Collar occupancy: A new quantitative imaging tool for morphometric analysis of oligodendrocytes

Myelin detection in fluorescence microscopy images using machine learning

BACKGROUND

The myelin sheath produced by glial cells insulates the axons, and supports the function of the nervous system. Myelin sheath degeneration causes neurodegenerative disorders, such as multiple sclerosis (MS). There are no therapies for MS that promote remyelination. Drug discovery frequently involves screening thousands of compounds. However, this is not feasible for remyelination drugs, since myelin quantification is a manual labor-intensive endeavor. Therefore, the development of assistive software for expedited myelin detection is instrumental for MS drug discovery by enabling high-content image-based drug screens.

NEW METHOD

In this study, we developed a machine learning based expedited myelin detection approach in fluorescence microscopy images. Multi-channel three-dimensional microscopy images of a mouse stem cell-based myelination assay were labeled by experts. A spectro-spatial feature extraction method was introduced to represent local dependencies of voxels both in spatial and spectral domains. Feature extraction yielded two data set of over forty-seven thousand annotated images in total.

RESULTS

Myelin detection performances of 23 different supervised machine learning techniques including a customized-convolutional neural network (CNN), were assessed using various train/test split ratios of the data sets. The highest accuracy values of 98.84±0.09% and 98.46±0.11% were achieved by Boosted Trees and customized-CNN, respectively.

COMPARISON WITH EXISTING METHODS

Our approach can detect myelin in a common experimental setup. Myelin extending in any orientation in 3 dimensions is segmented from 3 channel z-stack fluorescence images.

CONCLUSIONS

Our results suggest that the proposed expedited myelin detection approach is a feasible and robust method for remyelination drug screening.

Glial restricted precursor cells in central nervous system disorders: Current applications and future perspectives

The crosstalk between glial cells and neurons represents an exceptional feature for maintaining the normal function of the central nervous system (CNS). Increasing evidence has revealed the importance of glial progenitor cells in adult neurogenesis, reestablishment of cellular pools, neuroregeneration, and axonal (re)myelination. Several types of glial progenitors have been described, as well as their potentialities for recovering the CNS from certain traumas or pathologies. Among these precursors, glial-restricted precursor cells (GRPs) are considered the earliest glial progenitors and exhibit tripotency for both Type I/II astrocytes and oligodendrocytes. GRPs have been derived from embryos and embryonic stem cells in animal models and have maintained their capacity for self-renewal. Despite the relatively limited knowledge regarding the isolation, characterization, and function of these progenitors, GRPs are promising candidates for transplantation therapy and reestablishment/repair of CNS functions in neurodegenerative and neuropsychiatric disorders, as well as in traumatic injuries. Herein, we review the definition, isolation, characterization and potentialities of GRPs as cell-based therapies in different neurological conditions. We briefly discuss the implications of using GRPs in CNS regenerative medicine and their possible application in a clinical setting. MAIN POINTS: GRPs are progenitors present in the CNS with differentiation potential restricted to the glial lineage. These cells have been employed in the treatment of a myriad of neurodegenerative and traumatic pathologies, accompanied by promising results, herein reviewed.