Dissertationen zum Thema „Physicochemical Approach“

Les préoccupations grandissantes concernant la santé et l’environnement rendent la demande en ingrédients naturels toujours plus forte. Parallèlement, les fournisseurs d’ingrédients naturels tentent de rendre les procédés d’extraction plus performants, plus sûrs, moins consommateurs en énergie et en ressources non-renouvelables. Les hydrotropes, capables de solubiliser des composés hydrophobes dans l’eau, constituent une alternative prometteuse aux solvants organiques, souvent dérivés du pétrole, potentiellement explosifs et émetteurs de composés organiques volatiles. Afin de développer un nouveau procédé d’extraction hydrotropique efficace à base d’amphiphiles biosourcés, nous nous sommes intéressés à la compréhension des cinétiques et des phénomènes physico-chimiques impliqués dans l’extraction de l’acide carnosique (AC), un puissant antioxydant phénolique présent dans le romarin et la sauge officinale. L’extraction de l’AC par des hydrotropes modèles de type éthers de polyéthylène glycol a permis de démontrer l’efficacité et la compétitivité de l’extraction hydrotropique par rapport à une extraction conventionnelle utilisant un solvant. Des relations structure/propriétés physico-chimiques/efficacité ont été établies, puis généralisées aux hydrotropes biosourcés à base de glycérol (éthers de butyle, pentyle, et isopentyle) ou de sucres comme le xyloside d’amyle qui a été sélectionné par la suite pour son efficacité, sa biodégradabilité et sa disponibilité. L’optimisation des conditions d’extraction à l'aide de plans d'expériences a permis de doubler la quantité d’AC récupéré dans l’extrait sec. Pour finir, différentes techniques de précipitation de l’AC contenu dans des solutions hydrotropiques ont été comparées afin de faciliter sa récupération. Parmi elles, l’addition d’eau comme anti-solvant s’est révélée la plus efficace pour précipiter l’AC extrait du romarin. Sur la base de la composition et de l’aspect du précipité obtenu selon différentes conditions de précipitation, nous avons finalement pu établir un mécanisme visant à expliquer les différentes étapes de la précipitation hydrotropique
The growing concerns for health and environment makes the demand for natural ingredients ever higher. At the same time, natural ingredients manufacturers are trying to design effective, safer and less energy-costly extraction processes while avoiding the use of non-renewable resources. Hydrotropes are able to solubilize hydrophobic compounds in water, and constitute a promising alternative to organic solvents, which are often derived from petroleum, potentially explosives and producers of volatile organic compounds. To design a new effective hydrotropic extraction process using biobased amphiphiles, we investigated the physical chemical and kinetic phenomena governing the extraction of carnosic acid (CA), a powerful phenolic antioxidant that occurs in rosemary and sage. The CA extraction using alkyl polyethylene glycols ethers as model hydrotropes demonstrated the efficiency and the competitiveness of hydrotropic extractions compared to conventional solvent extractions. Quantitative Structure/properties relationship (QSPR) studies were established and generalized to biobased hydrotropes including butyl or pentyl glycerol ethers, and sugar-based hydrotropes such as amyl xyloside, which was further selected for its efficiency, biodegradability and commercial availability. The optimization of the extraction conditions led to double the CA recovered in the dry extract. Finally, different techniques have been investigated to precipitate CA from a hydrotropic solution. Among them, the addition of water as an anti-solvent appears as the more effective for precipitating CA from rosemary extract. Finally, the comparison of the precipitate composition and aspect obtained using various precipitation conditions led us to establish a mechanism explaining the different steps of the hydrotropic precipitation

The development of sensors assays for comprehensive characterisation of biological samples and effective minimal-invasive diagnostics is highly prioritised. Last decade this research area has been actively developing due to possibility of simultaneous, real- time, in vivo detection and monitoring of diverse physicochemical parameters and analytes. The new approach which has been introduced in this thesis was to develop and examine an optical diagnostic assay consisting of a mixture of environmental-sensitive fluorescent dyes. The operating principle of the system has been inspired by electronic nose and tongue devices which combine nonspecific (or semispecific) sensing elements and chemometric techniques for multivariate data analysis. The performance of the optical assay was based on the analysis of the spectrum of selected dyes with discreet reading of their emission maxima. The variations in peaks intensities caused by environmental changes provided distinctive fluorescence patterns, which could be handled similar to the signals collected from nose/tongue devices. The analytical capability of the assay was engendered by changes in fluorescence signal of the dye mixture in response to changes in pH, temperature, ionic strength and the presence of oxygen. Further findings have also proved the ability of optical assay to estimate development phases and to discriminate between different strains of growing cell cultures as well as identify various gastrointestinal diseases in human. This novel fluorescence-based diagnostic tool offers a promising alternative to electrochemical systems providing high sensitive measurements with broad dynamic range, easy, inexpensive measurements and the possibility of remote sensing and extreme assay miniaturisation. Additionally it does not require reference signal. This new approach can impact on a number of applications such as routine minimal- invasive diagnostics for medical samples, biomedical analysis, pharmaceutical or cosmetic research, quality control and process monitoring of food or environmental samples.

The availability of new technologies supplied life scientists with large amounts of experimental data. The data sets are large not only in terms of the number of observations, but also in terms of the number of recorded features. One of the aims of modeling is to explain a given phenomenon in possibly the simplest way, hence the need for selection of suitable features. We extended a Monte Carlo-based approach to selecting statistically significant features with discovery of feature interdependencies and used it in modeling sequence-function relationships in proteins. Our approach led to compact and easy-to-interpret predictive models. First, we represented protein sequences in terms of their physicochemical properties. This was followed by our feature selection and discovery of feature interdependencies. Finally, predictive models based on e.g., decision trees or rough sets were constructed. We applied the method to model two important biological problems: 1) HIV-1 resistance to reverse transcriptase-targeted drugs and 2) post-translational modifications of proteins. In the case of HIV resistance, we were not only able to predict whether the mutated protein is resistant to a drug or not, but we also suggested some new, previously neglected, mutations that possibly contribute to drug resistance. For all these mutations we proposed probable molecular mechanisms of action using literature and 3D structure studies. In the case of predicting PTMs, we built high accuracy models of modifications. In comparison to other methods, we were able to resolve whether the closest neighborhood of a residue (the nanomer) is sufficient to determine its modification status. Importantly, the application of our method yields networks of interdependent physicochemical properties of amino acids that show how these properties collaborate in establishing a given modification. We believe that the presented methods will help researchers to analyze a large class of important biological problems and will guide them in their research.

L'huile d'olive est une composante vitale du régime méditerranéen en raison de sa valeur nutritionnelle et économique bien connues. Plusieurs facteurs environnementaux, agricoles et technologiques jouent un rôle important dans la définition de la qualité de l'huile d'olive. Au Liban, des études préliminaires ont montré que certains critères de qualité dépassent les valeurs seuils des normes éditées par le Conseil Oléicole International (COI) pour les huiles d’olive extra-vierges, dont les causes n'ont pas été identifiées. En conséquence, quatre-vingt-seize échantillons d'huile d'olive ont été récoltés sur deux saisons, traités en utilisant différentes méthodes d'extraction et collectés sur huit sites (Akkar, Chouf, Hasbaya, Koura, Tyr, Nabatiyeh, Zgharta et Hermel) à fort potentiel pour l’obtention d’une indication géographique protégée (IGP). Dans cette optique, les huiles extraites et/ou collectées, ont été soumises à une analyse chimique conventionnelle comme suggéré par le COI et à une analyse rapide en utilisant la spectroscopie de fluorescence 3D en mode frontal (3D-FFFS) et la chromatographie en phase gazeuse ultra-rapide (Ultra-Fast GC).Une corrélation entre le profil en acides gras et les conditions pédoclimatiques des principales régions oléicoles du Liban a été constatée. L'altitude, la température et l'humidité relative sont les principaux facteurs d’influence du profil d'acides gras. Les régions libanaises à haute altitude, à température moyenne basse et à faible humidité relative ont une teneur élevée en acide oléique. Les zones à basse altitude, à température moyenne plus élevée et avec une humidité relative plus élevée ont un profil en acides gras caractérisé par les acides linoléique, linolénique, palmitoléique et palmitique. Les facteurs agricoles, en particulier la date de récolte, affectent également les constituants majeurs et mineurs de l'huile d'olive. En effet, l'acidité et les polyphénols totaux étaient fortement influencés par celle-ci. De plus, une modification du profil d'acides gras caractérisée par une teneur en linoléique plus élevée, une teneur en oléique plus faible, une augmentation du ∆7-stigmasténol dépassant la limite fixée par le CIO et la présence de composés malodorants (dont l’éthanol) ont été observés lors de récoltes plus tardives. En outre, deux facteurs technologiques, notamment un stockage inadéquat des fruits et de mauvaises pratiques hygiéniques de fabrication, ont favorisé la lipolyse enzymatique du triacylglycérol du fruit modifiant de manière significative les profils d'arômes et d’acides gras de l'huile d'olive.La 3D-FFFS et l'Ultra-FGC ont toutes deux montré de très bonnes performances. La 3D-FFFS couplée à des techniques chimiométriques a été appliquée sur des qualités hétérogènes et dégradées d'échantillons d'huile d'olive libanaise afin de prédire les principaux paramètres physicochimiques de qualité. Ainsi, vingt-deux modèles de régression MLR basés sur les scores PARAFAC ont été générés, dont la majorité a montré un bon coefficient de corrélation (R>0,7). Un deuxième modèle, utilisant la PLS sur les matrices d'émission-excitation (EEM) dépliées, a conduit à des résultats similaires, avec une légère amélioration par rapport au modèle MLR. D’autre part, l’Ultra Flash GC a permis d’identifier en quelques minutes seulement (< 2 min) l'éthanol, le (E,E)-2,4-décadiénal (défaut organoleptique) et le 1-hexanol (fruité, herbeux) comme principaux volatils caractérisant la variété Soury.Cette étude offre la possibilité d’établir au Liban un plan de contrôle analytique qui lie les aspects environnementaux et les techniques de culture/récolte aux caractéristiques physico-chimiques de l'huile d'olive qui en résultent. Une telle matrice monitorée à l’aide de techniques d'analyse rapide facilitera la vérification de la conformité du produit final aux normes internationales. En outre, ce travail préparera le terrain grâce à une fiche d'identification détaillée pour l'IGP
Olive oil is a vital component of the Mediterranean diet, hence Lebanese, owed to its well-known economic and nutritional value. Several environmental, agricultural, and technological factors play an essential role in defining olive oil's quality. In Lebanon, preliminary studies on the quality of extra virgin olive oil have shown that certain quality criteria exceed the International Olive Council's (IOC) standards. However, the causes of such non-conformities have not been clearly identified. Accordingly, ninety-six olive oil samples have been harvested from two seasons, processed using different extraction methods, and collected from eight locations (Akkar, Chouf, Hasbaya, Koura, Tyr, Nabatiyeh, Zgharta, and Hermel). These locations are identified by the European Union to have potentials for Protected Geographical Indications (PGI). In this perspective, and to meet the European framework's requirements, the analyzed oil will be subjected to conventional chemical analysis as suggested by the IOC and to ultra-fast analysis using 3D-front face spectroscopy (3D-FFFS) and ultra-flash gas chromatography (Ultra-FGC).A correlation between the fatty acid profile and the pedoclimatic conditions of the main olive growing regions in Lebanon was noticed. Three main pedoclimatic conditions, altitude, temperature, and relative humidity, were the major influencers and the reason for the distinctive fatty acid profile of the Lebanese olive oil. Lebanese areas with high altitudes, low average temperature, and low relative humidity have high oleic acid content. As for areas with lower altitudes, higher average temperature, and higher relative humidity, the fatty acid profile was characterized by linoleic, linolenic, palmitoleic, and palmitic acids. In addition to the environmental factors, agricultural ones, particularly the harvest date, had affected the chemical constituents of olive oil. The results obtained showed that the harvest date strongly influenced acidity and total polyphenols. A change in the fatty acid profile characterized by a higher linoleic and lower oleic content, an increase in ∆^7-stigmastenol exceeding the limit set by the IOC standards, and a dominating off-flavor compound (ethanol) was noticed as a result of delaying the harvesting time. Besides, two technological factors, particularly improper fruit storage, and bad hygienic practices, significantly affected olive oil’s quality parameters and fatty acid content.3D-FFFS and Ultra-FGC were used in-line with conventional analysis, and they both showed an undeniable performance. 3D-FFFS coupled with chemometric tools, namely multiple linear regression (MLR) applied on parallel factor (PARAFAC) scores and partial least squares (PLS), was tested on inconsistent qualities of olive oil samples to predict quality parameters. Twenty-two MLR models were generated, the majority of which showed a good correlation coefficient (R>0.7). A second model using PLS on the unfolded emission-excitation matrices was also conducted to improve the regression and assess whether the variability can be handled successfully. However, similar results, with a slight improvement over the MLR model, were obtained. As for Ultra Flash GC, it made it possible to identify, in only a few minutes (< 2 min), ethanol, (E,E)-2,4-decadienal (organoleptic defect), and 1-hexanol (fruity, grassy) as the main volatiles characterizing the Soury variety.This study offers the potential to disseminate an analytical control plan that links environmental aspects in Lebanon and cultivation/harvesting techniques to olive oil's resulting physicochemical characteristics. Such a matrix incorporating rapid analysis techniques will facilitate governance over the end product's final quality and, subsequently, conformity to IOC standards. Furthermore, this work will set the ground through a detailed identification fiche for PGI

In many countries water quality is assessed by using indices derived from the presence of macroinvertebrate species. This study aimed to improve the application of one such index (Hindu-Kush Himalaya based index: HKHbios) to rivers and streams in Bhutan. Sampling in a number of different streams showed that there was a strong influence of the monsoon on stream macroinvertebrates, however the month to month and site to site HKHbios scores showed no consistent patterns. Dry season sampling and increased ecological information on a number of macroinvertebrate taxa were identified as areas where water quality assessment in Bhutanese streams could be improved.

The amorphous state is becoming increasingly important in the pharmaceutical setting. Formulation of poorly water soluble drugs in the amorphous form enhances physicochemical properties of the drug, such as solubility and dissolution rate, which in turn may lead to an increased bioavailability. However, despite these advantages, many properties of the amorphous state are not yet understood and amorphous materials pose a challenge for structural analysis since they lack three dimensional long range order. Hence, compared to crystalline materials often little structural information can be gained using standard characterisation techniques. In this thesis, a range of analytical techniques and data analysis tools were used to characterise as well as quantify amorphous drugs and compare them to their crystalline counterparts. Apart from established characterisation techniques such as X-ray powder diffraction, microscopy, and differential scanning calorimetry, molecular-level characterisation was carried out using vibrational spectroscopies including infrared, near infrared, and Raman spectroscopy combined with multivariate analysis methods. To obtain deeper understanding of the structure of amorphous drugs and their corresponding crystalline forms novel approaches such as pair distribution function analysis of X-ray diffraction data and computational chemistry were employed. Three model drugs namely indomethacin, saquinavir, and fenofibrate were investigated in the scope of this thesis. For indomethacin differences between amorphous forms of indomethacin prepared by ball milling, spray drying, as well as melting and subsequent cooling were analysed using infrared, near infrared, and Raman spectroscopy in combination with principal component analysis. While all spectroscopic techniques were able to differentiate between the differently prepared samples, Raman spectroscopy proved to be most sensitive to small differences in the solid state of different samples. Consistent with the study of indomethacin, Raman spectroscopy combined with principal component analysis was the most sensitive analytical technique to detect structural changes induced by milling or heating saquinavir. In addition, pair distribution function transforms of the X-ray powder diffraction data significantly contributed to the understanding of differences in short-range and long-range order between differently treated saquinavir samples. A combination of vibrational spectroscopy, quantum mechanical calculations, and multivariate analysis proved suitable for physicochemical analysis of amorphous fenofibrate. The results of the study support the idea that non hydrogen bonded molecules such as fenofibrate are likely to exhibit random molecular orientations and conformations in the amorphous phase since the weak intermolecular interactions that occur between such molecules can easily be disrupted. A study of ternary mixtures of crystalline and amorphous forms of indomethacin showed that Raman and near-infrared spectroscopy in conjunction with PLS regression are well suited for quantification of the different solid-state forms simultaneously. It was found that near-infrared spectroscopy can be used to more accurately quantify the mixtures compared to Raman spectroscopy when fluorescing components, such as amorphous indomethacin, are present. Nevertheless quantification with Raman spectroscopy was still possible. Overall, the analytical methods used in this thesis were successfully employed for qualitative and quantitative analysis of amorphous drugs and their crystalline counterparts. It could be shown that it is beneficial to use a combination of different analytical techniques and data analysis tools since results are complementary and allow a more comprehensive description of the solid state.

La valorisation de la biomasse et du dioxyde de carbone est à présent considérée comme une solution aux problèmes environnementaux du réchauffement climatique et l'épuisement des réserves de pétrole. Ainsi, les huiles végétales ont attiré l'attention croissante des milieux universitaires et industriels, comme une source de biomasse potentielle renouvelable qui peut être appliquée à la production de substitut fossile pour un développement durable, due à leurs caractères renouvelables, durables, biodégradables. De plus, cette biomasse est disponible avec une énorme quantité. Durant des décennies de recherches, les processus d'époxydation et de carbonatation sont deux méthodes d'application populaires pour la valorisation des huiles végétales. La conversion des huiles végétales en huiles époxydées est définie par une conversion d'un composé insaturé en un groupe époxyde. Jusqu'ici, l'oxydation de Prileschajew est la méthode de synthèse plus efficace pour la possible industrialisation du processus d'époxydation de huiles végétales, qui est une manière conventionnelle bien connue à utiliser comme processus de production commerciale. Ce type d'époxydation utilise l'acide percarboxylique comme transporteur d'oxygène qui est formé in situ dans la phase aqueuse, et ensuite époxyde les groupes insaturés des huiles végétales en groupes époxyde. Cependant, cette méthode présente une réaction secondaire d'ouverture du cycle du groupe époxyde au cours du processus. Donc, les conditions du procédé d'époxydation doivent être optimisées afin de minimiser les réactions d'ouverture de cycle. Des paramètres de réaction, y compris la concentration en catalyseur acide (acide sulfurique), réactifs (eau, groupe époxyde, peroxyde d'hydrogène, acide acétique) et la température de réaction, ont été discutés dans cette étude pour l'époxydation et réaction d'ouverture de cycle des huiles végétales. Au cours de la modélisation cinétique, les constantes cinétiques associées pour les réactions d'ouverture du cycle ont été estimées. En se basant sur ce modèle, les réactions d'ouverture du cycle époxyde par les acides acétique et peracétique sont plus rapides que celles de l'eau et du peroxyde d'hydrogène. Un réacteur en mode semi-fermé, avec addition du peroxyde d'hydrogène et de l'acide sulfurique, est la configuration la plus appropriée pour la production d'huiles végétales époxydées. Pour déterminer les conditions optimales et passer à échelle industrielle dans les procédés d'époxydation et de la carbonation, il faut connaître différentes propriétés physicochimiques telles que la viscosité, la densité, l'indice de réfraction, la capacité thermique spécifique et les évolutions de ces données avec la température. Cependant, aucune information sur ces propriétés est disponible dans la littérature. Pour cette étude, l'évolution de ces propriétés ont été déterminées pour trois huiles végétales et leurs dérivés époxydées et carbonates (l'huile de coton, l'huile de lin et l'huile de soja) avec la température et leur composition. La densité et l'indice de réfraction ont été trouvé linéairement dépendant de la température pour les huiles étudiées. La relation entre la contrainte de cisaillement et le taux de cisaillement dans l’étude de viscosité, indique que ces huiles sont des fluides newtoniens. Il a été démontré que la capacité thermique spécifique suit une équation polynomiale du second ordre avec la température. Sur la base de ces résultats, il a été démontré que certaines corrélations pourraient être utilisées pour prédire les évolutions de ces propriétés physicochimiques à différentes compositions et températures
Nowadays, biomass and carbon dioxide valorization are considered as a helpful solution to the environmental issues of global warming and the depletion of petroleum reserves. Thus, vegetable oils have attracted increasing attention of academic and industrial communities, as one of the potential renewable biomass that can be applied to the production of fossil substitute for sustainable development, owning to their advantages of renewable, sustainable, biodegradable, and universally available with huge feedstock. Among decades of researches, epoxidation and carbonation processes are two popular application methods for vegetable oil valorization. The conversion of vegetable oils into epoxidized ones is defined by a conversion of unsaturated compound into an epoxide group. So far, the potential application for the production of epoxidized oil in the industrial is the Prileschajew oxidation, which is a wellknown conventional way to be used as the commercial production process. This type of epoxidation uses percarboxylic acid as an oxygen carrier, which is formed in situ in the aqueous phase, and then epoxidize the unsaturated groups on the vegetable oils into epoxide groups. During the process, however, this method presents side reaction of ring-opening of the epoxide group. Therefore, the selective epoxidation process conditions need to be optimized in order to minimize the ring-opening reactions. In this study, process parameters including the concentration of acid catalyst (sulfuric acid), reactants (water, epoxide group, hydrogen peroxide, acetic acid) and the reaction temperature have been discussed for the epoxidation and ring opening of vegetable oils. During the kinetic modeling stage, the related kinetic constants for the ring opening reactions were estimated. Based on this model, the ring opening by acetic and peracetic acids was found to be faster than by water and hydrogen peroxide. A semibatch reactor, where hydrogen peroxide and sulfuric acid were added, was found to be the most suitable configuration. To determine the optimum operating conditions and scale up the epoxidation or carbonation processes, it requires the database of different physicochemical properties, i.e. viscosity, density, refractive index, or specific heat capacity and the evolutions of these properties with the temperature. However, this information is absent in the literature. For this study, the evolution of these properties with temperature and compositions (double bond, epoxide and carbonated groups concentration) was determined for three vegetable oils and their corresponding epoxidized and carbonated forms (cottonseed oil, linseed oil and soybean oil). Density and refractive indices of these oils were found to vary linearly with temperature. Based on the measurement of changes in viscous stresses with shear rates, these oils were found to be Newtonian fluids. It was demonstrated that specific heat capacity follows a polynomial equation of second order with temperature. Based on these results, it was demonstrated that some correlations could be used to predict the evolutions of these physicochemical properties at different composition and temperature based on the knowledge of the property of the pure compounds

Une approche de la médecine régénérative du système nerveux consiste à développer des substituts biologiques avec une fonction réparatrice en utilisant des cellules souches et des biomatériaux qui peuvent être recouverts des molécules de la matrice extracellulaire. Nous avons ainsi développé des microcarriers pharmacologiquements actifs, MPA. Ce sont des microsphères (MS) polymériques à base de PLGA, biodégradables et biocompatibles, recouvertes des molécules d’adhérence qui fournissent un support en 3-dimensions aux cellules. Les microcarriers ainsi associés aux cellules souches permettent, après implantation, d’augmenter la survie et de maintenir l’état de différenciation des cellules qu’ils portent,renforçant leurs effets de réparation tissulaire. Ces MPA peuvent également libérer des facteurs de croissance encapsulés et afin d’améliorer le relargage de protéines encapsulées une nouvelle combinaison de polymère : PLGA-Poloxamer188 (P188) -PLGA a été développé dans notre laboratoire. Il a aussi été montré que les MPA de PLGA-P188-PLGA fonctionnalisées avec de la fibronectine et poly-D-lysine induisaient une meilleure prolifération de cellules souches mésenchymateuses que les MPA de PLGA.Ces cellules sont très largement utilisées en médecine régénérative car elles sont faciles à prélever, se trouvant dans la moelle osseuse, et capables de se différencier vers le lignage chondrogénique, ostéogénique et dans certaines conditions, neuronale. Nous travaillons avec une sous population de ces cellules appelées cellules MIAMI (marrow isolated adult multilineage inducible) qui s’engagent vers une différenciation en cellule neuronale après un traitement avec 2 facteurs de croissance (EGF/ bFGF) et sur un support matriciel de laminine. Dernièrement, il a été mis en évidence que les propriétés physicochimiques des supports polymériques régissent également le comportement des cellules souches(adhésion, survie et différenciation). L’objectif de cette étude est d’étudier l’effet des propriétés physicochimiques et mécaniques des surfaces i) des MS sur l’adsorption de laminine et poly-D-lysine et ii) des MPA sur l’adhérence et la différenciation neuronale des cellules MIAMI. Nous avons montré que la présence du bloc hydrophile « poloxamère 188 » dans la composition du polymère PLGA-P188-PLGAdiminue l’adsorption de molécules d’adhérence en formant une couche sur ces surfaces. Sur les MPA de PLGA, les molécules d’adhérence s’adsorbent bien quelle que soit la charge globale des molécules. Cesdeux MPA ont une charge globale positive et permettent l’attachement de cellules à leur surface. Cependant, l’adhérence à court terme de cellules est plus forte sur les MPA de PLGA comparé aux MPA de PLGA-P188-PLGA mais à la longue les cellules finissent par adhérer aux deux supports. Le PLGAP188-PLGA présente une forte énergie libre de surface et ces MPA présentent une surface moins rigide que les MPA de PLGA. Nos résultats suggèrent que ces caractéristiques de surface permettent aux cellules d’adhérer malgré la faible quantité de laminine sur ces supports. A long terme les cellules présentent le même comportement quel que soit le type du support. Elles se différencient en cellule de type neuronal exprimant des marqueurs de neurone mature comme le neurofilament et nous trouvons le même nombre de cellules adhérées à leur surface. En outre, nous avons montré que les cellules sont capables de sécréter de la même manière des molécules de la matrice extracellulaire sur les deux types de MPA expliquant probablement la similitude de comportement à long terme
An approach to regenerative nervous system medicine is to develop biological substitutes with restorative function using stem cells and biomaterials that can be coated with extracellular matrix molecules. We have developed pharmacologically active microcarriers, PAMs. These are PLGA based, biodegradable and biocompatible polymeric microspheres (MS) coated with adhesion molecules that provide 3-dimensional support for cells. The microcarriers thus associated with the stem cells make it possible, after implantation, to increase the survival and maintain the state of differentiation of the cells they carry, reinforcing their tissue repair effects. These PAMs can also release encapsulated growth factors and to enhance the release of encapsulated proteins a new polymer combination: PLGA-Poloxamer188 (P188) -PLGA has been developed in our laboratory. It has also been shown that PLGA-P188-PLGA PAMs functionalized with fibronectin and poly-Dlysineinduce better proliferation of mesenchymal stem cells than PLGA PAMs. These cells are very widely used in regenerative medicine because they are easy to collect, found in the bone marrow, and able to differentiate towards the chondrogenic lineage, osteogenic and under certain conditions,neuronal. We are working with a subpopulation of these cells called MIAMI cells (marrow isolated adult multilineage inducible) that engage in neuronal cell differentiation after treatment with 2growth factors (EGF / bFGF) and on a laminin matrix support. Recently, it has been demonstrated that the physicochemical properties of polymeric supports also regulate the behavior of stem cells (adhesion, survival and differentiation). The objective of this study is to study the effect of physicochemical and mechanical properties of surfaces i) MS on laminin and poly-D-lysineadsorption and ii) PAMs on adhesion and neuronal differentiation of MIAMI cells. We have shown that the presence of the hydrophilic "poloxamer 188" block in the PLGA-P188-PLGA polymer composition decreases the adsorption of adhesion molecules by forming a layer on these surfaces.On PLGA PAMs, the adhesion molecules adsorb well regardless of the overall charge of the molecules. These two PAMs have a positive overall charge and allow the attachment of cells to their surface. However, in short-term cell adhesion is stronger on PLGA PAMs compared to PLGA-P188-PLGA PAMs, but in the long-term the cells eventually adhere to both supports. PLGA-P188-PLGAhas a high free surface energy and these PAMs have a less rigid surface than PLGA PAMs. Our results suggest that these surface characteristics allow cells to adhere despite the low amount of laminin on these supports. In the long-term the cells exhibit the same behavior whatever the type of PAMs. They differentiate into neuronal cells expressing mature neuron markers such as the neurofilament-M and we find the same number of cells adhered to their surface. Furthermore, we have shown that cells are able to secrete extracellular matrix molecules in the same way on both types of PAMs, probably explaining the similarity of the behavior in long-term

Research Doctorate - Doctor of Philosophy (PhD)
In the drug discovery process, approximately five to ten thousand compounds are initially screened but only 1% of these enter the preclinical testing stage that determines whether the compound is safe, efficacious, and feasible to use for a disease state. Owing to regulatory, toxicity, resistance and human health concerns, demand is increasing for refinement of and intensive use of molecular physicochemical properties via effective and robust mathematical methods for drug discovery. Chemoinformatics is now a well-recognised discipline focused on searching, identifying and extracting meaningful information from chemical sequences and structures of compounds. A candidate drug is usually a small molecule (~50 atoms) that acts by many different mechanisms of protein. Every year, several drugs are discarded from the market owing to poor pharmacodynamic and pharmacokinetic properties, which motivates this study that attempts to clarify the factors that facilitate compounds to be drug-like. The druglikeness of a molecule is characterised in part by its satisfying Lipinski’s rule-of-five (Ro5) regarding its molecular properties, such as mass and hydrophobicity, which play an important role in oral absorption, distribution, metabolism and excretion. A debate has existed for some time and now accelerated in the industry as to what constitutes a good ‘hit’. Increasing evidence suggests that relying completely on Lipinski’s Ro5 for potential drug synthesis may increase the likelihood of future drug failures. Retrospective analysis of failed drug discovery projects and incorporation of beyond Ro5 rules may provide useful information in innovating drugs for difficult targets. There is an urgent need to develop reliable computational methods for predicting drug-likeness of candidate molecules to identify those unlikely to survive the later stages of discovery and development. Visualisation and machine learning methods are two common approaches to uncover underlying patterns in the pharmacological property space, so called chemo-space, for drug design. Thus far, drug-likeness has been studied from several viewpoints, and in this thesis, we use proposed druggability rules (Hudson et al. 2012, 2014, 2017) to determine cut points for each molecular predictor based on non-Bayesian mixture model-based clustering with discriminant analysis, MC/DA (MclustDA R package). we also used decision tree for choosing cut-off ranges of molecular descriptors. To date, Hudson et al.’s (2014, 2017) results have established an improved scoring function, beyond the cut points of the Ro5. In this thesis, mixture-based modeling (Bayesian and two non-Bayesian) tools are applied via different ‘R’ packages (Rmixmod, depmixS4 and mixAK), to identify good and poor drug candidates using a combination of 9 and 10 molecular physicochemical and structural properties and scoring functions of violations (Hudson et al. 2014, 2017). The non-Bayesian Gaussian mixture method (GMM) is shown to be optimal at classifying true good and poor molecules correctly in terms of Ro5, oral_Ro5 drug-like (Divide into two parts: oral_Ro5 drug-like status1 and oral_Ro5 drug-like status2), eRo5 (extended rule of 5) and bRo5 (beyond rule of five) drugs classification, as suggested recently by Lipinski (2014, 2016) and Doak et al. (2014, 2016). In the thesis, the GMM approach, and the optimal 10 descriptors (whether continuous and categorical) set model (based on the following molecular parameters- MW, logP, logD, Hydrogen bond donors and acceptors, polar surface area, number of atoms and rings, Halogen), shows good predictive performance, with Matthews correlation coefficient (C) values in the range of 0.41–0.58, compared with other descriptors set models using Bayesian (mixAK) and non-Bayesian (HMM) methods in terms of computational time and higher sensitivity, specificity and C values. The GMM classification identified 1013 drug-like molecules of which 4 % were in bRo5 space and 266 non drug-like molecules of which 38% were in bRo5 space, supporting recent trends to more outside the Ro5 region. These mixture models are formed the basis to identify molecules and disease targets in the chemo-space using visualisation methods such as Principal component analysis (PCA), Factor analysis for mixed data (FAMD) and Correspondence analysis (CA). These three visualisation and data reductive methods successfully identify a group of molecules and specific disease targets with a prescribed range of ADME properties in different quadrants in the chemo space. This work also demonstrates that PCA, MCA and FAMD methods could be a powerful technique for exploring complex datasets in drug discovery study to identify outliers. It is shown that both lipophilicity measurement descriptors logP and logD have a significant influence on the facilitation of compounds and DC’s segregations. Two non-Bayesian mixture clustering approaches, the Gaussian mixture method (GMM via Rmixmod) and the Hidden Markov model (HMM via depmixS4) as applied in this thesis permit capture of the global properties of molecules with related targets. Based on these mixture approaches, this study is identified disease targets using the score function and molecular physicochemical properties of drugs-towards target. All mixture clustering models are identified 9 poor/non-druggable and 26 good/druggable targets with the anti-bacterial and adrenergic targets identified as the topmost poor and good druggable target respectively. Furthermore, three popular machine learning (ML) methods, such as (1) recursive partitioning, (2) naïve Bayesian and (3) support vector machine technique was also used to discriminate drug-like and non grug-like molecules based on molecular descriptors. Among these ML techniques, the SVM model is superior in terms of different rule-based drugs classifications and achieved a sensitivity range of 94% to 99% and specificity range of 84% to 100%, likewise exhibiting higher C values 0.68 to 0.99. The three-mixture based clustering with classification analyses results which use both LogD and logP are offering an excellent opportunity to consider these lipophilicity measurement descriptors (logP and logD) in conjunction with other descriptors to help predict permeability and solubility of active compounds in drug discovery. This study has the potential to significantly reduce the false classification of drugs and suggest an appropriate predictor set to help identify for new drug innovations.

Thesis (Ph. D.)--Florida State University, 2004.
Advisor: Dr. Andrew Dzurik, Florida State University, College of Engineering, Dept. of Civil and Environmental Engineering. Title and description from dissertation home page (viewed July 12, 2004). Includes bibliographical references.