Impact of the Secretome of Human Mesenchymal Stem Cells on Brain Structure and Animal Behavior in a Rat Model of Parkinson's Disease
Bibliographic record
Abstract
Research in the last decade strongly suggests that mesenchymal stem cell (MSC)-mediated therapeutic benefits are mainly due to their secretome, which has been proposed as a possible therapeutic tool for the treatment of Parkinson's disease (PD). Indeed, it has been shown that the MSC secretome increases neurogenesis and cell survival, and has numerous neuroprotective actions under different conditions. Additionally, using dynamic culturing conditions (through computer-controlled bioreactors) can further modulate the MSC secretome, thereby generating a more potent neurotrophic factor cocktail (i.e., conditioned medium). In this study, we have characterized the MSC secretome by proteomic-based analysis, investigating its therapeutic effects on the physiological recovery of a 6-hydroxidopamine (6-OHDA) PD rat model. For this purpose, we injected MSC secretome into the substantia nigra (SNc) and striatum (STR), characterizing the behavioral performance and determining histological parameters for injected animals versus untreated groups. We observed that the secretome potentiated the increase of dopaminergic neurons (i.e., tyrosine hydroxylase-positive cells) and neuronal terminals in the SNc and STR, respectively, thereby supporting the recovery observed in the Parkinsonian rats' motor performance outcomes (assessed by rotarod and staircase tests). Finally, proteomic characterization of the MSC secretome (through combined mass spectrometry analysis and Bioplex assays) revealed the presence of important neuroregulatory molecules, namely cystatin C, glia-derived nexin, galectin-1, pigment epithelium-derived factor, vascular endothelial growth factor, brain-derived neurotrophic factor, interleukin-6, and glial cell line-derived neurotrophic factor. Overall, we concluded that the use of human MSC secretome alone was able to partially revert the motor phenotype and the neuronal structure of 6-OHDA PD animals. This indicates that the human MSC secretome could represent a novel therapeutic for the treatment of PD. Stem Cells Translational Medicine 2017;6:634-646.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".