DIFFERENTIATION OF HUMAN UMBILICAL CORD MESENCHYMAL STEM CELLS INTO INSULIN PRODUCING BETA CELLS FOR DIABETIC THERAPY.
Bibliographic record
Abstract
The aim of the present study was to evaluate the potential of using human umbilical cord tissue as a source of mesenchymal stem cells to differentiate into functional pancreatic -cells. Method: Umbilical Cord Mesenchymal Stem Cells (MSCs), which have a low risk of immune rejection, were isolated, cultured in-vitro and characterized by Flowcytometry and immunocytochemistry. Further they were differentiated successfully in-vitro into functional pancreatic -cells using H-DMEM (25 mM glucose/L) supplemented with -Mercaptoethanol (0.1 mM/L), b-Fibroblast growth factor (10 g/L), Taurine (10 mM/L) and Nicotinamide (10 mM/L). Results: Umbilical cord sample of 8 cm length yielded 1.5*10 5 0.5*10 5 cells after enzymatic digestion. These were passaged to confluence and were found by Flowcytometry to be CD-73 + , CD-90 + , CD-105 + , Vimentin + , CD-34 -, CD-45 -and HLA-DR -indicating that 95% of cells were MSCs. These were differentiated for 25 days and 20% stained positive for Dithizone, which is a specific marker for pancreatic beta cells. Insulin secreted in the medium was evaluated with and without glucose stimulation. Conclusion: It is evident from this work that Umbilical cord tissue which is easily and ethically available is suitable to isolate MSCs, which have a potential to differentiate into insulin secreting -cell invitro. These differentiated cells can be placed in-vivo either by Edmonton protocol into the pancreatic duct or embedded in omentum for managing both Type-1 and Type-2 Diabetes Mellitus. This is a promising treatment option, especially since recent literature proposes that pancreatic -cell apoptosis is the underlying cause of both these pathologies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 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 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".