868 resultados para STRUCTURE-PROPERTY RELATIONSHIP


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The quantitative structure property relationship (QSPR) for the boiling point (Tb) of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) was investigated. The molecular distance-edge vector (MDEV) index was used as the structural descriptor. The quantitative relationship between the MDEV index and Tb was modeled by using multivariate linear regression (MLR) and artificial neural network (ANN), respectively. Leave-one-out cross validation and external validation were carried out to assess the prediction performance of the models developed. For the MLR method, the prediction root mean square relative error (RMSRE) of leave-one-out cross validation and external validation was 1.77 and 1.23, respectively. For the ANN method, the prediction RMSRE of leave-one-out cross validation and external validation was 1.65 and 1.16, respectively. A quantitative relationship between the MDEV index and Tb of PCDD/Fs was demonstrated. Both MLR and ANN are practicable for modeling this relationship. The MLR model and ANN model developed can be used to predict the Tb of PCDD/Fs. Thus, the Tb of each PCDD/F was predicted by the developed models.

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Les modèles pharmacocinétiques à base physiologique (PBPK) permettent de simuler la dose interne de substances chimiques sur la base de paramètres spécifiques à l’espèce et à la substance. Les modèles de relation quantitative structure-propriété (QSPR) existants permettent d’estimer les paramètres spécifiques au produit (coefficients de partage (PC) et constantes de métabolisme) mais leur domaine d’application est limité par leur manque de considération de la variabilité de leurs paramètres d’entrée ainsi que par leur domaine d’application restreint (c. à d., substances contenant CH3, CH2, CH, C, C=C, H, Cl, F, Br, cycle benzénique et H sur le cycle benzénique). L’objectif de cette étude est de développer de nouvelles connaissances et des outils afin d’élargir le domaine d’application des modèles QSPR-PBPK pour prédire la toxicocinétique de substances organiques inhalées chez l’humain. D’abord, un algorithme mécaniste unifié a été développé à partir de modèles existants pour prédire les PC de 142 médicaments et polluants environnementaux aux niveaux macro (tissu et sang) et micro (cellule et fluides biologiques) à partir de la composition du tissu et du sang et de propriétés physicochimiques. L’algorithme résultant a été appliqué pour prédire les PC tissu:sang, tissu:plasma et tissu:air du muscle (n = 174), du foie (n = 139) et du tissu adipeux (n = 141) du rat pour des médicaments acides, basiques et neutres ainsi que pour des cétones, esters d’acétate, éthers, alcools, hydrocarbures aliphatiques et aromatiques. Un modèle de relation quantitative propriété-propriété (QPPR) a été développé pour la clairance intrinsèque (CLint) in vivo (calculée comme le ratio du Vmax (μmol/h/kg poids de rat) sur le Km (μM)), de substrats du CYP2E1 (n = 26) en fonction du PC n octanol:eau, du PC sang:eau et du potentiel d’ionisation). Les prédictions du QPPR, représentées par les limites inférieures et supérieures de l’intervalle de confiance à 95% à la moyenne, furent ensuite intégrées dans un modèle PBPK humain. Subséquemment, l’algorithme de PC et le QPPR pour la CLint furent intégrés avec des modèles QSPR pour les PC hémoglobine:eau et huile:air pour simuler la pharmacocinétique et la dosimétrie cellulaire d’inhalation de composés organiques volatiles (COV) (benzène, 1,2-dichloroéthane, dichlorométhane, m-xylène, toluène, styrène, 1,1,1 trichloroéthane et 1,2,4 trimethylbenzène) avec un modèle PBPK chez le rat. Finalement, la variabilité de paramètres de composition des tissus et du sang de l’algorithme pour les PC tissu:air chez le rat et sang:air chez l’humain a été caractérisée par des simulations Monte Carlo par chaîne de Markov (MCMC). Les distributions résultantes ont été utilisées pour conduire des simulations Monte Carlo pour prédire des PC tissu:sang et sang:air. Les distributions de PC, avec celles des paramètres physiologiques et du contenu en cytochrome P450 CYP2E1, ont été incorporées dans un modèle PBPK pour caractériser la variabilité de la toxicocinétique sanguine de quatre COV (benzène, chloroforme, styrène et trichloroéthylène) par simulation Monte Carlo. Globalement, les approches quantitatives mises en œuvre pour les PC et la CLint dans cette étude ont permis l’utilisation de descripteurs moléculaires génériques plutôt que de fragments moléculaires spécifiques pour prédire la pharmacocinétique de substances organiques chez l’humain. La présente étude a, pour la première fois, caractérisé la variabilité des paramètres biologiques des algorithmes de PC pour étendre l’aptitude des modèles PBPK à prédire les distributions, pour la population, de doses internes de substances organiques avant de faire des tests chez l’animal ou l’humain.

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Descriptors and quantitative structure property relationships (QSPR) were investigated for mechanical property prediction of carbon nanotubes (CNTs). 78 molecular dynamics (MD) simulations were carried out, and 20 descriptors were calculated to build quantitative structure property relationships (QSPRs) for Young's modulus and Poisson's ratio in two separate analyses: vacancy only and vacancy plus methyl functionalization. In the first analysis, C N2/CT (number of non-sp2 hybridized carbons per the total carbons) and chiral angle were identified as critical descriptors for both Young's modulus and Poisson's ratio. Further analysis and literature findings indicate the effect of chiral angle is negligible at larger CNT radii for both properties. Raman spectroscopy can be used to measure CN2/C T, providing a direct link between experimental and computational results. Poisson's ratio approaches two different limiting values as CNT radii increases: 0.23-0.25 for chiral and armchair CNTs and 0.10 for zigzag CNTs (surface defects <3%). In the second analysis, the critical descriptors were CN2/CT, chiral angle, and MN/CT (number of methyl groups per total carbons). These results imply new types of defects can be represented as a new descriptor in QSPR models. Finally, results are qualified and quantified against experimental data. © 2013 American Chemical Society.

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To optimize solubility of drugs, current strategies mainly focus on engineering and screening of smart crystal phases. Two salts of the anti-human immunodeficiency virus (HIV) drug lamivudinenamely, lamivudine hydrochloride and lamivudine hydrochloride monohydrate, were prepared in the course of screening the crystallization conditions of lamivudine duplex, an uncommon DNA-mimic, double-stranded helical structure made up of partially protonated drug pairs. Here, water solubilities of lamivudine hydrochloride, lamivudine hydrochloride monohydrate, and lamivudine duplex are reported. The aqueous solubility of this anti-HIV drug was significantly increased in both salts and also in lamivudine duplex in relation to the water solubility of lamivudine form II. In comparison with the lamivudine form II incorporated into therapeutic formulations, the drug solubility was increased at a temperature of 299 +/- 2 K by factors of 1.2, 3.3, and 4.5 in lamivudine hydrochloride, lamivudine hydrochloride monohydrate, and lamivudine duplex, respectively, demonstrating that this solid-state property of lamivudine can be improved by crystal engineering strategies. Solubility profiles were understood on the basis of structural and solventsolute interaction approaches. At last, correlations between solubility and crystal structures allowed for a rational approach to understand how this physicochemical feature could be enhanced by engineering new salts of the drug. (C) 2012 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 101:21432154, 2012

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Blood-brain barrier (BBB) permeation is an essential property for drugs that act in the central nervous system (CNS) for the treatment of human diseases, such as epilepsy, depression, Alzheimer's disease, Parkinson disease, schizophrenia, among others. In the present work, quantitative structure-property relationship (QSPR) studies were conducted for the development and validation of in silico models for the prediction of BBB permeation. The data set used has substantial chemical diversity and a relatively wide distribution of property values. The generated QSPR models showed good statistical parameters and were successfully employed for the prediction of a test set containing 48 compounds. The predictive models presented herein are useful in the identification, selection and design of new drug candidates having improved pharmacokinetic properties.

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Gegenstand dieser Arbeit war die Untersuchung von metallischen gemischtvalenten Manganaten und magnetischen Doppelperowskiten. Aufgrund ihres großen negativen Magnetowiderstandes (MW) sind diese halbmetallischen Oxide interessant für mögliche technische Anwendungen, z.B. als Leseköpfe in Festplatten. Es wurden die kristallographischen, elektronischen und magnetischen Eigenschaften von epitaktischen Dünnschichten und polykristallinen Pulverproben bestimmt.Epitaktische Dünnschichten der Verbindungen La0.67Ca0.33MnO3 und La0.67Sr0.33MnO3 wurdenmit Kaltkathodenzerstäubung und Laserablation auf einkristallinen Substraten wie SrTiO3abgeschieden. Mit Hall-Effekt Messungen wurde ein Zusammenbruch der Ladungsträgerdichte bei der Curie-Temperatur TC beobachtet.Mit dem Wechsel des Dotierungsatoms A von Ca (TC=232 K) zu Sr (TC=345 K)in La0.67A0.33MnO3 konnte die Feldsensitivität des Widerstandes bei Raumtemperatur gesteigert werden. Um die Sensitivität weiter zu erhöhen wurde die hohe Spinpolarisation von nahezu 100% in Tunnelexperimenten ausgenutzt. Dazu wurden biepitaktische La0.67Ca0.33MnO3 Schichten auf SrTiO3 Bikristallsubstraten hergestellt. Die Abhängigkeit des Tunnelmagnetowiderstandes (TMW) vom magnetischen Feld, Temperatur und Strum war ein Schwerpunkt der Untersuchung. Mittels spinpolarisierten Tunnelns durch die künstliche Korngrenze konnte ein hysteretischer TMW von 70% bei 4 K in kleinen Magnetfeldern von 120 Oe gemessen werden. Eine weitere magnetische Oxidverbindung, der Doppelperowskit Sr2FeMoO6 miteine Curie-Temperatur oberhalb 400 K und einem großen MW wurde mittels Laserablation hergestellt. Die Proben zeigten erstmals das Sättigunsmoment, welches von einer idealen ferrimagnetischen Anordnung der Fe und Mo Ionen erwartet wird. Mit Hilfe von Magnetotransportmessungen und Röntgendiffraktometrie konnte eine Abhängigkeit zwischen Kristallstruktur (Ordnung oder Unordnung im Fe, Mo Untergitter) und elektronischem Transport (metallisch oder halbleitend) aufgedeckt werden.Eine zweiter Doppelperowskit Ca2FeReO6 wurde im Detail als Pulverprobe untersucht. Diese Verbindung besitzt die höchste Curie-Temperatur von 540 K, die bis jetzt in magnetischen Perowskiten gefunden wurde. Mit Neutronenstreuung wurde eine verzerrte monoklinische Struktur und eine Phasenseparation aufgedeckt.

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In this work the synthesis of polyarylated cycloparaphenylenes (CPPs) is described in order to form structurally defined carbon nanotube (CNT) segments by the Scholl reaction. Therefore, polyphenylene macrocycles in different sizes and substitution patterns were synthesized. The influence of the ring-strain on the oxidative cyclodehydrogenation of these macrocycles towards CNT segments was investigated. It was demonstrated that a selective solution based bottom-up synthesis of CNT segments could be accomplished, having polyarylated CPPs, sufficient in size and with the right substituents at the critical positions. These findings mark an important step towards the bottom-up synthesis of length- and diameter defined ultrashort CNTsrnIn the second part of this work, novel non-precious metal catalysts (NPMCs) based on phenanthroline-indole macrocycles were synthesized and their electrocatalytic performance in the cathodic oxygen reduction was investigated. It could be demonstrated that all catalysts contributed to the direct 4-electron reduction of oxygen to water in alkaline media and a superior long-term stability was observed. Since these NPMCs are not heat pre-treated, the catalytically active site was structurally well-defined, allowing the investigation of the structure-property relationship. Moreover, it could be shown that these novel NPMCs act as efficient ORR catalysts and could replace the expensive and scarce platinum in fuel cell applications.rn

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This study identifies and investigates the potential use of in-eye trigger mechanisms to supplement the widely available information on release of ophthalmic drugs from contact lenses under passive release conditions. Ophthalmic dyes and surrogates have been successfully employed to investigate how these factors can be drawn together to make a successful system. The storage of a drug-containing lens in a pH lower than that of the ocular environment can be used to establish an equilibrium that favours retention of the drug in the lens prior to ocular insertion. Although release under passive conditions does not result in complete dye elution, the use of mechanical agitation techniques which mimic the eyelid blink action in conjunction with ocular tear chemistry promotes further release. In this way differentiation between passive and triggered in vitro release characteristics can be established. Investigation of the role of individual tear proteins revealed significant differences in their ability to alter the equilibrium between matrix-held and eluate-held dye or drug. These individual experiments were then investigated in vivo using ophthalmic dyes. Complete elution was found to be achievable in-eye; this demonstrated the importance of that fraction of the drug retained under passive conditions and the triggering effect of in-eye conditions on the release process. Understanding both the structure-property relationship between drug and material and in-eye trigger mechanisms, using ophthalmic dyes as a surrogate, provides the basis of knowledge necessary to design ocular drug delivery vehicles for in-eye release in a controllable manner.

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Sol-gel-synthesized bioactive glasses may be formed via a hydrolysis condensation reaction, silica being introduced in the form of tetraethyl orthosilicate (TEOS), and calcium is typically added in the form of calcium nitrate. The synthesis reaction proceeds in an aqueous environment; the resultant gel is dried, before stabilization by heat treatment. These materials, being amorphous, are complex at the level of their atomic-scale structure, but their bulk properties may only be properly understood on the basis of that structural insight. Thus, a full understanding of their structure-property relationship may only be achieved through the application of a coherent suite of leading-edge experimental probes, coupled with the cogent use of advanced computer simulation methods. Using as an exemplar a calcia-silica sol-gel glass of the kind developed by Larry Hench, in the memory of whom this paper is dedicated, we illustrate the successful use of high-energy X-ray and neutron scattering (diffraction) methods, magic-angle spinning solid-state NMR, and molecular dynamics simulation as components to a powerful methodology for the study of amorphous materials.

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Ce mémoire porte sur les recherches et les développements dans le domaine des électrolytes à base de liquide ionique redox. Une nouvelle famille de liquide ionique redox basée sur le ferrocenylsulfonyl(trifluoromethylsulfonyl) (FcNTf) a été développée et étudiée pour la première fois afin de démontrer le potentiel de ces liquides ioniques dans les dispositifs de stockage d’énergie. En premier lieu, les liquides ioniques redox (RILs) composés de l’anion électroactif et du cation d’alkylimidazolium sont synthétisés et caractérisés. L’impact de la variation des chaînes alkyles du cation sur les propriétés physicochimiques et électrochimiques du RIL a été étudié. À une faible concentration en solution, l’impact du cation a peu d’influence sur l’ensemble des propriétés. Cependant, à haute concentration (>50 % massique) et sans électrolyte de support, la formation de films en oxydation a été observée à l'électrode positive. Ce point est intéressant pour les futures recherches et développements dans le domaine, puisque la variation des chaînes alkyles du cation des liquides ioniques redox et la formation de films lors de l’oxydation du FcNTf est peu connue et comprise en littérature. De plus, l’optimisation des conditions de solution d'électrolyte RIL dans les supercapaciteurs est aussi présentée. En deuxième lieu, la mise en application des RILs dans les supercapaciteurs a été testée. La performance énergétique et le mécanisme d’autodécharge ont été ciblés dans cette étude. En présence de l’électrolyte redox, la contribution des réactions faradaiques permet d'accomplir un gain énergique de 287 % versus les systèmes purement capacitifs. À cause de la formation de film à l’électrode, l’électrolyte redox FcNTf joue un rôle primordial dans la prévention de l’autodécharge versus les liquides ioniques qui étaient connus jusqu’à présent. Finalement, ce mémoire a permis de mieux comprendre les effets structure-propriétés relative aux modifications du cation chez les liquides ioniques redox.

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Ce mémoire porte sur les recherches et les développements dans le domaine des électrolytes à base de liquide ionique redox. Une nouvelle famille de liquide ionique redox basée sur le ferrocenylsulfonyl(trifluoromethylsulfonyl) (FcNTf) a été développée et étudiée pour la première fois afin de démontrer le potentiel de ces liquides ioniques dans les dispositifs de stockage d’énergie. En premier lieu, les liquides ioniques redox (RILs) composés de l’anion électroactif et du cation d’alkylimidazolium sont synthétisés et caractérisés. L’impact de la variation des chaînes alkyles du cation sur les propriétés physicochimiques et électrochimiques du RIL a été étudié. À une faible concentration en solution, l’impact du cation a peu d’influence sur l’ensemble des propriétés. Cependant, à haute concentration (>50 % massique) et sans électrolyte de support, la formation de films en oxydation a été observée à l'électrode positive. Ce point est intéressant pour les futures recherches et développements dans le domaine, puisque la variation des chaînes alkyles du cation des liquides ioniques redox et la formation de films lors de l’oxydation du FcNTf est peu connue et comprise en littérature. De plus, l’optimisation des conditions de solution d'électrolyte RIL dans les supercapaciteurs est aussi présentée. En deuxième lieu, la mise en application des RILs dans les supercapaciteurs a été testée. La performance énergétique et le mécanisme d’autodécharge ont été ciblés dans cette étude. En présence de l’électrolyte redox, la contribution des réactions faradaiques permet d'accomplir un gain énergique de 287 % versus les systèmes purement capacitifs. À cause de la formation de film à l’électrode, l’électrolyte redox FcNTf joue un rôle primordial dans la prévention de l’autodécharge versus les liquides ioniques qui étaient connus jusqu’à présent. Finalement, ce mémoire a permis de mieux comprendre les effets structure-propriétés relative aux modifications du cation chez les liquides ioniques redox.

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Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: (1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (E LUMO) via QSAR modelling and analysis; (2) to validate the models by using internal and external cross-validation techniques; (3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl ) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: (1) Linear or Multi-linear Regression (MLR); (2) Partial Least Squares (PLS); and (3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: (1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; (2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; (3) E LUMO are shown to correlate highly with the NCl for several classes of DBPs; and (4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

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Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: 1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (ELUMO) via QSAR modelling and analysis; 2) to validate the models by using internal and external cross-validation techniques; 3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: 1) Linear or Multi-linear Regression (MLR); 2) Partial Least Squares (PLS); and 3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: 1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; 2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; 3) ELUMO are shown to correlate highly with the NCl for several classes of DBPs; and 4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

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An examination of crystallographic data has indicated that the structure/activity relationship for diorganotin dihalide complexes is different from that of other metal dihalides, in that the SnN bond lengths appear to determine the antitumour activity.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)