New genetic models and mesenchymal cells as tools to ameliorate anti-tumor immunity

Résumé Le but final de ce projet est d'utiliser des cellules T ou des cellules souches mésenchymateuses modifiées génétiquement afin de surexprimer localement les deux chémokines CXCL13 et CCL2 ensemble ou chacune séparément à l'intérieur d'une tumeur solide. CXCL13 est supposé induire des structures lymphoïdes ectopiques. Un niveau élevé de CCL2 est présumé initier une inflammation aiguë. La combinaison des deux effets amène à un nouveau modèle d'étude des mécanismes régulateur de la tolérance périphérique et de l'immunité tumorale. Les connaissances acquises grâce à ce modèle pourraient permettre le développement ou l'amélioration des thérapies immunes du cancer. Le but premier de ce travail a été l'établissement d'un modèle génétique de la souris permettant d'exprimer spécifiquement dans la tumeur les deux chémokines d'intérêt à des niveaux élevés. Pour accomplir cette tâche, qui est en fait une thérapie génétique de tumeurs solides, deux types de cellules porteuses potentielles ont été évaluées. Des cellules CD8+ T et des cellules mésenchymateuses de la moelle osseuse transférées dans des receveurs portant une tumeur. Si on pouvait répondre aux besoins de la thérapie génétique, indépendamment de la thérapie immune envisagée, on posséderait là un outil précieux pour bien d'autres approches thérapeutiques. Plusieurs lignées de souris transgéniques ont été générées comme source de cellules CD8+ T modifiées afin d'exprimer les chémokines d'intérêt. Dans une approche doublement transgénique les propriétés de deux promoteurs spécifiques de cellules T ont été combinées en utilisant la technologie Cre-loxP. Le promoteur de granzyme B confère une dépendance d'activation et le promoteur distal de lck assure une forte expression constitutive dès que les cellules CD8+ T ont été activées. Les transgènes construits ont montré une bonne performance in vivo et des souris qui expriment CCL2 dans des cellules CD8+ T activées ont été obtenues. Ces cellules peuvent maintenant être utilisées avec différents protocoles pour transférer des cellules T cytotoxiques (CTL) dans des receveurs porteur d'une tumeur, permettant ainsi d'évaluer leur capacité en tant que porteuse de chémokine d'infiltrer la tumeur. L'établissement de souris transgéniques, qui expriment pareillement CXCL13 est prévu dans un avenir proche. L'évaluation de cellules mésenchymateuses de la moelle osseuse a démontré que ces cellules se greffent efficacement dans le stroma tumoral suite à la co-injection avec des cellules tumorales. Cela représente un outil précieux pour la recherche, vu qu'il permet d'introduire des cellules manipulées dans un modèle tumoral. Les résultats confirment partiellement d'autres résultats rapportés dans un modèle amélioré. Cependant, l'efficacité et la spécificité suggérées de la migration systémique de cellules mésenchymateuses de la moelle osseuse dans une tumeur n'ont pas été observées dans notre modèle, ce qui indique, que ces cellules ne se prêtent pas à une utilisation thérapeutique. Un autre résultat majeur de ce travail est l'établissement de cultures de cellules mésenchymateuses de la moelle osseuse in vitro conditionnées par des tumeurs, ce qui a permis à ces cellules de s'étendre plus rapidement en gardant leur capacité de migration et de greffe. Cela offre un autre outil précieux, vu que la culture in vitro est un pas nécessaire pour une manipulation thérapeutique. Abstract The ultimate aim of the presented project is to use genetically modified T cells or mesenchymal stem cells to locally overexpress the two chemokines CXCL13 and CCL2 together or each one alone inside a solid tumor. CXCL13 is supposed to induce ectopic lymphoid structures and a high level of CCL2 is intended to trigger acute inflamation. The combination of these two effects represents a new model for studying mechanisms that regulate peripheral tolerance and tumor immunity. Gained insights may help developing or improving immunotherapy of cancer. The primary goal of the executed work was the establishment of a genetic mouse model that allows tumor-specific expression of high levels of the two chemokines of interest. For accomplishing this task, which represents gene therapy of solid tumors, two types of potentially useful carrier cells were evaluated. CD8+ T cells and mesenchymal bone marrow cells to be used in adoptive cell transfers into tumor-bearing mice. Irrespectively of the envisaged immunotherapy, satisfaction of so far unmet needs of gene therapy would be a highly valuable tool that may be employed by many other therapeutic approaches, too. Several transgenic mouse lines were generated as a source of CD8+ T cells modified to express the chemokines of interest. In a double transgenic approach the properties of two T cell-specific promoters were combined using Cre-loxP technology. The granzyme B promoter confers activation-dependency and the lck distal promoter assures strong constitutive expression once the CD8+ T cell has been activated. The constructed transgenes showed a good performance in vivo and mice expressing CCL2 in activated CD8+ T cells were obtained. These cells can now be used with different protocols for adoptively transferring cytotoxic T cells (CTL) into tumor-bearing recipients, thus allowing to study their capacity as tumor-infiltrating chemokine carrier. The establishment of transgenic mice likewisely expressing CXCL13 is expected in the near future. In addition, T cells from generated single transgenic mice that have high expression of an EGFP reporter in both CD4+ and CD8+ cells can be easily traced in vivo when setting up adoptive transfer conditions. The evaluation of mesenchymal bone marrow cells demonstrated that these cells can efficiently engraft into tumor stroma upon local coinjection with tumor cells. This represents a valuable tool for research purposes as it allows to introduce manipulated stromal cells into a tumor model. Therefore, the established engraftment model is suited for studying the envisaged immunotherapy. These results confirm to some extend previously reported results in an improved model, however, the suggested systemic tumor homing efficiency and specificity of mesenchymal bone marrow cells was not observed in our model indicating that these cells may not be suited for therapeutic use. Another major result of the presented work is the establishment oftumor-conditioned in vitro culture of mesenchymal bone marrow cells, which allowed to more rapidly expand these cells while maintaining their tumor homing and engrafting capacities. This offers another valuable tool as in vitro culture is a necessary step for therapeutic manipulations.

Peripheral inflammation increases the damage in animal models of nigrostriatal dopaminergic neurodegeneration: possible implication in Parkinson's disease incidence.

Inflammatory processes described in Parkinson’s disease (PD) and its animal models appear to be important in the progression of the pathogenesis, or even a triggering factor. Here we review that peripheral inflammation enhances the degeneration of the nigrostriatal dopaminergic system induced by different insults; different peripheral inflammations have been used, such as IL-1β and the ulcerative colitis model, as well as insults to the dopaminergic system such as 6-hydroxydopamine or lipopolysaccharide. In all cases, an increased loss of dopaminergic neurons was described; inflammation in the substantia nigra increased, displaying a great activation of microglia along with an increase in the production of cytokines such as IL-1β and TNF-α. Increased permeability or disruption of the BBB, with overexpression of the ICAM-1 adhesion molecule and infiltration of circulating monocytes into the substantia nigra, is also involved, since the depletion of circulating monocytes prevents the effects of peripheral inflammation. Data are reviewed in relation to epidemiological studies of PD.

Time-series regression models to study the short-term effects of environmental factors on health

Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants

Sulfur isotope analysis of cinnabar from Roman wall paintings by elemental analysis/isotope ratio mass spectrometry - tracking the origin of archaeological red pigments and their authenticity

The most valuable pigment of the Roman wall paintings was the red color obtained from powdered cinnabar (Minium Cinnabaris pigment), the red mercury sulfide (HgS), which was brought from mercury (Hg) deposits in the Roman Empire. To address the question of whether sulfur isotope signatures can serve as a rapid method to establish the provenance of the red pigment in Roman frescoes, we have measured the sulfur isotope composition (delta(34) S value in parts per thousand VCDT) in samples of wall painting from the Roman city Aventicum (Avenches, Vaud, Switzerland) and compared them with values from cinnabar from European mercury deposits (Almaden in Spain, Idria in Slovenia, Monte Amiata in Italy, Moschellandsberg in Germany, and Genepy in France). Our study shows that the delta(34) S values of cinnabar from the studied Roman wall paintings fall within or near to the composition of Almaden cinnabar; thus, the provenance of the raw material may be deduced. This approach may provide information on provenance and authenticity in archaeological, restoration and forensic studies of Roman and Greek frescoes. Copyright (c) 2010 John Wiley & Sons, Ltd.

Back to the future in Chagas disease: from animal models to patient cohort studies, progress in immunopathogenesis research

Despite the wealth of information generated by trans-disciplinary research in Chagas disease, knowledge about its multifaceted pathogenesis is still fragmented. Here we review the body of experimental studies in animal models supporting the concept that persistent infection by Trypanosoma cruzi is crucial for the development of chronic myocarditis. Complementing this review, we will make an effort to reconcile seemingly contradictory results concerning the immune profiles of chronic patients from Argentina and Brazil. Finally, we will review the results of molecular studies suggesting that parasite-induced inflammation and tissue damage is, at least in part, mediated by the activities of trans-sialidase, mucin-linked lipid anchors (TLR2 ligand) and cruzipain (a kinin-releasing cysteine protease). One hundred years after the discovery of Chagas disease, it is reassuring that basic and clinical research tends to converge, raising new perspectives for the treatment of chronic Chagas disease.

A Bayesian network approach to the database serch problem in criminal proceedings

Background The 'database search problem', that is, the strengthening of a case - in terms of probative value - against an individual who is found as a result of a database search, has been approached during the last two decades with substantial mathematical analyses, accompanied by lively debate and centrally opposing conclusions. This represents a challenging obstacle in teaching but also hinders a balanced and coherent discussion of the topic within the wider scientific and legal community. This paper revisits and tracks the associated mathematical analyses in terms of Bayesian networks. Their derivation and discussion for capturing probabilistic arguments that explain the database search problem are outlined in detail. The resulting Bayesian networks offer a distinct view on the main debated issues, along with further clarity. Methods As a general framework for representing and analyzing formal arguments in probabilistic reasoning about uncertain target propositions (that is, whether or not a given individual is the source of a crime stain), this paper relies on graphical probability models, in particular, Bayesian networks. This graphical probability modeling approach is used to capture, within a single model, a series of key variables, such as the number of individuals in a database, the size of the population of potential crime stain sources, and the rarity of the corresponding analytical characteristics in a relevant population. Results This paper demonstrates the feasibility of deriving Bayesian network structures for analyzing, representing, and tracking the database search problem. The output of the proposed models can be shown to agree with existing but exclusively formulaic approaches. Conclusions The proposed Bayesian networks allow one to capture and analyze the currently most well-supported but reputedly counter-intuitive and difficult solution to the database search problem in a way that goes beyond the traditional, purely formulaic expressions. The method's graphical environment, along with its computational and probabilistic architectures, represents a rich package that offers analysts and discussants with additional modes of interaction, concise representation, and coherent communication.

Simultaneous estimation of indirect and interaction effects using structural equation models

Interaction effects are usually modeled by means of moderated regression analysis. Structural equation models with non-linear constraints make it possible to estimate interaction effects while correcting formeasurement error. From the various specifications, Jöreskog and Yang's(1996, 1998), likely the most parsimonious, has been chosen and further simplified. Up to now, only direct effects have been specified, thus wasting much of the capability of the structural equation approach. This paper presents and discusses an extension of Jöreskog and Yang's specification that can handle direct, indirect and interaction effects simultaneously. The model is illustrated by a study of the effects of an interactive style of use of budgets on both company innovation and performance

Correcting Measurement Error Bias in Interaction Models with Small Samples

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

Policy gradient based Reinforcement Learning for real autonomous underwater cable tracking

This paper proposes a field application of a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot in cable tracking task. The learning system is characterized by using a direct policy search method for learning the internal state/action mapping. Policy only algorithms may suffer from long convergence times when dealing with real robotics. In order to speed up the process, the learning phase has been carried out in a simulated environment and, in a second step, the policy has been transferred and tested successfully on a real robot. Future steps plan to continue the learning process on-line while on the real robot while performing the mentioned task. We demonstrate its feasibility with real experiments on the underwater robot ICTINEU AUV

In vitro and in vivo experimental models for drug screening and development for Chagas disease

Chagas disease, a neglected illness, affects nearly 12-14 million people in endemic areas of Latin America. Although the occurrence of acute cases sharply has declined due to Southern Cone Initiative efforts to control vector transmission, there still remain serious challenges, including the maintenance of sustainable public policies for Chagas disease control and the urgent need for better drugs to treat chagasic patients. Since the introduction of benznidazole and nifurtimox approximately 40 years ago, many natural and synthetic compounds have been assayed against Trypanosoma cruzi, yet only a few compounds have advanced to clinical trials. This reflects, at least in part, the lack of consensus regarding appropriate in vitro and in vivo screening protocols as well as the lack of biomarkers for treating parasitaemia. The development of more effective drugs requires (i) the identification and validation of parasite targets, (ii) compounds to be screened against the targets or the whole parasite and (iii) a panel of minimum standardised procedures to advance leading compounds to clinical trials. This third aim was the topic of the workshop entitled Experimental Models in Drug Screening and Development for Chagas Disease, held in Rio de Janeiro, Brazil, on the 25th and 26th of November 2008 by the Fiocruz Program for Research and Technological Development on Chagas Disease and Drugs for Neglected Diseases Initiative. During the meeting, the minimum steps, requirements and decision gates for the determination of the efficacy of novel drugs for T. cruzi control were evaluated by interdisciplinary experts and an in vitro and in vivo flowchart was designed to serve as a general and standardised protocol for screening potential drugs for the treatment of Chagas disease.

Dam wall detection and tracking using a Mechanically Scanned Imaging Sonar

In dam inspection tasks, an underwater robot has to grab images while surveying the wall meanwhile maintaining a certain distance and relative orientation. This paper proposes the use of an MSIS (mechanically scanned imaging sonar) for relative positioning of a robot with respect to the wall. An imaging sonar gathers polar image scans from which depth images (range & bearing) are generated. Depth scans are first processed to extract a line corresponding to the wall (with the Hough transform), which is then tracked by means of an EKF (Extended Kalman Filter) using a static motion model and an implicit measurement equation associating the sensed points to the candidate line. The line estimate is referenced to the robot fixed frame and represented in polar coordinates (rho&thetas) which directly corresponds to the actual distance and relative orientation of the robot with respect to the wall. The proposed system has been tested in simulation as well as in water tank conditions

Recovering Euclidean deformable models from stereo-motion

In this paper we present a novel structure from motion (SfM) approach able to infer 3D deformable models from uncalibrated stereo images. Using a stereo setup dramatically improves the 3D model estimation when the observed 3D shape is mostly deforming without undergoing strong rigid motion. Our approach first calibrates the stereo system automatically and then computes a single metric rigid structure for each frame. Afterwards, these 3D shapes are aligned to a reference view using a RANSAC method in order to compute the mean shape of the object and to select the subset of points on the object which have remained rigid throughout the sequence without deforming. The selected rigid points are then used to compute frame-wise shape registration and to extract the motion parameters robustly from frame to frame. Finally, all this information is used in a global optimization stage with bundle adjustment which allows to refine the frame-wise initial solution and also to recover the non-rigid 3D model. We show results on synthetic and real data that prove the performance of the proposed method even when there is no rigid motion in the original sequence

Modern statistical models for forensic fingerprint examinations : a critical review

Over the last decade, the development of statistical models in support of forensic fingerprint identification has been the subject of increasing research attention, spurned on recently by commentators who claim that the scientific basis for fingerprint identification has not been adequately demonstrated. Such models are increasingly seen as useful tools in support of the fingerprint identification process within or in addition to the ACE-V framework. This paper provides a critical review of recent statistical models from both a practical and theoretical perspective. This includes analysis of models of two different methodologies: Probability of Random Correspondence (PRC) models that focus on calculating probabilities of the occurrence of fingerprint configurations for a given population, and Likelihood Ratio (LR) models which use analysis of corresponding features of fingerprints to derive a likelihood value representing the evidential weighting for a potential source.