3D Co-culture Model on the Role of Vimentin in Notch Signaling and Vascularization
Bibliographic record
Abstract
Abstract The Notch signaling pathway is a conserved pathway that is central in vascular tissue development and pathology. Because this pathway controls such important events, it is regulated at multiple steps of its cascade, such as post-translational modification of its ligand and receptor. Recent studies have suggested regulation of the Notch signaling by a pulling force to be required to activate Notch signaling. In this exploratory study, 3D fibrin gels were used as a co-culture system of endothelial cells and 10T1/2 cells to assess whether vimentin is implicated in the regulation of Notch signaling and neovascularization. The results show that 10T1/2 cells increase the expression of Hes-1, Hes-5, and Acta2 during co-culture with human coronary artery endothelial cells (HCAECs) and that vimentin knock-down using siRNA partially reduced the expression under static conditions. On the other hand, while the same trend was observed for Hes-5 under dynamic conditions, Acta2 was overexpressed, and vimentin knock-down did not affect its expression levels. Moreover, the development of newly formed micro-vessels is observed in 3D fibrin gels in the presence of VEGF but could not be formed when vimentin expression was knocked down. These results suggest that vimentin plays a secondary role in Notch signaling; however, it is essential for neovascularization.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".