The Effects of Ageing on Proliferation Potential, Differentiation Potential and Cell Surface Characterisation of Human Mesenchymal Stem Cells
Bibliographic record
Abstract
Mesenchymal stem cells (MSCs) have a great capacity for use in regenerative medicine and other clinical applications. However, one question creating curiosity of their use, is how they are affected by ageing. As we now live within an ageing population, the prevalence of age related disorders is increasing, so it is important to investigate how effectively MSCs from older patients can be expanded and differentiated in vitro before their use in autologous cell transplantation. This paper will look at how ageing effects proliferation potential, differentiation potential and cell surface characterisation of human mesenchymal stem cells. Keywords: Ageing, characterisation, differentiation, mesenchymal stem cells, proliferation, regenerative medicine, inner cell mass, embryonic stem, adult stem cells, muscle tissue
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".