Extracellular vesicles derived from human Wharton’s jelly mesenchymal stem cells protect hippocampal neurons from oxidative stress and synapse damage induced by amyloid-β oligomers
Bibliographic record
Abstract
BACKGROUND: Mesenchymal stem cells (MSCs) have been explored as promising tools for treatment of several neurological and neurodegenerative diseases. MSCs release abundant extracellular vesicles (EVs) containing a variety of biomolecules, including mRNAs, miRNAs, and proteins. We hypothesized that EVs derived from human Wharton's jelly would act as mediators of the communication between hMSCs and neurons and could protect hippocampal neurons from damage induced by Alzheimer's disease-linked amyloid beta oligomers (AβOs). METHODS: We isolated and characterized EVs released by human Wharton's jelly mesenchymal stem cells (hMSC-EVs). The neuroprotective action of hMSC-EVs was investigated in primary hippocampal cultures exposed to AβOs. RESULTS: hMSC-EVs were internalized by hippocampal cells in culture, and this was enhanced in the presence of AβOs in the medium. hMSC-EVs protected hippocampal neurons from oxidative stress and synapse damage induced by AβOs. Neuroprotection by hMSC-EVs was mediated by catalase and was abolished in the presence of the catalase inhibitor, aminotriazole. CONCLUSIONS: hMSC-EVs protected hippocampal neurons from damage induced by AβOs, and this was related to the transfer of enzymatically active catalase contained in EVs. Results suggest that hMSC-EVs should be further explored as a cell-free therapeutic approach to prevent neuronal damage in Alzheimer's disease.
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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 | 0.001 |
| 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) | 0.001 | 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".