Immobilization of Jagged1 Enhances Vascular Smooth Muscle Cells Maturation by Activating the Notch Pathway
Bibliographic record
Abstract
In Notch signaling, the Jagged1-Notch3 ligand-receptor pairing is implicated for regulating the phenotype maturity of vascular smooth muscle cells. However, less is known about the role of Jagged1 presentation strategy in this regulation. In this study, we used bead-immobilized Jagged1 to direct phenotype control of primary human coronary artery smooth muscle cells (HCASMC), and to differentiate embryonic multipotent mesenchymal progenitor (10T1/2) cell towards a vascular lineage. This Jagged1 presentation strategy was sufficient to activate the Notch transcription factor HES1 and induce early-stage contractile markers, including smooth muscle α-actin and calponin in HCASMCs. Bead-bound Jagged1 was unable to regulate the late-stage markers myosin heavy chain and smoothelin; however, serum starvation and TGFβ1 were used to achieve a fully contractile smooth muscle cell. When progenitor 10T1/2 cells were used for Notch3 signaling, pre-differentiation with TGFβ1 was required for a robust Jagged1 specific response, suggesting a SMC lineage commitment was necessary to direct SMC differentiation and maturity. The presence of a magnetic tension force to the ligand-receptor complex was evaluated for signaling efficacy. Magnetic pulling forces downregulated HES1 and smooth muscle α-actin in both HCASMCs and progenitor 10T1/2 cells. Taken together, this study demonstrated that (i) bead-bound Jagged1 was sufficient to activate Notch3 and promote SMC differentiation/maturation and (ii) magnetic pulling forces did not activate Notch3, suggesting the bead alone was able to provide necessary clustering or traction forces for Notch activation. Notch is highly context-dependent; therefore, these findings provide insights to improve biomaterial-driven Jagged1 control of SMC behavior.
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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 | 0.000 | 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 | 0.000 |
| 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".