New validated prognostic models and prognostic calculators in patients with low-grade gliomas diagnosed by central pathology review: a pooled analysis of EORTC/RTOG/NCCTG phase III clinical trials.

Background In a previous study, the European Organisation for Research and Treatment of Cancer (EORTC) reported a scoring system to predict survival of patients with low-grade gliomas (LGGs). A major issue in the diagnosis of brain tumors is the lack of agreement among pathologists. New models in patients with LGGs diagnosed by central pathology review are needed. Methods Data from 339 EORTC patients with LGGs diagnosed by central pathology review were used to develop new prognostic models for progression-free survival (PFS) and overall survival (OS). Data from 450 patients with centrally diagnosed LGGs recruited into 2 large studies conducted by North American cooperative groups were used to validate the models. Results Both PFS and OS were negatively influenced by the presence of baseline neurological deficits, a shorter time since first symptoms (<30 wk), an astrocytic tumor type, and tumors larger than 5 cm in diameter. Early irradiation improved PFS but not OS. Three risk groups have been identified (low, intermediate, and high) and validated. Conclusions We have developed new prognostic models in a more homogeneous LGG population diagnosed by central pathology review. This population better fits with modern practice, where patients are enrolled in clinical trials based on central or panel pathology review. We could validate the models in a large, external, and independent dataset. The models can divide LGG patients into 3 risk groups and provide reliable individual survival predictions. Inclusion of other clinical and molecular factors might still improve models' predictions.

PACIC Instrument: disentangling dimensions using published validation models.

OBJECTIVE: To better understand the structure of the Patient Assessment of Chronic Illness Care (PACIC) instrument. More specifically to test all published validation models, using one single data set and appropriate statistical tools. DESIGN: Validation study using data from cross-sectional survey. PARTICIPANTS: A population-based sample of non-institutionalized adults with diabetes residing in Switzerland (canton of Vaud). MAIN OUTCOME MEASURE: French version of the 20-items PACIC instrument (5-point response scale). We conducted validation analyses using confirmatory factor analysis (CFA). The original five-dimension model and other published models were tested with three types of CFA: based on (i) a Pearson estimator of variance-covariance matrix, (ii) a polychoric correlation matrix and (iii) a likelihood estimation with a multinomial distribution for the manifest variables. All models were assessed using loadings and goodness-of-fit measures. RESULTS: The analytical sample included 406 patients. Mean age was 64.4 years and 59% were men. Median of item responses varied between 1 and 4 (range 1-5), and range of missing values was between 5.7 and 12.3%. Strong floor and ceiling effects were present. Even though loadings of the tested models were relatively high, the only model showing acceptable fit was the 11-item single-dimension model. PACIC was associated with the expected variables of the field. CONCLUSIONS: Our results showed that the model considering 11 items in a single dimension exhibited the best fit for our data. A single score, in complement to the consideration of single-item results, might be used instead of the five dimensions usually described.

Estimating the basic reproductive number from viral sequence data.

Epidemiological processes leave a fingerprint in the pattern of genetic structure of virus populations. Here, we provide a new method to infer epidemiological parameters directly from viral sequence data. The method is based on phylogenetic analysis using a birth-death model (BDM) rather than the commonly used coalescent as the model for the epidemiological transmission of the pathogen. Using the BDM has the advantage that transmission and death rates are estimated independently and therefore enables for the first time the estimation of the basic reproductive number of the pathogen using only sequence data, without further assumptions like the average duration of infection. We apply the method to genetic data of the HIV-1 epidemic in Switzerland.

Exploring models for the length of stay distribution.

Diagnosis Related Groups (DRG) are frequently used to standardize the comparison of consumption variables, such as length of stay (LOS). In order to be reliable, this comparison must control for the presence of outliers, i.e. values far removed from the pattern set by the majority of the data. Indeed, outliers can distort the usual statistical summaries, such as means and variances. A common practice is to trim LOS values according to various empirical rules, but there is little theoretical support for choosing between alternative procedures. This pilot study explores the possibility of describing LOS distributions with parametric models which provide the necessary framework for the use of robust methods.

Focused time-lapse inversion of radio and audio magnetotelluric data

Geoelectrical techniques are widely used to monitor groundwater processes, while surprisingly few studies have considered audio (AMT) and radio (RMT) magnetotellurics for such purposes. In this numerical investigation, we analyze to what extent inversion results based on AMT and RMT monitoring data can be improved by (1) time-lapse difference inversion; (2) incorporation of statistical information about the expected model update (i.e., the model regularization is based on a geostatistical model); (3) using alternative model norms to quantify temporal changes (i.e., approximations of l(1) and Cauchy norms using iteratively reweighted least-squares), (4) constraining model updates to predefined ranges (i.e., using Lagrange Multipliers to only allow either increases or decreases of electrical resistivity with respect to background conditions). To do so, we consider a simple illustrative model and a more realistic test case related to seawater intrusion. The results are encouraging and show significant improvements when using time-lapse difference inversion with non l(2) model norms. Artifacts that may arise when imposing compactness of regions with temporal changes can be suppressed through inequality constraints to yield models without oscillations outside the true region of temporal changes. Based on these results, we recommend approximate l(1)-norm solutions as they can resolve both sharp and smooth interfaces within the same model. (C) 2012 Elsevier B.V. All rights reserved.

GeoKernels: Modeling of Spatial Data on GeoManifolds

This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental data modeling on natural manifolds, such as complex topographies of the mountainous regions, where environmental processes are highly influenced by the relief. These relations, possibly regionalized and nonlinear, can be modeled from data with machine learning using the digital elevation models in semi-supervised kernel methods. The range of the tools and methodological issues discussed in the study includes feature selection and semisupervised Support Vector algorithms. The real case study devoted to data-driven modeling of meteorological fields illustrates the discussed approach.

Neocortical maturation during adolescence: change in neuronal soma dimension.

During adolescence, cognitive abilities increase robustly. To search for possible related structural alterations of the cerebral cortex, we measured neuronal soma dimension (NSD = width times height), cortical thickness and neuronal densities in different types of neocortex in post-mortem brains of five 12-16 and five 17-24 year-olds (each 2F, 3M). Using a generalized mixed model analysis, mean normalized NSD comparing the age groups shows layer-specific change for layer 2 (p < .0001) and age-related differences between categorized type of cortex: primary/primary association cortex (BA 1, 3, 4, and 44) shows a generalized increase; higher-order regions (BA 9, 21, 39, and 45) also show increase in layers 2 and 5 but decrease in layers 3, 4, and 6 while limbic/orbital cortex (BA 23, 24, and 47) undergoes minor decrease (BA 1, 3, 4, and 44 vs. BA 9, 21, 39, and 45: p = .036 and BA 1, 3, 4, and 44 vs. BA 23, 24, and 47: p = .004). These data imply the operation of cortical layer- and type-specific processes of growth and regression adding new evidence that the human brain matures during adolescence not only functionally but also structurally.

PyRate: a new program to estimate speciation and extinction rates from incomplete fossil data

Despite the advancement of phylogenetic methods to estimate speciation and extinction rates, their power can be limited under variable rates, in particular for clades with high extinction rates and small number of extant species. Fossil data can provide a powerful alternative source of information to investigate diversification processes. Here, we present PyRate, a computer program to estimate speciation and extinction rates and their temporal dynamics from fossil occurrence data. The rates are inferred in a Bayesian framework and are comparable to those estimated from phylogenetic trees. We describe how PyRate can be used to explore different models of diversification. In addition to the diversification rates, it provides estimates of the parameters of the preservation process (fossilization and sampling) and the times of speciation and extinction of each species in the data set. Moreover, we develop a new birth-death model to correlate the variation of speciation/extinction rates with changes of a continuous trait. Finally, we demonstrate the use of Bayes factors for model selection and show how the posterior estimates of a PyRate analysis can be used to generate calibration densities for Bayesian molecular clock analysis. PyRate is an open-source command-line Python program available at http://sourceforge.net/projects/pyrate/.

Measuring ecological niche overlap from occurrence and spatial environmental data

1. Aim - Concerns over how global change will influence species distributions, in conjunction with increased emphasis on understanding niche dynamics in evolutionary and community contexts, highlight the growing need for robust methods to quantify niche differences between or within taxa. We propose a statistical framework to describe and compare environmental niches from occurrence and spatial environmental data.¦2. Location - Europe, North America, South America¦3. Methods - The framework applies kernel smoothers to densities of species occurrence in gridded environmental space to calculate metrics of niche overlap and test hypotheses regarding niche conservatism. We use this framework and simulated species with predefined distributions and amounts of niche overlap to evaluate several ordination and species distribution modeling techniques for quantifying niche overlap. We illustrate the approach with data on two well-studied invasive species.¦4. Results - We show that niche overlap can be accurately detected with the framework when variables driving the distributions are known. The method is robust to known and previously undocumented biases related to the dependence of species occurrences on the frequency of environmental conditions that occur across geographic space. The use of a kernel smoother makes the process of moving from geographical space to multivariate environmental space independent of both sampling effort and arbitrary choice of resolution in environmental space. However, the use of ordination and species distribution model techniques for selecting, combining and weighting variables on which niche overlap is calculated provide contrasting results.¦5. Main conclusions - The framework meets the increasing need for robust methods to quantify niche differences. It is appropriate to study niche differences between species, subspecies or intraspecific lineages that differ in their geographical distributions. Alternatively, it can be used to measure the degree to which the environmental niche of a species or intraspecific lineage has changed over time.

Structural joint inversion of time-lapse crosshole ERT and GPR traveltime data

Time-lapse geophysical monitoring and inversion are valuable tools in hydrogeology for monitoring changes in the subsurface due to natural and forced (tracer) dynamics. However, the resulting models may suffer from insufficient resolution, which leads to underestimated variability and poor mass recovery. Structural joint inversion using cross-gradient constraints can provide higher-resolution models compared with individual inversions and we present the first application to time-lapse data. The results from a synthetic and field vadose zone water tracer injection experiment show that joint 3-D time-lapse inversion of crosshole electrical resistance tomography (ERT) and ground penetrating radar (GPR) traveltime data significantly improve the imaged characteristics of the point injected plume, such as lateral spreading and center of mass, as well as the overall consistency between models. The joint inversion method appears to work well for cases when one hydrological state variable (in this case moisture content) controls the time-lapse response of both geophysical methods. Citation: Doetsch, J., N. Linde, and A. Binley (2010), Structural joint inversion of time-lapse crosshole ERT and GPR traveltime data, Geophys. Res. Lett., 37, L24404, doi: 10.1029/2010GL045482.

How quickly should we titrate antihypertensive medication? Systematic review modelling blood pressure response from trial data.

Context There are no evidence syntheses available to guide clinicians on when to titrate antihypertensive medication after initiation. Objective To model the blood pressure (BP) response after initiating antihypertensive medication. Data sources electronic databases including Medline, Embase, Cochrane Register and reference lists up to December 2009. Study selection Trials that initiated antihypertensive medication as single therapy in hypertensive patients who were either drug naive or had a placebo washout from previous drugs. Data extraction Office BP measurements at a minimum of two weekly intervals for a minimum of 4 weeks. An asymptotic approach model of BP response was assumed and non-linear mixed effects modelling used to calculate model parameters. Results and conclusions Eighteen trials that recruited 4168 patients met inclusion criteria. The time to reach 50% of the maximum estimated BP lowering effect was 1 week (systolic 0.91 weeks, 95% CI 0.74 to 1.10; diastolic 0.95, 0.75 to 1.15). Models incorporating drug class as a source of variability did not improve fit of the data. Incorporating the presence of a titration schedule improved model fit for both systolic and diastolic pressure. Titration increased both the predicted maximum effect and the time taken to reach 50% of the maximum (systolic 1.2 vs 0.7 weeks; diastolic 1.4 vs 0.7 weeks). Conclusions Estimates of the maximum efficacy of antihypertensive agents can be made early after starting therapy. This knowledge will guide clinicians in deciding when a newly started antihypertensive agent is likely to be effective or not at controlling BP.

Test of four colon cancer risk-scores in formalin fixed paraffin embedded microarray gene expression data.

BACKGROUND: Prognosis prediction for resected primary colon cancer is based on the T-stage Node Metastasis (TNM) staging system. We investigated if four well-documented gene expression risk scores can improve patient stratification. METHODS: Microarray-based versions of risk-scores were applied to a large independent cohort of 688 stage II/III tumors from the PETACC-3 trial. Prognostic value for relapse-free survival (RFS), survival after relapse (SAR), and overall survival (OS) was assessed by regression analysis. To assess improvement over a reference, prognostic model was assessed with the area under curve (AUC) of receiver operating characteristic (ROC) curves. All statistical tests were two-sided, except the AUC increase. RESULTS: All four risk scores (RSs) showed a statistically significant association (single-test, P < .0167) with OS or RFS in univariate models, but with HRs below 1.38 per interquartile range. Three scores were predictors of shorter RFS, one of shorter SAR. Each RS could only marginally improve an RFS or OS model with the known factors T-stage, N-stage, and microsatellite instability (MSI) status (AUC gains < 0.025 units). The pairwise interscore discordance was never high (maximal Spearman correlation = 0.563) A combined score showed a trend to higher prognostic value and higher AUC increase for OS (HR = 1.74, 95% confidence interval [CI] = 1.44 to 2.10, P < .001, AUC from 0.6918 to 0.7321) and RFS (HR = 1.56, 95% CI = 1.33 to 1.84, P < .001, AUC from 0.6723 to 0.6945) than any single score. CONCLUSIONS: The four tested gene expression-based risk scores provide prognostic information but contribute only marginally to improving models based on established risk factors. A combination of the risk scores might provide more robust information. Predictors of RFS and SAR might need to be different.

Unfolding nature "in silico" : overcoming practical and metodological limitations of species distribution models

Abstract : The existence of a causal relationship between the spatial distribution of living organisms and their environment, in particular climate, has been long recognized and is the central principle of biogeography. In turn, this recognition has led scientists to the idea of using the climatic, topographic, edaphic and biotic characteristics of the environment to predict its potential suitability for a given species or biological community. In this thesis, my objective is to contribute to the development of methodological improvements in the field of species distribution modeling. More precisely, the objectives are to propose solutions to overcome limitations of species distribution models when applied to conservation biology issues, or when .used as an assessment tool of the potential impacts of global change. The first objective of my thesis is to contribute to evidence the potential of species distribution models for conservation-related applications. I present a methodology to generate pseudo-absences in order to overcome the frequent lack of reliable absence data. I also demonstrate, both theoretically (simulation-based) and practically (field-based), how species distribution models can be successfully used to model and sample rare species. Overall, the results of this first part of the thesis demonstrate the strong potential of species distribution models as a tool for practical applications in conservation biology. The second objective this thesis is to contribute to improve .projections of potential climate change impacts on species distributions, and in particular for mountain flora. I develop and a dynamic model, MIGCLIM, that allows the implementation of dispersal limitations into classic species distribution models and present an application of this model to two virtual species. Given that accounting for dispersal limitations requires information on seed dispersal, distances, a general methodology to classify species into broad dispersal types is also developed. Finally, the M~GCLIM model is applied to a large number of species in a study area of the western Swiss Alps. Overall, the results indicate that while dispersal limitations can have an important impact on the outcome of future projections of species distributions under climate change scenarios, estimating species threat levels (e.g. species extinction rates) for a mountainous areas of limited size (i.e. regional scale) can also be successfully achieved when considering dispersal as unlimited (i.e. ignoring dispersal limitations, which is easier from a practical point of view). Finally, I present the largest fine scale assessment of potential climate change impacts on mountain vegetation that has been carried-out to date. This assessment involves vegetation from 12 study areas distributed across all major western and central European mountain ranges. The results highlight that some mountain ranges (the Pyrenees and the Austrian Alps) are expected to be more affected by climate change than others (Norway and the Scottish Highlands). The results I obtain in this study also indicate that the threat levels projected by fine scale models are less severe than those derived from coarse scale models. This result suggests that some species could persist in small refugias that are not detected by coarse scale models. Résumé : L'existence d'une relation causale entre la répartition des espèces animales et végétales et leur environnement, en particulier le climat, a été mis en évidence depuis longtemps et est un des principes centraux en biogéographie. Ce lien a naturellement conduit à l'idée d'utiliser les caractéristiques climatiques, topographiques, édaphiques et biotiques de l'environnement afin d'en prédire la qualité pour une espèce ou une communauté. Dans ce travail de thèse, mon objectif est de contribuer au développement d'améliorations méthodologiques dans le domaine de la modélisation de la distribution d'espèces dans le paysage. Plus précisément, les objectifs sont de proposer des solutions afin de surmonter certaines limitations des modèles de distribution d'espèces dans des applications pratiques de biologie de la conservation ou dans leur utilisation pour évaluer l'impact potentiel des changements climatiques sur l'environnement. Le premier objectif majeur de mon travail est de contribuer à démontrer le potentiel des modèles de distribution d'espèces pour des applications pratiques en biologie de la conservation. Je propose une méthode pour générer des pseudo-absences qui permet de surmonter le problème récurent du manque de données d'absences fiables. Je démontre aussi, de manière théorique (par simulation) et pratique (par échantillonnage de terrain), comment les modèles de distribution d'espèces peuvent être utilisés pour modéliser et améliorer l'échantillonnage des espèces rares. Ces résultats démontrent le potentiel des modèles de distribution d'espèces comme outils pour des applications de biologie de la conservation. Le deuxième objectif majeur de ce travail est de contribuer à améliorer les projections d'impacts potentiels des changements climatiques sur la flore, en particulier dans les zones de montagnes. Je développe un modèle dynamique de distribution appelé MigClim qui permet de tenir compte des limitations de dispersion dans les projections futures de distribution potentielle d'espèces, et teste son application sur deux espèces virtuelles. Vu que le fait de prendre en compte les limitations dues à la dispersion demande des données supplémentaires importantes (p.ex. la distance de dispersion des graines), ce travail propose aussi une méthode de classification simplifiée des espèces végétales dans de grands "types de disperseurs", ce qui permet ainsi de d'obtenir de bonnes approximations de distances de dispersions pour un grand nombre d'espèces. Finalement, j'applique aussi le modèle MIGCLIM à un grand nombre d'espèces de plantes dans une zone d'études des pré-Alpes vaudoises. Les résultats montrent que les limitations de dispersion peuvent avoir un impact considérable sur la distribution potentielle d'espèces prédites sous des scénarios de changements climatiques. Cependant, quand les modèles sont utilisés pour évaluer les taux d'extinction d'espèces dans des zones de montages de taille limitée (évaluation régionale), il est aussi possible d'obtenir de bonnes approximations en considérant la dispersion des espèces comme illimitée, ce qui est nettement plus simple d'un point dé vue pratique. Pour terminer je présente la plus grande évaluation à fine échelle d'impact potentiel des changements climatiques sur la flore des montagnes conduite à ce jour. Cette évaluation englobe 12 zones d'études réparties sur toutes les chaines de montages principales d'Europe occidentale et centrale. Les résultats montrent que certaines chaines de montagnes (les Pyrénées et les Alpes Autrichiennes) sont projetées comme plus sensibles aux changements climatiques que d'autres (les Alpes Scandinaves et les Highlands d'Ecosse). Les résultats obtenus montrent aussi que les modèles à échelle fine projettent des impacts de changement climatiques (p. ex. taux d'extinction d'espèces) moins sévères que les modèles à échelle large. Cela laisse supposer que les modèles a échelle fine sont capables de modéliser des micro-niches climatiques non-détectées par les modèles à échelle large.

Establishment of models to study mouse and human retinogenesis "in vitro" : isolation and characterization of retinal stem cells

SUMMARY IN FRENCH Les cellules souches sont des cellules indifférenciées capables a) de proliférer, b) de s'auto¬renouveller, c) de produire des cellules différenciées, postmitotiques et fonctionnelles (multipotencialité), et d) de régénérer le tissu après des lésions. Par exemple, les cellules de souches hematopoiétiques, situées dans la moelle osseuse, peuvent s'amplifier, se diviser et produire diverses cellules différenciées au cours de la vie, les cellules souches restant dans la moelle osseuse et consentant leur propriété. Les cellules souches intestinales, situées dans la crypte des microvillosités peuvent également régénérer tout l'intestin au cours de la vie. La rétine se compose de six classes de neurones et d'un type de cellule gliale. Tous ces types de cellules sont produits par un progéniteur rétinien. Le pic de production des photorécepteurs se situe autour des premiers jours postnatals chez la souris. A cette période la rétine contient les cellules hautement prolifératives. Dans cette étude, nous avons voulu analyser le phénotype de ces cellules et leur potentiel en tant que cellules souches ou progénitrices. Nous nous sommes également concentrés sur l'effet de certains facteurs épigéniques sur leur destin cellulaire. Nous avons observé que toutes les cellules prolifératives isolées à partir de neurorétines postnatales de souris expriment le marqueur de glie radiaire RC2, ainsi que des facteurs de transcription habituellement trouvés dans la glie radiaire (Mash1, Pax6), et répondent aux critères des cellules souches : une capacité élevée d'expansion, un état indifférencié, la multipotencialité (démontrée par analyse clonale). Nous avons étudié la différentiation des cellules dans différents milieux de culture. En l'absence de sérum, l'EGF induit l'expression de la β-tubulin-III, un marqueur neuronal, et l'acquisition d'une morphologie neuronale, ceci dans 15% des cellules présentes. Nous avons également analysé la prolifération de cellules. Seulement 20% des cellules incorporent le bromodéoxyuridine (BrdU) qui est un marqueur de division cellulaire. Ceci démontre que l'EGF induit la formation des neurones sans une progression massive du cycle cellulaire. Par ailleurs, une stimulation de 2h d'EGF est suffisante pour induire la différentiation neuronale. Certains des neurones formés sont des cellules ganglionnaires rétiniennes (GR), comme l'indique l'expression de marqueurs de cellules ganglionnaires (Ath5, Brn3b et mélanopsine), et dans de rare cas d'autres neurones rétiniens ont été observés (photorécepteurs (PR) et cellules bipolaires). Nous avons confirmé que les cellules souches rétiniennes tardives n'étaient pas restreintes au cours du temps et qu'elles conservent leur multipotencialité en étant capables de générer des neurones dits précoces (GR) ou tardifs (PR). Nos résultats prouvent que l'EGF est non seulement un facteur contrôlant le développement glial, comme précédemment démontré, mais également un facteur efficace de différentiation pour les neurones rétiniens, du moins in vitro. D'autre part, nous avons voulu établir si l'oeil adulte humain contient des cellules souches rétiniennes (CSRs). L'oeil de certains poissons ou amphibiens continue de croître pendant l'âge adulte du fait de l'activité persistante des cellules souches rétiniennes. Chez les poissons, le CSRs se situe dans la marge ciliaire (CM) à la périphérie de la rétine. Bien que l'oeil des mammifères ne se développe plus pendant la vie d'adulte, plusieurs groupes ont prouvé que l'oeil de mammifères adultes contient des cellules souches rétiniennes également dans la marge ciliaire plus précisément dans l'épithélium pigmenté et non dans la neurorétine. Ces CSRs répondent à certains critères des cellules souches. Nous avons identifié et caractérisé les cellules souches rétiniennes résidant dans l'oeil adulte humain. Nous avons prouvé qu'elles partagent les mêmes propriétés que leurs homologues chez les rongeurs c.-à-d. auto-renouvellement, amplification, et différenciation en neurones rétiniens in vitro et in vivo (démontré par immunocoloration et microarray). D'autre part, ces cellules peuvent être considérablement amplifiées, tout en conservant leur potentiel de cellules souches, comme indiqué par l'analyse de leur profil d'expression génique (microarray). Elles expriment également des gènes communs à diverses cellules souches: nucleostemin, nestin, Brni1, Notch2, ABCG2, c-kit et son ligand, aussi bien que cyclin D3 qui agit en aval de c-kit. Nous avons pu montré que Bmi1et Oct4 sont nécessaires pour la prolifération des CSRs confortant leur propriété de cellules souches. Nos données indiquent que la neurorétine postnatale chez la souris et l'épithélium pigmenté de la marge ciliaire chez l'humain adulte contiennent les cellules souches rétiniennes. En outre, nous avons développé un système qui permet d'amplifier et de cultiver facilement les CSRs. Ce modèle permet de disséquer les mécanismes impliqués lors de la retinogenèse. Par exemple, ce système peut être employé pour l'étude des substances ou des facteurs impliqués, par exemple, dans la survie ou dans la génération des cellules rétiniennes. Il peut également aider à disséquer la fonction de gènes ou les facteurs impliqués dans la restriction ou la spécification du destin cellulaire. En outre, dans les pays occidentaux, la rétinite pigmentaire (RP) touche 1 individu sur 3500 et la dégénérescence maculaire liée à l'âge (DMLA) affecte 1 % à 3% de la population âgée de plus de 60 ans. La génération in vitro de cellules rétiniennes est aussi un outil prometteur pour fournir une source illimitée de cellules pour l'étude de transplantation cellulaire pour la rétine. SUMMARY IN ENGLISH Stem cells are defined as undifferentiated cells capable of a) proliferation, b) self maintenance (self-renewability), c) production of many differentiated functional postmitotic cells (multipotency), and d) regenerating tissue after injury. For instance, hematopoietic stem cells, located in bone marrow, can expand, divide and generate differentiated cells into the diverse lineages throughout life, the stem cells conserving their status. In the villi crypt, the intestinal stem cells are also able to regenerate the intestine during their life time. The retina is composed of six classes of neurons and one glial cell. All these cell types are produced by the retinal progenitor cell. The peak of photoreceptor production is reached around the first postnatal days in rodents. Thus, at this stage the retina contains highly proliferative cells. In our research, we analyzed the phenotype of these cells and their potential as possible progenitor or stem cells. We also focused on the effect of epigenic factor(s) and cell fate determination. All the proliferating cells isolated from mice postnatal neuroretina harbored the radial glia marker RC2, expressed transcription factors usually found in radial glia (Mash 1, Pax6), and met the criteria of stem cells: high capacity of expansion, maintenance of an undifferentiated state, and multipotency demonstrated by clonal analysis. We analyzed the differentiation seven days after the transfer of the cells in different culture media. In the absence of serum, EGF led to the expression of the neuronal marker β-tubulin-III, and the acquisition of neuronal morphology in 15% of the cells. Analysis of cell proliferation by bromodeoxyuridine incorporation revealed that EGF mainly induced the formation of neurons without stimulating massively cell cycle progression. Moreover, a pulse of 2h EGF stimulation was sufficient to induce neuronal differentiation. Some neurons were committed to the retinal ganglion cell (RGC) phenotype, as revealed by the expression of retinal ganglion markers (Ath5, Brn3b and melanopsin), and in few cases to other retinal phenotypes (photoreceptors (PRs) and bipolar cells). We confirmed that the late RSCs were not restricted over-time and conserved multipotentcy characteristics by generating retinal phenotypes that usually appear at early (RGC) or late (PRs) developmental stages. Our results show that EGF is not only a factor controlling glial development, as previously shown, but also a potent differentiation factor for retinal neurons, at least in vitro. On the other hand, we wanted to find out if the adult human eye contains retina stem cells. The eye of some fishes and amphibians continues to grow during adulthood due to the persistent activity of retinal stem cells (RSCs). In fish, the RSCs are located in the ciliary margin zone (CMZ) at the periphery of the retina. Although, the adult mammalian eye does not grow during adult life, several groups have shown that the adult mouse eye contains retinal stem cells in the homologous zone (i.e. the ciliary margin), in the pigmented epithelium and not in the neuroretina. These RSCs meet some criteria of stem cells. We identified and characterized the human retinal stem cells. We showed that they posses the same features as their rodent counterpart i.e. they self-renew, expand and differentiate into retinal neurons in vitro and in vivo (indicated by immunostaining and microarray analysis). Moreover, they can be greatly expanded while conserving their sternness potential as revealed by the gene expression profile analysis (microarray approach). They also expressed genes common to various stem cells: nucleostemin, nestin, Bmil , Notch2, ABCG2, c-kit and its ligand, as well as cyclin D3 which acts downstream of c-kit. Furthermore, Bmil and Oct-4 were required for RSC proliferation reinforcing their stem cell identity. Our data indicate that the mice postnatal neuroretina and the adult pigmented epithelium of adult human ciliary margin contain retinal stem cells. We developed a system to easily expand and culture RSCs that can be used to investigate the retinogenesis. For example, it can help to screen drugs or factors involved, for instance, in the survival or generation of retinal cells. This could help to dissect genes or factors involved in the restriction or specification of retinal cell fate. In Western countries, retinitis pigmentosa (RP) affects 1 out of 3'500 individuals and age-related macula degeneration (AMD) strikes 1 % to 3% of the population over 60. In vitro generation of retinal cells is thus a promising tool to provide an unlimited cell source for cellular transplantation studies in the retina.

Impact of biological and environmental variabilities on biological monitoring: an approach using toxicokinetic models

Biological monitoring of occupational exposure is characterized by important variability, due both to variability in the environment and to biological differences between workers. A quantitative description and understanding of this variability is important for a dependable application of biological monitoring. This work describes this variability,using a toxicokinetic model, for a large range of chemicals for which reference biological reference values exist. A toxicokinetic compartmental model describing both the parent compound and its metabolites was used. For each chemical, compartments were given physiological meaning. Models were elaborated based on physiological, physicochemical, and biochemical data when available, and on half-lives and central compartment concentrations when not available. Fourteen chemicals were studied (arsenic, cadmium, carbon monoxide, chromium, cobalt, ethylbenzene, ethyleneglycol monomethylether, fluorides, lead, mercury, methyl isobutyl ketone, penthachlorophenol, phenol, and toluene), representing 20 biological indicators. Occupational exposures were simulated using Monte Carlo techniques with realistic distributions of both individual physiological parameters and exposure conditions. Resulting biological indicator levels were then analyzed to identify the contribution of environmental and biological variability to total variability. Comparison of predicted biological indicator levels with biological exposure limits showed a high correlation with the model for 19 out of 20 indicators. Variability associated with changes in exposure levels (GSD of 1.5 and 2.0) is shown to be mainly influenced by the kinetics of the biological indicator. Thus, with regard to variability, we can conclude that, for the 14 chemicals modeled, biological monitoring would be preferable to air monitoring. For short half-lives (less than 7 hr), this is very similar to the environmental variability. However, for longer half-lives, estimated variability decreased. [Supplementary materials are available for this article. Go to the publisher's online edition of Journal of Occupational and Environmental Hygiene for the following free supplemental resource: tables detailing the CBTK models for all 14 chemicals and the symbol nomenclature that was used.] [Authors]