Deferoxamine promotes mesenchymal stem cell homing in noise‐induced injured cochlea through <scp>PI</scp>3K/<scp>AKT</scp> pathway
Bibliographic record
Abstract
OBJECTIVE: Over 5% of the world's population suffers from disabling hearing loss. Stem cell homing in target tissue is an important aspect of cell-based therapy, which its augmentation increases cell therapy efficiency. Deferoxamine (DFO) can induce the Akt activation, and phosphorylation status of AKT (p-AKT) upregulates CXC chemokine receptor-4 (CXCR4) expression. We examined whether DFO can enhance mesenchymal stem cells (MSCs) homing in noise-induced damaged cochlea by PI3K/AKT dependent mechanism. MATERIALS AND METHODS: Mesenchymal stem cells were treated with DFO. AKT, p-AKT protein and hypoxia inducible factor 1- α (HIF-1α) and CXCR4 gene and protein expression was evaluated by RT- PCR and Western blot analysis. For in vivo assay, rats were assigned to control, sham, noise exposure groups without any treatment or receiving normal, DFO-treated and DFO +LY294002 (The PI3K inhibitor)-treated MSCs. Following chronic exposure to 115 dB white noise, MSCs were injected into the rat cochlea through the round window. Number of Hoechst- labelled cells was determined in the endolymph after 24 hours. RESULTS: Deferoxamine increased P-AKT, HIF-1α and CXCR4 expression in MSCs compared to non-treated cells. DFO pre-conditioning significantly increased the homing ability of MSCs into injured ear compared to normal MSCs. These effects of DFO were blocked by LY294002. CONCLUSIONS: Pre-conditioning of MSCs by DFO before transplantation can improve stem cell homing in the damaged cochlea through PI3K/AKT pathway activation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".