Adipose mesenchymal stem cells-derived extracellular vesicles exert their preferential action in damaged central sites of SOD1 mice rather than peripherally
Bibliographic record
Abstract
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder involving motor neuron (MN) loss in the motor cortex, brainstem and spinal cord leading to progressive paralysis and death. Due to the pathogenetic complexity, there are no effective therapies available. In this context the use of mesenchymal stem cells and their vesicular counterpart is an emerging therapeutic strategy to counteract neurodegeneration. The extracellular vesicles derived from adipose stem cells (ASC-EVs) recapitulate and ameliorate the neuroprotective effect of stem cells and, thanks to their small dimensions, makes their use suitable to develop novel therapeutic approaches for neurodegenerative diseases as ALS. Here we investigate a therapeutic regimen of ASC-EVs injection in SOD1(G93A) mice, the most widely used murine model of ALS. Repeated intranasal administrations of high doses of ASC-EVs were able to ameliorate motor performance of injected SOD1(G93A) mice at the early stage of the disease and produce a significant improvement at the end-stage in the lumbar MNs rescue. Moreover, ASC-EVs preserve the structure of neuromuscular junction without counteracting the muscle atrophy. The results indicate that the intranasal ASC-EVs administration acts in central nervous system sites rather than at peripheral level in SOD1(G93A) mice. These considerations allow us to identify future applications of ASC-EVs that involve different targets simultaneously to maximize the clinical and neuropathological outcomes in ALS in vivo models.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".