Identification of stock units of Mullus barbatus (Linnaeus, 1758) in the Italian seas: development of genomic 2b-RAD markers and biological variation analysis.

This thesis is settled within the STOCKMAPPING project, which represents one of the studies that were developed in the framework of RITMARE Flagship project. The main goals of STOCKMAPPING were the creation of a genomic mapping for stocks of demersal target species and the assembling of a database of population genomic, in order to identify stocks and stocks boundaries. The thesis focuses on three main objectives representing the core for the initial assessment of the methodologies and structure that would be applied to the entire STOCKMAPPING project: individuation of an analytical design to identify and locate stocks and stocks boundaries of Mullus barbatus, application of a multidisciplinary approach to validate biological methods and an initial assessment and improvement for the genotyping by sequencing technique utilized (2b-RAD). The first step is the individuation of an analytical design that has to take in to account the biological characteristics of red mullet and being representative for STOCKMAPPING commitments. In this framework a reduction and selection steps was needed due to budget reduction. Sampling areas were ranked according the individuation of four priorities. To guarantee a multidisciplinary approach the biological data associated to the collected samples were used to investigate differences between sampling areas and GSAs. Genomic techniques were applied to red mullet for the first time so an initial assessment of molecular protocols for DNA extraction and 2b-RAD processing were needed. At the end 192 good quality DNAs have been extracted and eight samples have been processed with 2b-RAD. Utilizing the software Stacks for sequences analyses a great number of SNPs markers among the eight samples have been identified. Several tests have been performed changing the main parameter of the Stacks pipeline in order to identify the most explicative and functional sets of parameters.

Radiotherapy with scanning carbon ion beams: biological dose analysis for partial treatment delivery

L’uso di particelle cariche pesanti in radioterapia prende il nome di adroterapia. L’adroterapia permette l’irraggiamento di un volume bersaglio minimizzando il danno ai tessuti sani circostanti rispetto alla radioterapia tradizionale a raggi X. Le proprietà radiobiologiche degli ioni carbonio rappresentano un problema per i modelli radiobiologici a causa della non linearità della loro efficacia biologica. In questa tesi presenteremo gli algoritmi che possono essere usati per calcolare la dose fisica e biologica per un piano di trattamento del CNAO (Centro Nazionale Adroterapia Oncologica). Un caso di particolare interesse è l’eventualità che un piano di trattamento venga interrotto prima del dovuto. A causa della non linearità della sopravvivenza cellulare al variare della quantità di dose ricevuta giornalmente, è necessario studiare gli effetti degli irraggiamenti parziali utilizzando algoritmi che tengano conto delle tante variabili che caratterizzano sia i fasci di ioni che i tessuti irraggiati. Nell'ambito di questa tesi, appositi algoritmi in MATLAB sono stati sviluppati e implementati per confrontare la dose biologica e fisica assorbita nei casi di trattamento parziale.

Multiplex network analysis with application to biological high-throughput data

In questa tesi vengono studiate alcune caratteristiche dei network a multiplex; in particolare l'analisi verte sulla quantificazione delle differenze fra i layer del multiplex. Le dissimilarita sono valutate sia osservando le connessioni di singoli nodi in layer diversi, sia stimando le diverse partizioni dei layer. Sono quindi introdotte alcune importanti misure per la caratterizzazione dei multiplex, che vengono poi usate per la costruzione di metodi di community detection . La quantificazione delle differenze tra le partizioni di due layer viene stimata utilizzando una misura di mutua informazione. Viene inoltre approfondito l'uso del test dell'ipergeometrica per la determinazione di nodi sovra-rappresentati in un layer, mostrando l'efficacia del test in funzione della similarita dei layer. Questi metodi per la caratterizzazione delle proprieta dei network a multiplex vengono applicati a dati biologici reali. I dati utilizzati sono stati raccolti dallo studio DILGOM con l'obiettivo di determinare le implicazioni genetiche, trascrittomiche e metaboliche dell'obesita e della sindrome metabolica. Questi dati sono utilizzati dal progetto Mimomics per la determinazione di relazioni fra diverse omiche. Nella tesi sono analizzati i dati metabolici utilizzando un approccio a multiplex network per verificare la presenza di differenze fra le relazioni di composti sanguigni di persone obese e normopeso.

Electron energy-loss spectroscopy as a tool for elemental analysis in biological speciments.

A transmission electron microscope (TEM) accessory, the energy filter, enables the establishment of a method for elemental microanalysis, the electron energy-loss spectroscopy (EELS). In conventional TEM, unscattered, elastic, and inelastic scattered electrons contribute to image information. Energy-filtering TEM (EFTEM) allows elemental analysis at the ultrastructural level by using selected inelastic scattered electrons. EELS is an excellent method for elemental microanalysis and nanoanalysis with good sensitivity and accuracy. However, it is a complex method whose potential is seldom completely exploited, especially for biological specimens. In addition to spectral analysis, parallel-EELS, we present two different imaging techniques in this chapter, namely electron spectroscopic imaging (ESI) and image-EELS. We aim to introduce these techniques in this chapter with the elemental microanalysis of titanium. Ultrafine, 22-nm titanium dioxide particles are used in an inhalation study in rats to investigate the distribution of nanoparticles in lung tissue.

GH mutant (R77C) in a pedigree presenting with the delay of growth and pubertal development: structural analysis of the mutant and evaluation of the biological activity

A heterozygous missense mutation in the GH-1 gene converting codon 77 from arginine (R) to cysteine (C), which was previously reported to have some GH antagonistic effect, was identified in a Syrian family. The index patient, a boy, was referred for assessment of his short stature (-2.5 SDS) at the age of 6 years. His mother and grandfather were also carrying the same mutation, but did not differ in adult height from the other unaffected family members. Hormonal examination in all affected subjects revealed increased basal GH, low IGF-I concentrations, and subnormal IGF-I response in generation test leading to the diagnosis of partial GH insensitivity. However, GH receptor gene (GHR) sequencing demonstrated no abnormalities. As other family members carrying the GH-R77C form showed similar alterations at the hormonal level, but presented with normal final height, no GH therapy was given to the boy, but he was followed through his pubertal development which was delayed. At the age of 20 years he reached his final height, which was normal within his parental target height. Functional characterization of the GH-R77C, assessed through activation of Jak2/Stat5 pathway, revealed no differences in the bioactivity between wild-type-GH (wt-GH) and GH-R77C. Detailed structural analysis indicated that the structure of GH-R77C, in terms of disulfide bond formation, is almost identical to that of the wt-GH despite the introduced mutation (Cys77). Previous studies from our group demonstrated a reduced capability of GH-R77C to induce GHR/GH-binding protein (GHBP) gene transcription rate when compared with wt-GH. Therefore, reduced GHR/GHBP expression might well be the possible cause for the partial GH insensitivity found in our patients. In addition, this group of patients deserve further attention because they could represent a distinct clinical entity underlining that an altered GH peptide may also have a direct impact on GHR/GHBP gene expression causing partial GH insensitivity. This might be responsible for the delay of growth and pubertal development. Finally, we clearly demonstrate that GH-R77C is not invariably associated with short stature, but that great care needs to be taken in ascribing growth failure to various heterozygous mutations affecting the GH-IGF axis and that careful functional studies are mandatory.

IDENTIFICATION OF GENES CONTROLLING BIOLOGICAL PROCESSES AND PATHWAYS THROUGH STATISTICAL ANALYSIS AND NETWORK RECONSTRUCTION

The developmental processes and functions of an organism are controlled by the genes and the proteins that are derived from these genes. The identification of key genes and the reconstruction of gene networks can provide a model to help us understand the regulatory mechanisms for the initiation and progression of biological processes or functional abnormalities (e.g. diseases) in living organisms. In this dissertation, I have developed statistical methods to identify the genes and transcription factors (TFs) involved in biological processes, constructed their regulatory networks, and also evaluated some existing association methods to find robust methods for coexpression analyses. Two kinds of data sets were used for this work: genotype data and gene expression microarray data. On the basis of these data sets, this dissertation has two major parts, together forming six chapters. The first part deals with developing association methods for rare variants using genotype data (chapter 4 and 5). The second part deals with developing and/or evaluating statistical methods to identify genes and TFs involved in biological processes, and construction of their regulatory networks using gene expression data (chapter 2, 3, and 6). For the first part, I have developed two methods to find the groupwise association of rare variants with given diseases or traits. The first method is based on kernel machine learning and can be applied to both quantitative as well as qualitative traits. Simulation results showed that the proposed method has improved power over the existing weighted sum method (WS) in most settings. The second method uses multiple phenotypes to select a few top significant genes. It then finds the association of each gene with each phenotype while controlling the population stratification by adjusting the data for ancestry using principal components. This method was applied to GAW 17 data and was able to find several disease risk genes. For the second part, I have worked on three problems. First problem involved evaluation of eight gene association methods. A very comprehensive comparison of these methods with further analysis clearly demonstrates the distinct and common performance of these eight gene association methods. For the second problem, an algorithm named the bottom-up graphical Gaussian model was developed to identify the TFs that regulate pathway genes and reconstruct their hierarchical regulatory networks. This algorithm has produced very significant results and it is the first report to produce such hierarchical networks for these pathways. The third problem dealt with developing another algorithm called the top-down graphical Gaussian model that identifies the network governed by a specific TF. The network produced by the algorithm is proven to be of very high accuracy.

Quantitative analysis of arachidonic acid, endocannabinoids, N-acylethanolamines and steroids in biological samples by LCMS/MS: Fit to purpose.

Arachidonic acid (5Z,8Z,11Z,14Z-eicosatetraenoic acid; C20:4) (arachidonate, AA) is a vital polyunsaturated omega-6 fatty acid (PUFA) without its presence the mammalian brain, muscles, and possibly other organs cannot develop or function [1] and [2]. AA fulfils numerous known and possibly yet unknown functions as integral part of mammalian phospholipid membranes and as free AA which also acts as a precursor of a variety of biologically active lipid mediators generally referred to as eicosanoids (e.g., prostaglandins, leukotrienes). A more recent class of eicosanoids is composed of the endogenous cannabinoids (endocannabinoids) 2-arachidonoyl glycerol (2-AG) and arachidonoyl ethanolamide (anandamide, AEA), which act on cannabinoid CB1 and CB2 receptors but also modulate ion channels and nuclear receptors [3] and [4]. In recent years, the role of endocannabinoids as prominent anti-inflammatory and neuromodulatory eicosanoids has been shown by numerous studies [5].

SOCIAL AND BIOLOGICAL DETERMINANTS OF SHORT-TERM GROWTH VELOCITY AMONG PRESCHOOLERS OF RURAL GUATEMALA: A PATH ANALYSIS APPROACH (WEIGHT-GAIN, IRON DEFICIENCY, GASTROINTESTINAL SYMPTOMS)

This dissertation develops and tests through path analysis a theoretical model to explain how socioeconomic, socioenvironmental, and biologic risk factors simultaneously influence each other to further produce short-term, depressed growth in preschoolers. Three areas of risk factors were identified: child's proximal environment, maturational stage, and biological vulnerability. The theoretical model represented both the conceptual framework and the nature and direction of the hypotheses. Original research completed in 1978-80 and in 1982 provided the background data. It was analyzed first by nested-analysis of variance, followed by path analysis. The study provided evidence of mild iron deficiency and gastrointestinal symptomatology in the etiology of depressed, short-term weight gain. Also, there was evidence suggesting that family resources for material and social survival significantly contribute to the variability of short-term, age-adjusted growth velocity. These results challenge current views of unifocal intervention, whether for prevention or control. For policy formulations, though, the mechanisms underlying any set of interlaced relationships must be decoded. Theoretical formulations here proposed should be reassessed under a more extensive research design. It is suggested that studies should be undertaken where social changes are actually in progress; otherwise, nutritional epidemiology in developing countries operates somewhere between social reality and research concepts, with little grasp of its real potential. The study stresses that there is a connection between substantive theory, empirical observation, and policy issues. ^

Biological treatment of wood preserving site groundwater by BioTrol, Inc. : applications analysis report.

Mode of access: Internet.

Manual for analysis of ethanol in biological liquids. Final report.

National Highway Traffic Safety Administration, Office of Driver and Pedestrian Research, Washington, D.C.

The analysis of fermentation acids; the qualitative and quantitative estimation of formic, acetic, propionic, butyric, and lactic acids in biological material ...

"Use of Duclaux method on various substances" (bibliography): p. 235-236. Bibliography: p. 245-277.

A vulnerability analysis of the temperate forests of south central Chile A vulnerability analysis of the temperate forests of south central Chile. Biological Conservation, 122 2005: 9-21.

Areas of the landscape that are priorities for conservation should be those that are both vulnerable to threatening processes and that if lost or degraded, will result in conservation targets being compromised. While much attention is directed towards understanding the patterns of biodiversity, much less is given to determining the areas of the landscape most vulnerable to threats. We assessed the relative vulnerability of remaining areas of native forest to conversion to plantations in the ecologically significant temperate rainforest region of south central Chile. The area of the study region is 4.2 million ha and the extent of plantations is approximately 200000 ha. First, the spatial distribution of native forest conversion to plantations was determined. The variables related to the spatial distribution of this threatening process were identified through the development of a classification tree and the generation of a multivariate. spatially explicit, statistical model. The model of native forest conversion explained 43% of the deviance and the discrimination ability of the model was high. Predictions were made of where native forest conversion is likely to occur in the future. Due to patterns of climate, topography, soils and proximity to infrastructure and towns, remaining forest areas differ in their relative risk of being converted to plantations. Another factor that may increase the vulnerability of remaining native forest in a subset of the study region is the proposed construction of a highway. We found that 90% of the area of existing plantations within this region is within 2.5 km of roads. When the predictions of native forest conversion were recalculated accounting for the construction of this highway, it was found that: approximately 27000 ha of native forest had an increased probability of conversion. The areas of native forest identified to be vulnerable to conversion are outside of the existing reserve network. (C) 2004 Elsevier Ltd. All tights reserved.

Optimisation of poly-b-hydroxyalkanoate analysis using gas chromatography for enhanced biological phosphorus removal systems

Poly-beta-hydroxyalkanoate (PHA) is a polymer commonly used in carbon and energy storage for many different bacterial cells. Polyphosphate accumulating organisms (PAOs) and glycogen accumulating organisms (GAOs), store PHA anaerobically through metabolism of carbon substrates such as acetate and propionate. Although poly-beta-hydroxybutyrate (PHB)and poly-beta-hydroxyvalerate (PHV) are commonly quantified using a previously developed gas chromatography (GC) method, poly-beta-hydroxy-2-methyl valerate (PH2MV) is seldom quantified despite the fact that it has been shown to be a key PHA fraction produced when PAOs or GAOs metabolise propionate. This paper presents two GC-based methods modified for extraction and quantification of PHB, PHV and PH2MV from enhanced biological phosphorus removal (EBPR) systems. For the extraction Of PHB and PHV from acetate fed PAO and GAO cultures, a 3% sulfuric acid concentration and a 2-20 h digestion time is recommended, while a 10% sulfuric acid solution digested for 20 h is recommended for PHV and PH2MV analysis from propionate fed EBPR systems. (c) 2005 Elsevier B.V. All rights reserved.

The applicability of recurrent neural networks for biological sequence analysis

Selection of machine learning techniques requires a certain sensitivity to the requirements of the problem. In particular, the problem can be made more tractable by deliberately using algorithms that are biased toward solutions of the requisite kind. In this paper, we argue that recurrent neural networks have a natural bias toward a problem domain of which biological sequence analysis tasks are a subset. We use experiments with synthetic data to illustrate this bias. We then demonstrate that this bias can be exploitable using a data set of protein sequences containing several classes of subcellular localization targeting peptides. The results show that, compared with feed forward, recurrent neural networks will generally perform better on sequence analysis tasks. Furthermore, as the patterns within the sequence become more ambiguous, the choice of specific recurrent architecture becomes more critical.