Characterization of Stem Cells From Pulp Tissue of Exfoliated Deciduous Teeth, Impacted Third Molars and Apical Papilla of Impacted Third Molars With Open Apices: A Comparative Analysis
Bibliographic record
Abstract
Background and Objective: Mesenchymal stem cells (MSCs) from many different dental tissues have enormous potential in tissue regeneration and immunotherapy. MSCs isolated and cultured in many different ways are known for their heterogenecity expressed through multiple phenotypes which in turn may reflect their distinct functional properties; it is important to analyze and compare the characteristics of each cell lines cultured. The objective of this study is to isolate MSCs from 3 different sources and analyze and compare their morphological and phenotypic characteristics. Materials and Methods: The samples were collected and mononuclear cells were isolated using enzymatic digestion method and the adherent cell cultures were maintained till passage 3 and the harvested cells were analyzed for different phenotypic markers such as CD34, CD45, CD29, CD105, CD73, CD90, SOX2, OCT3/4, and neuroectodermal stem cell marker (NESTIN). The comparative statistical analysis of characterized cells was done by standard deviation methods using SPSS software (Canada). Results: Our study was successful in isolation, culture, and characterization of stem cells from all the mentioned 3 sources. All established cultures were more than 95% positive for mesenchymal markers and less than 5% positive for hematopoietic markers. The cells also expressed pluripotency markers and neural markers. Further, the comparison of mean positive expressions among the groups using analysis of variance showed the different significance levels of expression of different markers in groups. Conclusion: MSCs from different sources show promising expression of different markers; therefore, it can be concluded that cells isolated from dental sources can be used for treating various neurodegenerative diseases in the future.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".