Olfactory mucosa stem cells: An available candidate for the treatment of the Parkinson's disease
Bibliographic record
Abstract
Olfactory ectomesenchymal stem cells (OE-MSCs) possess the immunosuppressive activity and regeneration capacity and hold a lot of promises for neurodegenerative disorders treatment. This study aimed to determine OE-MSCs which are able to augment and differentiate into functional neurons and regenerate the CNS and also examine whether the implantation of OE-MSCs in the pars compacta of the substantia nigra (SNpc) can improve Parkinson's symptoms in a rat model-induced with 6-hydroxydopamine. We isolated OE-MSCs from lamina propria in olfactory mucosa and characterized them using flow cytometry and immunocytochemistry. The therapeutic potential of OE-MSCs was evaluated by the transplantation of isolated cells using a rat model of acute SN injury as a Parkinson's disease. Significant behavioral improvement in Parkinsonian rats was elicited by the OE-MSCs. The results demonstrate that the expression of PAX2, PAX5, PITX3, dopamine transporter, and tyrosine hydroxylase was increased by OE-MSCs compared to the control group which is analyzed with real-time polymerase chain reaction technique and immunohistochemical staining. In the outcome, the transplantation of 1,1'-dioctadecyl-3,3,3'3'-tetramethyl indocarbocyanine perchlorate labeled OE-MSCs that were fully differentiated to dopaminergic neurons contribute to a substantial improvement in patients with Parkinson's. Together, our results provide that using OE-MSCs in neurodegenerative disorders might lead to better neural regeneration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".