Dataset Information

Neural Stem Cell Grafts Form Extensive Synaptic Networks that Integrate with Host Circuits after Spinal Cord Injury.

ABSTRACT: Neural stem/progenitor cell (NSPC) grafts can integrate into sites of spinal cord injury (SCI) and generate neuronal relays across lesions that can provide functional benefit. To determine if and how grafts become synaptically organized and connect with host systems, we performed calcium imaging of NSPC grafts in SCI sites in vivo and in adult spinal cord slices. NSPC grafts organize into localized and spontaneously active synaptic networks. Optogenetic stimulation of host corticospinal tract axons regenerating into grafts elicited distinct and segregated neuronal network responses throughout the graft. Moreover, optogenetic stimulation of graft-derived axons extending from the graft into the denervated spinal cord also triggered local host neuronal network responses. In vivo imaging revealed that behavioral stimulation likewise elicited focal synaptic responses within grafts. Thus neural progenitor grafts can form functional synaptic subnetworks whose activity patterns resemble intact spinal cord.

SUBMITTER: Ceto S

PROVIDER: S-EPMC7484050 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Neural Stem Cell Grafts Form Extensive Synaptic Networks that Integrate with Host Circuits after Spinal Cord Injury.

Ceto Steven S Sekiguchi Kohei J KJ Takashima Yoshio Y Nimmerjahn Axel A Tuszynski Mark H MH

Cell stem cell 20200805 3

Neural stem/progenitor cell (NSPC) grafts can integrate into sites of spinal cord injury (SCI) and generate neuronal relays across lesions that can provide functional benefit. To determine if and how grafts become synaptically organized and connect with host systems, we performed calcium imaging of NSPC grafts in SCI sites in vivo and in adult spinal cord slices. NSPC grafts organize into localized and spontaneously active synaptic networks. Optogenetic stimulation of host corticospinal tract ax ...[more]

PMID: 32758426

Similar Datasets

Project description:Based on DNA-methylation, ependymomas growing in the spinal cord comprise two major molecular types termed spinal (SP-EPN) and myxopapillary ependymomas (MPE(-A/B)), which differ with respect to their clinical features and prognosis. Due to the existing discrepancy between histomorphogical diagnoses and classification using methylation data, we asked whether deep neural networks can predict the DNA methylation class of spinal cord ependymomas from hematoxylin and eosin stained whole-slide images. Using explainable AI, we further aimed to prospectively improve the consistency of histology-based diagnoses with DNA methylation profiling by identifying and quantifying distinct morphological patterns of these molecular ependymoma types. We assembled a case series of 139 molecularly characterized spinal cord ependymomas (nMPE = 84, nSP-EPN = 55). Self-supervised and weakly-supervised neural networks were used for classification. We employed attention analysis and supervised machine-learning methods for the discovery and quantification of morphological features and their correlation to the diagnoses of experienced neuropathologists. Our best performing model predicted the DNA methylation class with 98% test accuracy and used self-supervised learning to outperform pretrained encoder-networks (86% test accuracy). In contrast, the diagnoses of neuropathologists matched the DNA methylation class in only 83% of cases. Domain-adaptation techniques improved model generalization to an external validation cohort by up to 22%. Statistically significant morphological features were identified per molecular type and quantitatively correlated to human diagnoses. The approach was extended to recently defined subtypes of myxopapillary ependymomas (MPE-(A/B), 80% test accuracy). In summary, we demonstrated the accurate prediction of the DNA methylation class of spinal cord ependymomas (SP-EPN, MPE(-A/B)) using hematoxylin and eosin stained whole-slide images. Our approach may prospectively serve as a supplementary resource for integrated diagnostics and may even help to establish a standardized, high-quality level of histology-based diagnostics across institutions-in particular in low-income countries, where expensive DNA-methylation analyses may not be readily available.

Dataset Information

Neural Stem Cell Grafts Form Extensive Synaptic Networks that Integrate with Host Circuits after Spinal Cord Injury.

Publications

Neural Stem Cell Grafts Form Extensive Synaptic Networks that Integrate with Host Circuits after Spinal Cord Injury.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets