Generation of Insulin Producing Cells using Mesenchymal Stem Cells Derived from Bone Marrow of New-Zealand White Rabbits
Bibliographic record
Abstract
Background: The utilization of stem cell trans-differentiation into insulin-producing cells (IPCs) would provide potential promising therapy for diabetes mellitus (DM). Objective: The study was aimed to investigate the differentiation potential of rabbit’s bone marrowderived cells into insulin producing cells. Methods: Bone marrow-derived mesenchymal stem cells (MSCs) were obtained from three New-Zealand male white rabbits and propagated in a primary culture for 14 days in low glucose Dulbecco's Modified Eagle's Medium (DMEM), harvested and subjected to another three passages encompassing 21 days. After that, MSCs were functionally defined by their ability to differentiate into osteoblasts. This was achieved by incubation with the DMEM containing 10 -7 M dexamethasone, 10 mM βglycerophosphate and 50 μl/ml of ascorbic acid. Osteogenic differentiation was followed up at days 2, 4, 7 and 9 by staining cells with alizarin red S and vonKossa. Results: It was found that the onset of differentiation was at day 7 and continued at day 9. On the other hand, another patch of MSCs were induced into insulin-producing cells by two step incubation. The first with high glucose serum-free DMEM containing 0.5 mmol/L β-mercaptoethanol for three days and the second follows by incubation with the same medium containing 10 mmol/L nicotinamideinstead of β-mercaptoethanolfor 18 days. Trans-differentiation was followed up at days 4, 9, 14 and 21. It was found that the cells have trans-differentiated into insulin-producing cells starting from day 14 and continued in the subsequent days as judged by their affinity to stain with diphenylthiocarbazone (dithizone or DTZ) at days 14 and 21. Conclusion: The results would provide some insights of using rabbit's bone marrow as a source of MSCs with their differentiation potentials. This might help for the development of a future stem cell therapy for diabetes as well as several other human diseases.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 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".