Multifunctional ligands for application in Alzheimer’s Disease: molecular modelling and biological evaluation

Projecte de recerca elaborat a partir d’una estada a la University of British Columbia, Canadà, entre 2010 i 2012 La malaltia d'Alzheimer (MA) representa avui la forma més comuna de demència en la població envellida. Malgrat fa 100 anys que va ser descoberta, encara avui no existeix cap tractament preventiu i/o curatiu ni cap agent de diagnòstic que permeti valorar quantitativament l'evolució d'aquesta malaltia. L'objectiu en el que s'emmarca aquest treball és contribuir a aportar solucions al problema de la manca d'agents terapèutics i de diagnosi, unívocs i rigorosos, per a la MA. Des del camp de la química bioinorgànica és fàcil fixar-se en l'excessiva concentració d'ions Zn(II) i Cu(II) en els cervells de malalts de MA, plantejar-se la seva utilització com a dianes terapèutica i, en conseqüència, cercar agents quelants que evitin la formació de plaques senils o contribueixin a la seva dissolució. Si bé aquest va ser el punt de partida d’aquest projecte, els múltiples factors implicats en la patogènesi de la MA fan que el clàssic paradigma d’ ¨una molècula, una diana¨ limiti la capacitat de la molècula de combatre aquesta malaltia tan complexa. Per tant, un esforç considerable s’ha dedicat al disseny d’agentsmultifuncionals que combatin els múltiples factors que caracteritzen el desenvolupament de la MA. En el present treball s’han dissenyat agents multifuncionals inspirats en dos esquelets moleculars ben establers i coneguts en el camp de la química medicinal: la tioflavina-T (ThT) i la deferiprona (DFP). La utilització de tècniques in silico que inclouen càlculs farmacocinètics i modelatge molecular ha estat un procés cabdal per a l’avaluació dels millors candidats en base als següents requeriments: (a) compliment de determinades propietats farmacocinètiques que estableixin el seu possible ús com a fàrmac (b) hidrofobicitat adequada per travessar la BBB i (c) interacció amb el pèptid Aen solució.

Combining palaeodistribution modelling and phylogeographical approaches for identifying glacial refugia in Alpine Primula

Aim We investigated the late Quaternary history of two closely related and partly sympatric species of Primula from the south-western European Alps, P. latifolia Lapeyr. and P. marginata Curtis, by combining phylogeographical and palaeodistribution modelling approaches. In particular, we were interested in whether the two approaches were congruent and identified the same glacial refugia. Location South-western European Alps. Methods For the phylogeographical analysis we included 353 individuals from 28 populations of P. marginata and 172 individuals from 15 populations of P. latifolia and used amplified fragment length polymorphisms (AFLPs). For palaeodistribution modelling, species distribution models (SDMs) were based on extant species occurrences and then projected to climate models (CCSM, MIROC) of the Last Glacial Maximum (LGM), approximately 21 ka. Results The locations of the modelled LGM refugia were confirmed by various indices of genetic variation. The refugia of the two species were largely geographically isolated, overlapping only 6% to 11% of the species' total LGM distribution. This overlap decreased when the position of the glacial ice sheet and the differential elevational and edaphic distributions of the two species were considered. Main conclusions The combination of phylogeography and palaeodistribution modelling proved useful in locating putative glacial refugia of two alpine species of Primula. The phylogeographical data allowed us to identify those parts of the modelled LGM refugial area that were likely source areas for recolonization. The use of SDMs predicted LGM refugial areas substantially larger and geographically more divergent than could have been predicted by phylogeographical data alone

Identification and modelling of human breast cancer subtypes

Résumé Le cancer du sein est le cancer le plus commun chez les femmes et est responsable de presque 30% de tous les nouveaux cas de cancer en Europe. On estime le nombre de décès liés au cancer du sein en Europe est à plus de 130.000 par an. Ces chiffres expliquent l'impact social considérable de cette maladie. Les objectifs de cette thèse étaient: (1) d'identifier les prédispositions et les mécanismes biologiques responsables de l'établissement des sous-types spécifiques de cancer du sein; (2) les valider dans un modèle ín vivo "humain-dans-souris"; et (3) de développer des traitements spécifiques à chaque sous-type de cancer du sein identifiés. Le premier objectif a été atteint par l'intermédiaire de l'analyse des données d'expression de gènes des tumeurs, produite dans notre laboratoire. Les données obtenues par puces à ADN ont été produites à partir de 49 biopsies des tumeurs du sein provenant des patientes participant dans l'essai clinique EORTC 10994/BIG00-01. Les données étaient très riches en information et m'ont permis de valider des données précédentes des autres études d'expression des gènes dans des tumeurs du sein. De plus, cette analyse m'a permis d'identifier un nouveau sous-type biologique de cancer du sein. Dans la première partie de la thèse, je décris I identification des tumeurs apocrines du sein par l'analyse des puces à ADN et les implications potentielles de cette découverte pour les applications cliniques. Le deuxième objectif a été atteint par l'établissement d'un modèle de cancer du sein humain, basé sur des cellules épithéliales mammaires humaines primaires (HMECs) dérivées de réductions mammaires. J'ai choisi d'adapter un système de culture des cellules en suspension basé sur des mammosphères précédemment décrit et pat décidé d'exprimer des gènes en utilisant des lentivirus. Dans la deuxième partie de ma thèse je décris l'établissement d'un système de culture cellulaire qui permet la transformation quantitative des HMECs. Par la suite, j'ai établi un modèle de xénogreffe dans les souris immunodéficientes NOD/SCID, qui permet de modéliser la maladie humaine chez la souris. Dans la troisième partie de ma thèse je décris et je discute les résultats que j'ai obtenus en établissant un modèle estrogène-dépendant de cancer du sein par transformation quantitative des HMECs avec des gènes définis, identifiés par analyse de données d'expression des gènes dans le cancer du sein. Les cellules transformées dans notre modèle étaient estrogène-dépendantes pour la croissance, diploïdes et génétiquement normales même après la culture cellulaire in vitro prolongée. Les cellules formaient des tumeurs dans notre modèle de xénogreffe et constituaient des métastases péritonéales disséminées et du foie. Afin d'atteindre le troisième objectif de ma thèse, j'ai défini et examiné des stratégies de traitement qui permettent réduire les tumeurs et les métastases. J'ai produit un modèle de cancer du sein génétiquement défini et positif pour le récepteur de l'estrogène qui permet de modéliser le cancer du sein estrogène-dépendant humain chez la souris. Ce modèle permet l'étude des mécanismes impliqués dans la formation des tumeurs et des métastases. Abstract Breast cancer is the most common cancer in women and accounts for nearly 30% of all new cancer cases in Europe. The number of deaths from breast cancer in Europe is estimated to be over 130,000 each year, implying the social impact of the disease. The goals of this thesis were first, to identify biological features and mechanisms --responsible for the establishment of specific breast cancer subtypes, second to validate them in a human-in-mouse in vivo model and third to develop specific treatments for identified breast cancer subtypes. The first objective was achieved via the analysis of tumour gene expression data produced in our lab. The microarray data were generated from 49 breast tumour biopsies that were collected from patients enrolled in the clinical trial EORTC 10994/BIG00-01. The data set was very rich in information and allowed me to validate data of previous breast cancer gene expression studies and to identify biological features of a novel breast cancer subtype. In the first part of the thesis I focus on the identification of molecular apacrine breast tumours by microarray analysis and the potential imptìcation of this finding for the clinics. The second objective was attained by the production of a human breast cancer model system based on primary human mammary epithelial cells {HMECs) derived from reduction mammoplasties. I have chosen to adopt a previously described suspension culture system based on mammospheres and expressed selected target genes using lentiviral expression constructs. In the second part of my thesis I mainly focus on the establishment of a cell culture system allowing for quantitative transformation of HMECs. I then established a xenograft model in immunodeficient NOD/SCID mice, allowing to model human disease in a mouse. In the third part of my thesis I describe and discuss the results that I obtained while establishing an oestrogen-dependent model of breast cancer by quantitative transformation of HMECs with defined genes identified after breast cancer gene expression data analysis. The transformed cells in our model are oestrogen-dependent for growth; remain diploid and genetically normal even after prolonged cell culture in vitro. The cells farm tumours and form disseminated peritoneal and liver metastases in our xenograft model. Along the lines of the third objective of my thesis I defined and tested treatment schemes allowing reducing tumours and metastases. I have generated a genetically defined model of oestrogen receptor alpha positive human breast cancer that allows to model human oestrogen-dependent breast cancer in a mouse and enables the study of mechanisms involved in tumorigenesis and metastasis.

Collage, a Collaborative Learning Design Editor Based on Patterns

This paper introduces Collage, a high-level IMS-LD compliant authoring tool that is specialized for CSCL (Computer-Supported Collaborative Learning). Nowadays CSCL is a key trend in elearning since it highlights the importance of social interactions as an essential element of learning. CSCL is an interdisciplinary domain, which demands participatory design techniques that allow teachers to get directly involved in design activities. Developing CSCL designs using LD is a difficult task for teachers since LD is a complex technical specification and modelling collaborative characteristics can be tricky. Collage helps teachers in the process of creating their own potentially effective collaborative Learning Designs by reusing and customizing patterns, according to the requirements of a particular learning situation. These patterns, called Collaborative Learning Flow Patterns (CLFPs), represent best practices that are repetitively used by practitioners when structuring the flow of (collaborative) learning activities. An example of an LD that can be created using Collage is illustrated in the paper. Preliminary evaluation results show that teachers, with experience in CL but without LD knowledge, can successfully design real collaborative learning experiences using Collage.

Toward integrated management of cerebral aneurysms

In the last few years, some of the visionary concepts behind the virtual physiological human began to be demonstrated on various clinical domains, showing great promise for improving healthcare management. In the current work, we provide an overview of image- and biomechanics-based techniques that, when put together, provide a patient-specific pipeline for the management of intracranial aneurysms. The derivation and subsequent integration of morphological, morphodynamic, haemodynamic and structural analyses allow us to extract patient-specific models and information from which diagnostic and prognostic descriptors can be obtained. Linking such new indices with relevant clinical events should bring new insights into the processes behind aneurysm genesis, growth and rupture. The development of techniques for modelling endovascular devices such as stents and coils allows the evaluation of alternative treatment scenarios before the intervention takes place and could also contribute to the understanding and improved design of more effective devices. A key element to facilitate the clinical take-up of all these developments is their comprehensive validation. Although a number of previously published results have shown the accuracy and robustness of individual components, further efforts should be directed to demonstrate the diagnostic and prognostic efficacy of these advanced tools through large-scale clinical trials.

Deployment of self-expandable stents in aneurysmatic cerebral vessels: comparison of different computational approaches for interventional planning

In the last few years, there has been a growing focus on faster computational methods to support clinicians in planning stenting procedures. This study investigates the possibility of introducing computational approximations in modelling stent deployment in aneurysmatic cerebral vessels to achieve simulations compatible with the constraints of real clinical workflows. The release of a self-expandable stent in a simplified aneurysmatic vessel was modelled in four different initial positions. Six progressively simplified modelling approaches (based on Finite Element method and Fast Virtual Stenting – FVS) have been used. Comparing accuracy of the results, the final configuration of the stent is more affected by neglecting mechanical properties of materials (FVS) than by adopting 1D instead of 3D stent models. Nevertheless, the differencesshowed are acceptable compared to those achieved by considering different stent initial positions. Regarding computationalcosts, simulations involving 1D stent features are the only ones feasible in clinical context.

Transcriptional activation of the macrophage migration-inhibitory factor gene by the corticotropin-releasing factor is mediated by the cyclic adenosine 3',5'- monophosphate responsive element-binding protein CREB in pituitary cells.

Macrophage migration-inhibitory factor (MIF) has recently been identified as a pituitary hormone that functions as a counterregulatory modulator of glucocorticoid action within the immune system. In the anterior pituitary gland, MIF is expressed in TSH- and ACTH-producing cells, and its secretion is induced by CRF. To investigate MIF function and regulation within pituitary cells, we initiated the characterization of the MIF 5'-regulatory region of the gene. The -1033 to +63 bp of the murine MIF promoter was cloned 5' to a luciferase reporter gene and transiently transfected into freshly isolated rat anterior pituitary cells. This construct drove high basal transcriptional activity that was further enhanced after stimulation with CRF or with an activator of adenylate cyclase. These transcriptional effects were associated with a concomitant rise in ACTH secretion in the transfected cells and by an increase in MIF gene expression as assessed by Northern blot analysis. A cAMP-responsive element (CRE) was identified within the MIF promoter region which, once mutated, abolished the cAMP responsiveness of the gene. Using this newly identified CRE, DNA-binding activity was detected by gel retardation assay in nuclear extracts prepared from isolated anterior pituitary cells and AtT-20 corticotrope tumor cells. Supershift experiments using antibodies against the CRE-binding protein CREB, together with competition assays and the use of recombinant CREB, allowed the detection of CREB-binding activity with the identified MIF CRE. These data demonstrate that CREB is the mediator of the CRF-induced MIF gene transcription in pituitary cells through an identified CRE in the proximal region of the MIF promoter.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling.

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.

Genome organization and gene expression shape the transposable element distribution in the Drosophila melanogaster euchromatin.

The distribution of transposable elements (TEs) in a genome reflects a balance between insertion rate and selection against new insertions. Understanding the distribution of TEs therefore provides insights into the forces shaping the organization of genomes. Past research has shown that TEs tend to accumulate in genomic regions with low gene density and low recombination rate. However, little is known about the factors modulating insertion rates across the genome and their evolutionary significance. One candidate factor is gene expression, which has been suggested to increase local insertion rate by rendering DNA more accessible. We test this hypothesis by comparing the TE density around germline- and soma-expressed genes in the euchromatin of Drosophila melanogaster. Because only insertions that occur in the germline are transmitted to the next generation, we predicted a higher density of TEs around germline-expressed genes than soma-expressed genes. We show that the rate of TE insertions is greater near germline- than soma-expressed genes. However, this effect is partly offset by stronger selection for genome compactness (against excess noncoding DNA) on germline-expressed genes. We also demonstrate that the local genome organization in clusters of coexpressed genes plays a fundamental role in the genomic distribution of TEs. Our analysis shows that-in addition to recombination rate-the distribution of TEs is shaped by the interaction of gene expression and genome organization. The important role of selection for compactness sheds a new light on the role of TEs in genome evolution. Instead of making genomes grow passively, TEs are controlled by the forces shaping genome compactness, most likely linked to the efficiency of gene expression or its complexity and possibly their interaction with mechanisms of TE silencing.

Bioclimatic constraints to Andean cat distribution: a modelling application for rare species

AimTo identify the bioclimatic niche of the endangered Andean cat (Leopardus jacobita), one of the rarest and least known felids in the world, by developing a species distribution model.LocationSouth America, High Andes and Patagonian steppe. Peru, Bolivia, Chile, Argentina.MethodsWe used 108 Andean cat records to build the models, and 27 to test them, applying the Maxent algorithm to sets of uncorrelated bioclimatic variables from global databases, including elevation. We based our biogeographical interpretations on the examination of the predicted geographic range, the modelled response curves and latitudinal variations in climatic variables associated with the locality data.ResultsSimple bioclimatic models for Andean cats were highly predictive with only 3-4 explanatory variables. The climatic niche of the species was defined by extreme diurnal variations in temperature, cold minimum and moderate maximum temperatures, and aridity, characteristic not only of the Andean highlands but also of the Patagonian steppe. Argentina had the highest representation of suitable climates, and Chile the lowest. The most favourable conditions were centrally located and spanned across international boundaries. Discontinuities in suitable climatic conditions coincided with three biogeographical barriers associated with climatic or topographic transitions.Main conclusionsSimple bioclimatic models can produce useful predictions of suitable climatic conditions for rare species, including major biogeographical constraints. In our study case, these constraints are also known to affect the distribution of other Andean species and the genetic structure of Andean cat populations. We recommend surveys of areas with suitable climates and no Andean cat records, including the corridor connecting two core populations. The inclusion of landscape variables at finer scales, crucially the distribution of Andean cat prey, would contribute to refine our predictions for conservation applications.

Modelling the effect of minor orthopaedic day surgery on patient mood at the early post-operative period: a prospective population-based cohort study.

OBJECTIVE: The effect of minor orthopaedic day surgery (MiODS) on patient's mood. METHODS: A prospective population-based cohort study of 148 consecutive patients with age above 18 and less than 65, an American Society of Anaesthesiology (ASA) score of 1, and the requirement of general anaesthesia (GA) were included. The Medical Outcomes Study - Short Form 36 (SF-36), Beck Anxiety Inventory (BAI) and Beck Depression Inventory (BDI) were used pre- and post-operatively. RESULTS: The mean physical component score of SF-36 before surgery was 45.3 (SD=+/-10.1) and 8 weeks following surgery was 44.9 (SD=+/-11.04) [n=148, p=0.51, 95% CI=(-1.03 to 1.52)]. For the measurement of the changes in mood using BDI, BAI and SF-36, latent construct modelling was employed to increase validity. The covariance between mood pre- and post-operatively (cov=69.44) corresponded to a correlation coefficient, r=0.88 indicating that patients suffering a greater number of mood symptoms before surgery continue to have a greater number of symptoms following surgery. When the latent mood constructs were permitted to have different means the model fitted well with chi(2) (df=1)=0.86 for which p=0.77, thus the null hypothesis that MiODS has no effect on patient mood was rejected. CONCLUSIONS: MiODS affects patient mood which deteriorates at 8 weeks post-operatively regardless of the pre-operative patient mood state. More importantly patients suffering a greater number of mood symptoms before MiODS continue to have a greater number of symptoms following surgery.