Epidermal Growth Factor and Perlecan Fragments Produced by Apoptotic Endothelial Cells Co-Ordinately Activate ERK1/2-Dependent Antiapoptotic Pathways in Mesenchymal Stem Cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mounting evidence indicates that mesenchymal stem cells (MSC) are pivotal to vascular repair and neointima formation in various forms of vascular disease. Yet, the mechanisms that allow MSC to resist apoptosis at sites where other cell types, such as endothelial cells (EC), are dying are not well defined. In the present work, we demonstrate that apoptotic EC actively release paracrine mediators which, in turn, inhibit apoptosis of MSC. Serum-free medium conditioned by apoptotic EC increases extracellular signal-regulated kinases 1 and 2 (ERK1/2) activation and inhibits apoptosis (evaluated by Bcl-xL protein levels and poly (ADP-ribose) polymerase cleavage) of human MSC. A C-terminal fragment of perlecan (LG3) released by apoptotic EC is one of the mediators activating this antiapoptotic response in MSC. LG3 interacts with beta1-integrins, which triggers downstream ERK1/2 activation in MSC, albeit to a lesser degree than medium conditioned by apoptotic EC. Hence, other mediators released by apoptotic EC are probably required for induction of the full antiapoptotic phenotype in MSC. Adopting a comparative proteomic strategy, we identified epidermal growth factor (EGF) as a novel mediator of the paracrine component of the endothelial apoptotic program. LG3 and EGF cooperate in triggering beta1-integrin and EGF receptor-dependent antiapoptotic signals in MSC centering on ERK1/2 activation. The present work, providing novel insights into the mechanisms facilitating the survival of MSC in a hostile environment, identifies EGF and LG3 released by apoptotic EC as central antiapoptotic mediators involved in this paracrine response.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it