be used for studying/making new hypotheses/planning experiments on aspects not fully understood yet, such as the maturation process, the functionality of the Ca2+ hangling or why the hESC-CM/hiPSC-CM action potentials (APs) show some differences with respect to APs from adult cardiomyocytes. Chapter I.1 introduces the main concepts about hESC-CMs/hiPSC-CMs, the cardiac AP, and computational modelling. Chapter I.2 presents the hESC-CM AP model, able to simulate the maturation process through two developmental stages, Early and Late, based on experimental and literature data. Chapter I.3 describes the hiPSC-CM AP model, able to simulate the ventricular-like and atrial-like phenotypes. This model was used to assess which currents are responsible for the differences between the ventricular-like AP and the adult ventricular AP. The secondary topic (Part II) consists in the study of texture descriptors for biological image processing. Chapter II.1 provides an overview on important texture descriptors such as Local Binary Pattern or Local Phase Quantization. Moreover the non-binary coding and the multi-threshold approach are here introduced. Chapter II.2 shows that the non-binary coding and the multi-threshold approach improve the classification performance of cellular/sub-cellular part images, taken from six datasets. Chapter II.3 describes the case study of the classification of indirect immunofluorescence images of HEp2 cells, used for the antinuclear antibody clinical test. Finally the general conclusions are reported.

Signal processing for molecular and cellular biological physics:an emerging field

Recent advances in our ability to watch the molecular and cellular processes of life in action-such as atomic force microscopy, optical tweezers and Forster fluorescence resonance energy transfer-raise challenges for digital signal processing (DSP) of the resulting experimental data. This article explores the unique properties of such biophysical time series that set them apart from other signals, such as the prevalence of abrupt jumps and steps, multi-modal distributions and autocorrelated noise. It exposes the problems with classical linear DSP algorithms applied to this kind of data, and describes new nonlinear and non-Gaussian algorithms that are able to extract information that is of direct relevance to biological physicists. It is argued that these new methods applied in this context typify the nascent field of biophysical DSP. Practical experimental examples are supplied.

Biologically inspired visual landmark processing for simultaneous localization and mapping

This paper illustrates a method for finding useful visual landmarks for performing simultaneous localization and mapping (SLAM). The method is based loosely on biological principles, using layers of filtering and pooling to create learned templates that correspond to different views of the environment. Rather than using a set of landmarks and reporting range and bearing to the landmark, this system maps views to poses. The challenge is to produce a system that produces the same view for small changes in robot pose, but provides different views for larger changes in pose. The method has been developed to interface with the RatSLAM system, a biologically inspired method of SLAM. The paper describes the method of learning and recalling visual landmarks in detail, and shows the performance of the visual system in real robot tests.

Digital processing of diffusion-tensor images of avascular tissues

Diffusion is the process that leads to the mixing of substances as a result of spontaneous and random thermal motion of individual atoms and molecules. It was first detected by the English botanist Robert Brown in 1827, and the phenomenon became known as ‘Brownian motion’. More specifically, the motion observed by Brown was translational diffusion – thermal motion resulting in random variations of the position of a molecule. This type of motion was given a correct theoretical interpretation in 1905 by Albert Einstein, who derived the relationship between temperature, the viscosity of the medium, the size of the diffusing molecule, and its diffusion coefficient. It is translational diffusion that is indirectly observed in MR diffusion-tensor imaging (DTI). The relationship obtained by Einstein provides the physical basis for using translational diffusion to probe the microscopic environment surrounding the molecule.