Role of Transforming Growth Factor Signalling in Marrow Stem Cell Differentiation
Bibliographic record
Abstract
Bone marrow stem cells have the ability to self renew and differentiate into a multitude of different cell types. Of the various cell potentials, the endothelial differentiation process has been the least understood due to highly context dependent methods of regulation. It was previously found that following mesodermal induction, endothelial precursors emerged in association with inhibited transforming growth factor beta (TGFβ) signalling. To better understand the role of TGFβ signalling in the differentiation process, we treated bone marrow mononuclear cells with either a TGFβ pathway inhibitor, GW788388, or exogenous activating ligand, TGFβ1, and characterized the expression levels of various cellular markers. We demonstrate that neither treatment leads directly to an endothelial phenotype. Instead, we propose a two-step process of TGFβ and bone morphogenic protein (BMP) signalling cross-talk, that could potentially be responsible for endothelial differentiation of bone marrow derived stem cells. Our ability to derive functional endothelial cells from postnatal stem cells may impact multiple fields of research, including the study of vascular regeneration and understanding the mechanisms underlying vascular disease.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".