Assessment of myocardial edema and area-at-risk in acute myocardial infarction by CMR: Evaluation of a novel T2-mapping method

Objectives. The goal of this study is to evaluate a T2-mapping sequence by: (i) measuring the reproducibility intra- and inter-observer variability in healthy volunteers in two separate scanning session with a T2 reference phantom; (2) measuring the mean T2 relaxation times by T2-mapping in infarcted myocardium in patients with subacute MI and compare it with patient's the gold standard X-ray coronary angiography and healthy volunteers results. Background. Myocardial edema is a consequence of an inflammation of the tissue, as seen in myocardial infarct (MI). It can be visualized by cardiovascular magnetic resonance (CMR) imaging using the T2 relaxation time. T2-mapping is a quantitative methodology that has the potential to address the limitation of the conventional T2-weighted (T2W) imaging. Methods. The T2-mapping protocol used for all MRI scans consisted in a radial gradient echo acquisition with a lung-liver navigator for free-breathing acquisition and affine image registration. Mid-basal short axis slices were acquired.T2-maps analyses: 2 observers semi- automatically segmented the left ventricle in 6 segments accordingly to the AHA standards. 8 healthy volunteers (age: 27 ± 4 years; 62.5% male) were scanned in 2 separate sessions. 17 patients (age : 61.9 ± 13.9 years; 82.4% male) with subacute STEMI (70.6%) and NSTEMI underwent a T2-mapping scanning session. Results. In healthy volunteers, the mean inter- and intra-observer variability over the entire short axis slice (segment 1 to 6) was 0.1 ms (95% confidence interval (CI): -0.4 to 0.5, p = 0.62) and 0.2 ms (95% CI: -2.8 to 3.2, p = 0.94, respectively. T2 relaxation time measurements with and without the correction of the phantom yielded an average difference of 3.0 ± 1.1 % and 3.1 ± 2.1 % (p = 0.828), respectively. In patients, the inter-observer variability in the entire short axis slice (S1-S6), was 0.3 ms (95% CI: -1.8 to 2.4, p = 0.85). Edema location as determined through the T2-mapping and the coronary artery occlusion as determined on X-ray coronary angiography correlated in 78.6%, but only in 60% in apical infarcts. All except one of the maximal T2 values in infarct patients were greater than the upper limit of the 95% confidence interval for normal myocardium. Conclusions. The T2-mapping methodology is accurate in detecting infarcted, i.e. edematous tissue in patients with subacute infarcts. This study further demonstrated that this T2-mapping technique is reproducible and robust enough to be used on a segmental basis for edema detection without the need of a phantom to yield a T2 correction factor. This new quantitative T2-mapping technique is promising and is likely to allow for serial follow-up studies in patients to improve our knowledge on infarct pathophysiology, on infarct healing, and for the assessment of novel treatment strategies for acute infarctions.

Radiolabeling of monoclonal antibody against carcinoembryonic antigen with 88Y and biodistribution studies.

The biodistribution of the 202 monoclonal antibody against CEA labeled with 88Y by the bicyclic DTPA anhydride method was studied in normal Balb/c mice. The in vitro binding to 1 X 10(7) CO112, LS174T and WiDR colon cancer cells was 21.0, 27.3 and 18.8%, respectively. The binding to an equal number of KM-3 leukemia cells and normal human lymphocytes was 8.9 and 3.2%, respectively. Liver, spleen, kidney and blood were the tissues that showed the highest uptake of radiolabeled antibody in vivo.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

IX ASMOSIA International Conference Interdisciplinary Studies on Ancient Stone: Tarragona, 8-13th June 2009 (Book of abstracts)

Aquesta obra recull els resums de les comunicacions orals i pòsters que es van presentar durant el IX Congrés Internacional de l’Association for the Study of Marbles and Other Stones in Antiquity (ASMOSIA), organitzat per l’ICAC en el marc del programa de recerca HAR2008-04600/HIST, amb el suport del programa d’Ajuts ARCS 2008 (referència expedient IR036826) de la Generalitat de Catalunya i del Ministeri de Ciència i Innovació (Accions Complementàries HAR2008-03181-E/HIST), i celebrat a Tarragona entre el 8 i el 13 de juny del 2009.

Onondaga chert : geological and palynological studies as applied to archaeology /

Cherts from the Middle Devonian Onondaga Formation of the Niagara Peninsula in Southern Ontario and Western New York State can now be distinguished from those of the Early Devonian Bois Blanc Formation of the same area based on differences in petrology, acritarchs, spores, and "Preservation Ratio" values. The finely crystalline, carbonate sediments of the Bois Blanc Formation were deposited under shallow, low energy conditions characterised by the acritarchs Leiofusa bacillum and L. minuta and a high relative abundance of the spore, Apiculiretusispora minor. The medio crystalline and bioclastic carbonate sediments of the Onondaga Formation were deposited under shallow, high energy conditions except for the finely crystalline lagoonal sediments of the Clarence Member which is characterised by the acritarchs Leiofusa navicula, L. sp. B, and L. tomaculata . The author has subdivided and correlated the Clarence Member of the Onondaga Formation using the "Preservation Ratio" values derived from the palynomorphs contained in the cherts. Clarence Member cherts were used by the Archaic people of the Niagara Peninsula for chipped-stone tools. The source area for the chert is considered to be the cobble beach deposits along the north shore of Lake Erie from Port Maitland to Nanticoke

Chemical and Biochemical Studies on Natural Antioxidants from sesamum Species

In the present study on natural antioxidants, the focus has been kept mainly on oil seeds, especially sesame and its by-products. Sesame, which has been under cultivation in India for centuries is called the 'Queen of oil seed crops' because of the high yield of oil obtained and the nutritional qualities of the seed, oil, and meal. Though India is the largest producer of sesame in the world, research on the various health benefits of sesame has been carried out by Japanese Sesame has an important place in the foods and tradit..ional medicine of India from time immemorial. Foreseeing the potential of sesame and its byproducts as an important antioxidant source and its availability in bulk, the present study was focussed on Sesamum species. There are not many reports on the wild species of Sesamum in India, especially of the Kerala region. Hence, in the present study we also included antioxidants of Sesamurnrnalabaricumdistributed throughout the coastal region.The important characteristics of sesame are attributed to the presence of the umquc compounds lignans. Lignans arc a group of natural products of phenyl propanoid ongm, whieh are widely distributed in nature. They display important physiological functions in plants, in human nutrition and medicine, given their extensive health promotive and curative properties. Much interest has been focussed on their effectiveness as antineoplastic agents and research in this area has revealed several modes of action by which they can regulate the growth of mammalian cells. Sesame is an important source of furofuran lignans, of which sesamin and the rare oxygenated derivative sesamoIin are the most abundant. Others include sesamol and glucosides of lignans. Sesarnin and episesamin are reported to have hypocholesterolemic effect, suppressive effect on chemically induced cancer, alleviation of allergy symptoms etc. Sesamol, sesamolin and the lignan glycosides are reported to inhibit lipid peroxidation. Present investigation on sesame and its byproducts have been carried out to explore the possibility of developing a natural antioxidant extract from available resources to be used as a substitute to synthetic ones in vegetable oils and foods. Preliminary analysis showed that sesame cake, a byproduct could still be utilized as a major source of lignans. Sesame cake, which is now used only as a cattlefeed, can be better utilized in the form of a valuable antioxidant source. The present study explains the development of a feasible process for the extraction of antioxidant compounds from sesame cake. The antioxidant extract so prepared from sesame cake has been tested for vegetable oil protection and is found to be effective at low concentration. In addition, studies also include the antioxidant, radical scavenging, anticancer, mosquitocidal and pesticidal activities of extract and individual compounds.

Fluorescence characterization and gain studies on a dye-doped graded index polymer optical-fiber preform

Preparation of an appropriate optical-fiber preform is vital for the fabrication of graded-index polymer optical fibers (GIPOF), which are considered to be a good choice for providing inexpensive high bandwidth data links, for local area networks and telecommunication applications. Recent development of the interfacial gel polymerization technique has caused a dramatic reduction in the total attenuation in GIPOF, and this is one of the potential methods to prepare fiber preforms for the fabrication of dye-doped polymer-fiber amplifiers. In this paper, the preparation of a dye-doped graded-index poly(methyl methacrylate) (PMMA) rod by the interfacial gel polymerization method using a PMMA tube is reported. An organic compound of high-refractive index, viz., diphenyl phthalate (DPP), was used to obtain a graded-index distribution, and Rhodamine B (Rh B), was used to dope the PMMA rod. The refractive index profile of the rod was measured using an interferometric technique and the index exponent was estimated. The single pass gain of the rod was measured at a pump wavelength of 532 nm. The extent of doping of the Rh B in the preform was studied by axially exciting a thin slice of the rod with white light and measuring the spatial variation of the fluorescence intensity across the sample.

Novel Approaches to Biodegradable Polymers: Synthesis and Biodegradation Studies

Biodegradable polymers have opened an emerging area of great interest because they are the ultimate solution for the disposal problems of synthetic polymers used for short time applications in the environmental and biomedical field. The biodegradable polymers available until recently have a number of limitations in terms of strength and dimensional stability. Most of them have processing problems and are also very expensive. Recent developments in biodegradable polymers show that monomers and polymers obtained from renewable resources are important owing to their inherent biodegradability, biocompatibility and easy availability. The present study is, therefore, mostly concemed with the utilization of renewable resources by effecting chemical modification/copolymerization on existing synthetic polymers/natural polymers for introducing better biodegradability and material properties.The thesis describes multiple approaches in the design of new biodegradable polymers: (1) Chemical modification of an existing nonbiodegradable polymer, polyethylene, by anchoring monosaccharides after functionalization to introduce biodegradability. (2) Copolymerization of an existing biodegradable polymer, polylactide, with suitable monomers and/or polymers to tailor their properties to suit the emerging requirements such as (2a) graft copolymerization of lactide onto chitosan to get controlled solvation and biodegradability and (2b) copolymerization of polylactide with cycloaliphatic amide segments to improve upon the thermal properties and processability.

Synthesis, spectral and structural studies of transition metal complexes of N(4)-substituted semicarbazones

The thesis is an introduction to our attempts to evaluate the coordination behaviour of a few compounds of our interest. Semicarbazones and their metal complexes have been an active area of research during the past years because of the beneficial biological activities of these substances. Tridentate NNO semicarbazone systems formed from heterocyclic and aromatic carbonyl compounds and their transition metal complexes are well-authenticated compounds in this field and their synthesis and characterization are well desirable. Hence, we decided to develop a research program aimed at the synthesis and characterization of novel semicarbazones derived from 2-benzoylpyridine and 2-acetylpyridine and their transition metal complexes. In addition to various physicochemical methods of analysis, single crystal X—Ray diffraction studies were also used for the characterization of the complexes.

Synthesis,characterization and application studies of some polymer supported metal complexes

Polymer supports are efficient reagents,substrates and catalysts and they are extensively used for carrying out reactions at controlled rates.Tailor-made polymer supports are highly versatile which have opened an excellent area of research.Now polymer supported chemistry is being exploited at an amazing rate and it seems to join the routine world of organic synthesis.Polymer supported ligands are found to be efficient complexing agents whose high selectivity enables the analysis and removal of heavy metal ions which are toxic to all the living organisms of land and sea.polymer supported membranes function as ion selective potentiometric sensors which allow the exchange of specific ions among other ions of the same charge.In this investigation three series of polymeric schiff bases and three series of metal complexes have been prepared.An attempt is done to develop optimum conditions for the removal of heavy metal ions using polymeric schiff bases.A novel copper sensor electrode have also been prepared from polymer supported metal complex.

Development and parametric studies of pulsed nitrogen and d-switched nd:glass lasers and some of their applications

Laser engineering is an area in which developments in the existing design concepts and technology appear at an alarming rate. Now—a-days, emphasis has shifted from innovation to cost reduction and system improvement. To a major extent, these studies are aimed at attaining larger power densities, higher system efficiency and identification of new lasing media and new lasing wavelengths. Todate researchers have put to use all the ditferent Forms of matter as lasing material. Laser action was observed For the first time in a gaseous system - the He-Ne system. This was Followed by a variety of solidstate and gas laser systems. Uarious organic dyes dissolved in suitable solvents were found to lase when pumped optically. Broad band emission characteristics of these dye molecules made wavelength tuning possible using optical devices. Laser action was also observed in certain p-n junctions of semiconductor materials and some of these systems are also tunable. The recent addition to this list was the observation of laser action from certain laser produced plasmas. The purpose of this investigation was to examine the design and Fabrication techniques of pulsed Nitrogen lasers and high power Nd: Glass laserso Attempt was also made to put the systems developed into certain related experiments

Mineralogical And Sedimentological Studies Of Innershelf And Beach Sediments Along The Coast Between Paravur And Kovalam, South Kerala, India

Continental shelf is of particular significance in marine geology , because it links the two basically different structural zones in the earth's crust; the continents and ocean basins. The shelf area has much wider importance in many fields of activity such as scientific, economic, social, political and strategic. The pace of development has ultimately put pressure on mankind to look for exploitable resources and accessibility to the continental shelf area and beyond. Added to the above, the developmental activities in the coastal area would readily and directly influence the innershelf sediments. This situation demands a thorough geological knowledge of the continental shelf area. Moreover, a successful management of the continental shelf zone requires an optimum data base on the physico-chemical nature of the shelf sediments. Although sedimentological studies were carried out along the western continental shelf of India, a well documented systematic study of the inner shelf off Trivandrum coast is still found to be lacking. Considering the physiographic settings and the vicinity of two renowned placer deposits at Chavara and Manavalakurichi, such a sedimetological inventory has become all the more vital. In view of the above, a research programme has been drawn up to account the salient sedimentological and mineralogical aspects of the innershelf and beach sediments between Paravur and Kovalam, Trivandrum district, Kerala (latitudes 8° 7'00" to 8° 47'45" and longitudes 76°43'00" to 77° 40'45"). The findings are presented in six chapters formatted to address the aim of this research.