Dataset Information

Peripheral Delivery of Neural Precursor Cells Ameliorates Parkinson's Disease-Associated Pathology.

ABSTRACT: : Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by loss of motor control due to a wide loss of dopaminergic neurons along the nigro-striatal pathway. Some of the mechanisms that contribute to this cell death are inflammation, oxidative stress, and misfolded alpha-synuclein-induced toxicity. Current treatments are effective at managing the early motor symptoms of the disease, but they become ineffective over time and lead to adverse effects. Previous research using intracerebral stem cell therapy for treatment of PD has provided promising results; however, this method is very invasive and is often associated with unacceptable side effects. In this study, we used an MPTP-injected mouse model of PD and intravenously administered neural precursors (NPs) obtained from mouse embryonic and mesenchymal stem cells. Clinical signs and neuropathology were assessed. Female mice treated with NPs had improved motor function and reduction in the neuroinflammatory response. In terms of safety, there were no tumorigenic formations or any detectable adverse effect after treatment. Our results suggest that peripheral administration of stem cell-derived NPs may be a promising and safe therapy for the recovery of impaired motor function and amelioration of brain pathology in PD.

SUBMITTER: Edwards Iii G

PROVIDER: S-EPMC6912680 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Peripheral Delivery of Neural Precursor Cells Ameliorates Parkinson's Disease-Associated Pathology.

Edwards Iii George G Gamez Nazaret N Armijo Enrique E Kramm Carlos C Morales Rodrigo R Taylor-Presse Kathleen K Schulz Paul E PE Soto Claudio C Moreno-Gonzalez Ines I

Cells 20191030 11

<b>:</b> Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by loss of motor control due to a wide loss of dopaminergic neurons along the nigro-striatal pathway. Some of the mechanisms that contribute to this cell death are inflammation, oxidative stress, and misfolded alpha-synuclein-induced toxicity. Current treatments are effective at managing the early motor symptoms of the disease, but they become ineffective over time and lead to adverse effects. Previous re ...[more]

PMID: 31671704

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Project description:The diagnosis of Parkinson's disease (PD) is challenging at all stages due to variable symptomatology, comorbidities, and mimicking conditions. Postmortem assessment remains the gold standard for a definitive diagnosis. While it is well recognized that PD manifests pathologically in the central nervous system with aggregation of α-synuclein as Lewy bodies and neurites, similar Lewy-type synucleinopathy (LTS) is additionally found in the peripheral nervous system that may be useful as an antemortem biomarker. We have previously found that detection of LTS in submandibular gland (SMG) biopsies is sensitive and specific for advanced PD; however, the sensitivity is suboptimal especially for early-stage disease. Further, visual microscopic assessment of biopsies by a neuropathologist to identify LTS is impractical for large-scale adoption. Here, we trained and validated a convolutional neural network (CNN) for detection of LTS on 283 digital whole slide images (WSI) from 95 unique SMG biopsies. A total of 8,450 LTS and 35,066 background objects were annotated following an inter-rater reliability study with Fleiss Kappa = 0.72. We used transfer learning to train a CNN model to classify image patches (151 × 151 pixels at 20× magnification) with and without the presence of LTS objects. The trained CNN model showed the following performance on image patches: sensitivity: 0.99, specificity: 0.99, precision: 0.81, accuracy: 0.99, and F-1 score: 0.89. We further tested the trained network on 1230 naïve WSI from the same cohort of research subjects comprising 42 PD patients and 14 controls. Logistic regression models trained on features engineered from the CNN predictions on the WSI resulted in sensitivity: 0.71, specificity: 0.65, precision: 0.86, accuracy: 0.69, and F-1 score: 0.76 in predicting clinical PD status, and 0.64 accuracy in predicting PD stage, outperforming expert neuropathologist LTS density scoring in terms of sensitivity but not specificity. These findings demonstrate the practical utility of a CNN detector in screening for LTS, which can translate into a computational tool to facilitate the antemortem tissue-based diagnosis of PD in clinical settings.

Dataset Information

Peripheral Delivery of Neural Precursor Cells Ameliorates Parkinson's Disease-Associated Pathology.

Publications

Peripheral Delivery of Neural Precursor Cells Ameliorates Parkinson's Disease-Associated Pathology.

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