Development and characterization of a new human hepatic cell line

The increasing demand and hampered use of primary human hepatocytes for research purposes have urged scientists to search for alternative cell sources, such as immortalized hepatic cell lines. The aim of this study was to develop a human hepatic cell line using the combined overexpression of TERT and the cell cycle regulators cyclin D1 and mutant isoform CDK4R24C. Following transduction of adult human primary hepatocytes with the selected immortalization genes, cell growth was triggered and a cell line was established. When cultured under appropriate conditions, the cell line expressed several hepatocytic markers and liver-enriched transcription factors at the transcriptional and/or translational level, secreted liver-specific proteins and showed glycogen deposition. These results suggest that the immortalization strategy applied to primary human hepatocytes could generate a novel hepatic cell line that seems to retain some key hepatic characteristics

Development and characterization of a new human hepatic cell line

The increasing demand and hampered use of primary human hepatocytes for research purposes have urged scientists to search for alternative cell sources, such as immortalized hepatic cell lines. The aim of this study was to develop a human hepatic cell line using the combined overexpression of TERT and the cell cycle regulators cyclin D1 and mutant isoform CDK4R24C. Following transduction of adult human primary hepatocytes with the selected immortalization genes, cell growth was triggered and a cell line was established. When cultured under appropriate conditions, the cell line expressed several hepatocytic markers and liver-enriched transcription factors at the transcriptional and/or translational level, secreted liver-specific proteins and showed glycogen deposition. These results suggest that the immortalization strategy applied to primary human hepatocytes could generate a novel hepatic cell line that seems to retain some key hepatic characteristics

Constrained manifold learning for the characterization of pathological deviations from normality

International audienceThis paper describes a technique to (1) learn the representation of a pathological motion pattern from a given population, and (2) compare individuals to this population. Our hypothesis is that this pattern can be modeled as a deviation from normal motion by means of non-linear embedding techniques. Each subject is represented by a 2D map of local motion abnormalities, obtained from a statistical atlas of myocardial motion built from a healthy population. The algorithm estimates a manifold from a set of patients with varying degrees of the same disease, and compares individuals to the training population using a mapping to the manifold and a distance to normality along the manifold. The approach extends recent manifold learning techniques by constraining the manifold to pass by a physiologically meaningful origin representing a normal motion pattern. Interpolation techniques using locally adjustable kernel improve the accuracy of the method. The technique is applied in the context of cardiac resynchronization therapy (CRT), focusing on a specific motion pattern of intra-ventricular dyssynchrony called septal flash (SF). We estimate the manifold from 50 CRT candidates with SF and test it on 37 CRT candidates and 21 healthy volunteers. Experiments highlight the relevance of nonlinear techniques to model a pathological pattern from the training set and compare new individuals to this pattern

Characterizing Pathological Deviations from Normality using Constrained Manifold-Learning

International audienceWe propose a technique to represent a pathological pattern as a deviation from normality along a manifold structure. Each subject is represented by a map of local motion abnormalities, obtained from a statistical atlas of motion built from a healthy population. The algorithm learns a manifold from a set of patients with varying degrees of the same pathology. The approach extends recent manifold-learning techniques by constraining the manifold to pass by a physiologically meaningful origin representing a normal motion pattern. Individuals are compared to the manifold population through a distance that combines a mapping to the manifold and the path along the manifold to reach its origin. The method is applied in the context of cardiac resynchronization therapy (CRT), focusing on a specific motion pattern of intra-ventricular dyssyn-chrony called septal flash (SF). We estimate the manifold from 50 CRT candidates with SF and test it on 38 CRT candidates and 21 healthy volunteers. Experiments highlight the need of nonlinear techniques to learn the studied data, and the relevance of the computed distance for comparing individuals to a specific pathological pattern

Métriques de distorsion pour l'analyse comparative de schémas de filigranage 3D

Dans cet article, nous traitons de la problématique de la mesure de distorsion des maillages 3D dans le cadre de l'analyse comparative de schémas de filigranage. Cette mesure est nécessaire afin de classifier les types de déformations acceptables et de déterminer des seuils de tolérance. Nous proposons dans cette optique deux approches distinctes et complémentaires. La première consiste en une métrique perceptive globale basée sur l'analyse des différences entre les vues 2D correspondantes de l'objet 3D et de sa version déformée. Nous montrons par nos résultats que le choix de l'information mutuelle comme critère de comparaison de ces vues projetées permet de mieux détecter de faibles distorsions à la limite de l'imperceptibilité, courantes dans le cadre du filigranage. La deuxième approche complète la première en analysant les différences locales entre maillages via l'estimation de l'énergie de déformation. Cette stratégie trouve ses fondements notamment dans le calcul de la paramétrisation planaire ou sphérique des surfaces maillées. Cette étude se conclut par la comparaison des résultats de ces méthodes et des métriques 3D de l'état de l'art

Septal Flash Assessment on CRT Candidates Based on Statistical Atlases of Motion

International audienceIn this paper, we propose a complete framework for the automatic detection and quantification of abnormal heart motion patterns using Statistical Atlases of Motion built from healthy populations. The method is illustrated on CRT patients with identified cardiac dyssyn-chrony and abnormal septal motion on 2D ultrasound (US) sequences. The use of the 2D US modality guarantees that the temporal resolution of the image sequences is high enough to work under a small displacements hypothesis. Under this assumption, the computed displacement fields can be directly considered as cardiac velocities. Comparison of subjects acquired with different spatiotemporal resolutions implies the reorientation and temporal normalization of velocity fields in a common space of coordinates. Statistics are then performed on the reoriented vector fields. Results show the ability of the method to correctly detect abnormal motion patterns and quantify their distance to normality. The use of local p-values for quantifying abnormal motion patterns is believed to be a promising strategy for computing new markers of cardiac dyssynchrony for better characterizing CRT candidates

A groupwise mutual information metric for cost efficient selection of a suitable reference in cardiac computational atlas construction

International audienceComputational atlases based on nonrigid registration have found much use in the medical imaging community. To avoid bias to any single element of the training set, there are two main approaches: using a (random) subject to serve as an initial reference and posteriorly removing bias, and a true groupwise registration with a constraint of zero average transformation for direct computation of the atlas. Major drawbacks are the possible selection of an outlier on one side, and an initialization with an invalid instance on the other. In both cases there is great potential for affecting registration performance, and producing a final average image in which the structure of interest deviates from the central anatomy of the population under study. We propose an inexpensive means of reference selection based on a groupwise correspondence measure, which avoids the selection of an outlier and is independent from the atlas construction approach that follows. Thus, it improves tractability of reference selection and robustness of automated atlas construction. We illustrate the method using a set of 20 cardiac multislice computed tomography volumes

Strategies for immortalization of primary hepatocytes

SummaryThe liver has the unique capacity to regenerate in response to a damaging event. Liver regeneration is hereby largely driven by hepatocyte proliferation, which in turn relies on cell cycling. The hepatocyte cell cycle is a complex process that is tightly regulated by several well-established mechanisms. In vitro, isolated hepatocytes do not longer retain this proliferative capacity. However, in vitro cell growth can be boosted by immortalization of hepatocytes. Well-defined immortalization genes can be artificially overexpressed in hepatocytes or the cells can be conditionally immortalized leading to controlled cell proliferation. This paper discusses the current immortalization techniques and provides a state-of-the-art overview of the actually available immortalized hepatocyte-derived cell lines and their applications

Learning pathological deviations from a normal pattern of myocardial motion: Added value for CRT studies?

International audienceStrong links exist between mechanical dyssynchrony and the response to cardiac resynchronization therapy (CRT). Recent publications recommend identifying correctable dyssynchrony patterns with a specific motion and deformation signature. The learning of these patterns is visual and highly subjective. We take advantage of statistical atlas and dimensionality reduction tools to learn a representation of these patterns. We hypothesize that myocardial motion patterns belong or lie close to a non-linear manifold, and model them as a pathological deviation from normality. Furthermore, we propose distances to compare new subjects with those patterns and with normality. We evaluate the value of this approach on 2D echocardiographic sequences from CRT candidates at baseline, with pacing on, and at one-year follow-up. We demonstrate that relating pattern changes with patient response is valuable, and paves the ground towards better therapy planning

Myocardial motion estimation combining tissue Doppler and B-mode echocardiographic images

International audienceWe present a registration framework that combines both tissue Doppler and B-mode echocardiographic sequences. The estimated spatiotemporal transform is diffeomorphic, and calculated by modeling its corresponding velocity field using continuous B-splines. A new cost function using both B-mode image voxel intensities and Doppler velocities is also proposed. Registration accuracy was evaluated on synthetic data with known ground truth. Results showed that our method allows quantifying wall motion with higher accuracy than when using a single modality. On patient data, both displacement and velocity curves were compared with the ones obtained from widely used commercial software using either B-mode images or TDI. Our method demonstrated to be more robust to image noise while being independent from the beam angle