Dynamic imaging of individual remyelination profiles in multiple sclerosis

Background Quantitative in vivo imaging of myelin loss and repair in patients with multiple sclerosis (MS) is essential to understand the pathogenesis of the disease and to evaluate promyelinating therapies. Selectively binding myelin in the central nervous system white matter, Pittsburgh compound B ([11C]PiB) can be used as a positron emission tomography (PET) tracer to explore myelin dynamics in MS. Methods Patients with active relapsing-remitting MS (n = 20) and healthy controls (n = 8) were included in a longitudinal trial combining PET with [11C]PiB and magnetic resonance imaging. Voxel-wise maps of [11C]PiB distribution volume ratio, reflecting myelin content, were derived. Three dynamic indices were calculated for each patient: the global index of myelin content change; the index of demyelination; and the index of remyelination. Results At baseline, there was a progressive reduction in [11C]PiB binding from the normal-appearing white matter to MS lesions, reflecting a decline in myelin content. White matter lesions were characterized by a centripetal decrease in the tracer binding at the voxel level. During follow-up, high between-patient variability was found for all indices of myelin content change. Dynamic remyelination was inversely correlated with clinical disability (p = 0.006 and beta-coefficient = -0.67 with the Expanded Disability Status Scale; p = 0.003 and beta-coefficient = -0.68 with the MS Severity Scale), whereas no significant clinical correlation was found for the demyelination index. Interpretation [11C]PiB PET allows quantification of myelin dynamics in MS and enables stratification of patients depending on their individual remyelination potential, which significantly correlates with clinical disability. This technique should be considered to assess novel promyelinating drugs. Ann Neurol 2016;79:726-73

Thalamic energy dysfunction is associated with thalamo-cortical tract damage in multiple sclerosis: a diffusion spectroscopy study

Background: Diffusion-weighted 1H magnetic resonance spectroscopy (DW-MRS) allows to quantify creatine-phosphocreatine brain diffusivity (ADC(tCr)), whose reduction in multiple sclerosis (MS) has been proposed as a proxy of energy dysfunction. Objective: To investigate whether thalamic ADC(tCr) changes are associated with thalamo-cortical tract damage in MS. Methods: Twenty patients with MS and 13 healthy controls (HC) were enrolled in a DW-MRS and DW imaging (DWI) study. From DW-MRS, ADC(tCr) and total N-acetyl-aspartate diffusivity (ADC(tNAA)) were extracted in the thalami. Three thalamo-cortical tracts and one non-thalamic control tract were reconstructed from DWI. Fractional anisotropy (FA), mean (MD), axial (AD), and radial diffusivity (RD), reflecting microstructural integrity, were extracted for each tract. Associations between thalamic ADC(tCr) and tract metrics were assessed using linear regression models adjusting for age, sex, thalamic volume, thalamic ADC(tNAA), and tract-specific lesion load. Results: Lower thalamic ADC(tCr) was associated with higher MD and RD of thalamo-cortical projections in MS (MD: p = 0.029; RD: p = 0.017), but not in HC (MD: p = 0.625, interaction term between thalamic ADC(tCr) and group = 0.019; RD: p = 0.320, interaction term = 0.05). Thalamic ADC(tCr) was not associated with microstructural changes of the control tract. Conclusion: Reduced thalamic ADC(tCr) correlates with thalamo-cortical tract damage in MS, showing that pathologic changes in thalamic energy metabolism are associated with structural degeneration of connected fibers

A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications.

RNA sequencing (RNA-seq) is a genomic approach for the detection and quantitative analysis of messenger RNA molecules in a biological sample and is useful for studying cellular responses. RNA-seq has fueled much discovery and innovation in medicine over recent years. For practical reasons, the technique is usually conducted on samples comprising thousands to millions of cells. However, this has hindered direct assessment of the fundamental unit of biology-the cell. Since the first single-cell RNA-sequencing (scRNA-seq) study was published in 2009, many more have been conducted, mostly by specialist laboratories with unique skills in wet-lab single-cell genomics, bioinformatics, and computation. However, with the increasing commercial availability of scRNA-seq platforms, and the rapid ongoing maturation of bioinformatics approaches, a point has been reached where any biomedical researcher or clinician can use scRNA-seq to make exciting discoveries. In this review, we present a practical guide to help researchers design their first scRNA-seq studies, including introductory information on experimental hardware, protocol choice, quality control, data analysis and biological interpretation

A multimodal cell census and atlas of the mammalian primary motor cortex

ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties

Monte Carlo construction of Karhunen-Loeve expansion for non Gaussian random fields

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Numerical simulation of homogeneous and inhomogeneous Gaussian stochastic vector fields

International audienceThe first part of this paper presents a numerical simulation method for homogeneous and inhomogeneous Gaussain vector fields. The convergence properties of the method are studied in detail as these are the only criteria for guaranteeing the quality of the silumated paths and hence the representativity of the simulation compared with the probabilistic model. Numerical simulation formulae are given explicitly in the first part. In the second part, an example is given of a velocity field simulation of atmospheric turbulence, as modeled by an isotropic homogeneous Gaussain field and by an inhomogeneous Gaussain field