Topography of brain sodium accumulation in progressive multiple sclerosis

Object

Sodium accumulation is involved in neuronal injury occurring in multiple sclerosis (MS). We aimed to assess sodium accumulation in progressive MS, known to suffer from severe neuronal injury.

Materials and methods

3D-²³Na-MRI was obtained on a 3T-MR-scanner in 20 progressive MS patients [11 primary-progressive (PPMS) and nine secondary-progressive (SPMS)] and 15 controls. Total sodium concentrations (TSC) within grey matter (GM), normal-appearing white matter (WM) and lesions were extracted. Statistical mapping analyses of TSC abnormalities were also performed.

Results

Progressive MS patients presented higher GM–TSC values (48.8 ± 3.1 mmol/l wet tissue vol, p < 0.001) and T₂lesions-TSC values (50.9 ± 2.2 mmol/l wet tissue vol, p = 0.01) compared to GM and WM of controls. Statistical mapping analysis showed TSC increases in PPMS patients confined to motor and somatosensory cortices, prefrontal cortices, pons and cerebellum. In SPMS, TSC increases were associated with areas involving: primary motor, premotor and somatosensory cortices; prefrontal, cingulate and visual cortices; the corpus callosum, thalami, brainstem and cerebellum. Anterior prefrontal and premotor cortices TSC were correlated with disability.

Conclusion

Sodium accumulation is present in progressive MS patients, more restricted to the motor system in PPMS and more widespread in SPMS. Local brain sodium accumulation appears as a promising marker to monitor patients with progressive MS.     

Degradation Products of Tryptophan in Cell Culture Media: Contribution to Color and Toxicity

Biomanufacturing processes may be optimized by storing cell culture media at room temperature, but this is currently limited by their instability and change in color upon long-term storage. This study demonstrates that one of the critical contributing factors toward media browning is tryptophan. LC-MS technology was utilized to identify tryptophan degradation products, which are likely formed primarily from oxidation reactions. Several of the identified compounds were shown to contribute significantly to color in solutions but also to exhibit toxicity against CHO cells. A cell-culture-compatible antioxidant, a-ketoglutaric acid, was found to be an efficient cell culture media additive for stabilizing components against degradation, inhibiting the browning of media formulations, and decreasing ammonia production, thus providing a viable method for developing room-temperature stable cell culture media.     

Multivariate Analysis of Multiple Datasets: a Practical Guide for Chemical Ecology

Chemical ecology has strong links with metabolomics, the large-scale study of all metabolites detectable in a biological sample. Consequently, chemical ecologists are often challenged by the statistical analyses of such large datasets. This holds especially true when the purpose is to integrate multiple datasets to obtain a holistic view and a better understanding of a biological system under study. The present article provides a comprehensive resource to analyze such complex datasets using multivariate methods. It starts from the necessary pre-treatment of data including data transformations and distance calculations, to the application of both gold standard and novel multivariate methods for the integration of different omics data. We illustrate the process of analysis along with detailed results interpretations for six issues representative of the different types of biological questions encountered by chemical ecologists. We provide the necessary knowledge and tools with reproducible R codes and chemical-ecological datasets to practice and teach multivariate methods.     

Monocular Vision for Mobile Robot Localization and Autonomous Navigation

This paper presents a new real-time localization system for a mobile robot. We show that autonomous navigation is possible in outdoor situation with the use of a single camera and natural landmarks. To do that, we use a three step approach. In a learning step, the robot is manually guided on a path and a video sequence is recorded with a front looking camera. Then a structure from motion algorithm is used to build a 3D map from this learning sequence. Finally in the navigation step, the robot uses this map to compute its localization in real-time and it follows the learning path or a slightly different path if desired. The vision algorithms used for map building and localization are first detailed. Then a large part of the paper is dedicated to the experimental evaluation of the accuracy and robustness of our algorithms based on experimental data collected during two years in various environments.     

Modeling the behavior of persons with mild cognitive impairment or Alzheimer’s for intelligent environment simulation

User Modeling and User-Adapted Interaction - Intelligent environments may improve the independence and quality of life of persons with mild cognitive impairment (MCI) or Alzheimer’s disease...     

Meaningful electronic signatures based on an automatic indexing method

Legal information certification and secured storage combined with documents electronic signature are of great interest when digital documents security and conservation are in concern. Therefore, these new and evolving technologies offer powerful abilities, such as identification, authentication and certification. The latter contribute to increase the global security of legal digital archives conservation and access. However, currently used cryptographic and hash coding concepts cannot intrinsically enclose cognitive information about both the signer and the signed content. Indeed, an evolution of these technologies may be necessary to achieve full text researches within hundreds or thousands of electronically signed documents. This article aims at describing a possible model along with associated processes to create and make use of these new electronic signatures called “meaningful electronic signatures” as opposed to traditional electronic signatures based on bit per bit computation.     

iLogDemons: A Demons-Based Registration Algorithm for Tracking Incompressible Elastic Biological Tissues

Tracking soft tissues in medical images using non-linear image registration algorithms requires methods that are fast and provide spatial transformations consistent with the biological characteristics of the tissues. LogDemons algorithm is a fast non-linear registration method that computes diffeomorphic transformations parameterised by stationary velocity fields. Although computationally efficient, its use for tissue tracking has been limited because of its ad-hoc Gaussian regularisation, which hampers the implementation of more biologically motivated regularisations. In this work, we improve the logDemons by integrating elasticity and incompressibility for soft-tissue tracking. To that end, a mathematical justification of demons Gaussian regularisation is proposed. Building on this result, we replace the Gaussian smoothing by an efficient elastic-like regulariser based on isotropic differential quadratic forms of vector fields. The registration energy functional is finally minimised under the divergence-free constraint to get incompressible deformations. As the elastic regulariser and the constraint are linear, the method remains computationally tractable and easy to implement. Tests on synthetic incompressible deformations showed that our approach outperforms the original logDemons in terms of elastic incompressible deformation recovery without reducing the image matching accuracy. As an application, we applied the proposed algorithm to estimate 3D myocardium strain on clinical cine MRI of two adult patients. Results showed that incompressibility constraint improves the cardiac motion recovery when compared to the ground truth provided by 3D tagged MRI.     

Transporting Deformations of Face Emotions in the Shape Spaces: A Comparison of Different Approaches

Studying the changes of shape is a common concern in many scientific fields. We address here two problems: (1) quantifying the deformation between two given shapes and (2) transporting this deformation to morph a third shape. These operations can be done with or without point correspondence, depending on the availability of a surface matching algorithm, and on the type of mathematical procedure adopted. In computer vision, the re-targeting of emotions mapped on faces is a common application. We contrast here four different methods used for transporting the deformation toward a target once it was estimated upon the matching of two shapes. These methods come from very different fields such as computational anatomy, computer vision and biology. We used the large diffeomorphic deformation metric mapping and thin plate spline, in order to estimate deformations in a deformational trajectory of a human face experiencing different emotions. Then we use naive transport (NT), linear shift (LS), direct transport (DT) and fanning scheme (FS) to transport the estimated deformations toward four alien faces constituted by 240 homologous points and identifying a triangulation structure of 416 triangles. We used both local and global criteria for evaluating the performance of the 4 methods, e.g., the maintenance of the original deformation. We found DT, LS and FS very effective in recovering the original deformation while NT fails under several aspects in transporting the shape change. As the best method may differ depending on the application, we recommend carefully testing different methods in order to choose the best one for any specific application.