IGF-1 Mediated Neuroprotective Effects of Olfactory-Derived Mesenchymal Stem Cells on Auditory Hair Cells
Bibliographic record
Abstract
IMPORTANCE: Mesenchymal stem cells (MSCs) have the capability of providing ongoing paracrine support to degenerating tissues. Since MSCs can be extracted from a broad range of tissues, their specific surface marker profiles and growth factor secretions can be different. We hypothesized that MSCs derived from different sources might also have different neuroprotective potential. OBJECTIVE: In this study, we extracted MSCs from rodent olfactory mucosa and compared their neuroprotective effects on auditory hair cell survival with MSCs extracted from rodent adipose tissue. METHODS: Organ of Corti explants were dissected from 41 cochlea and incubated with olfactory mesenchymal stem cells (OMSCs) and adipose mesenchymal stem cells (AMSCs). After 72 hours, Corti explants were fixed, stained, and hair cells counted. Growth factor concentrations were determined in the supernatant and cell lysate using Enzyme-Linked Immunosorbent Assay (ELISA). RESULTS: Co-culturing of organ of Corti explants with OMSCs resulted in a significant increase in inner and outer hair cell stereocilia survival, compared to control. Comparisons between both stem cell lines, showed that co-culturing with OMSCs resulted in superior inner and outer hair cell stereocilia survival rates over co-culturing with AMSCs. Assessment of growth factor secretions revealed that the OMSCs secrete significant amounts of insulin-like growth factor 1 (IGF-1). Co-culturing OMSCs with organ of Corti explants resulted in a 10-fold increase in IGF-1 level compared to control, and their secretion was 2 to 3 times higher compared to the AMSCs. CONCLUSIONS: This study has shown that OMSCs may mitigate auditory hair cell stereocilia degeneration. Their neuroprotective effects may, at least partially, be ascribed to their enhanced IGF-1 secretory abilities compared to AMSCs.
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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) | 0.000 | 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) | 0.001 | 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".