Abstract 12016: An Enhanced Collagen-Based Matrix Promotes Cardiomyocytic Differentiation of Embryonic Stem Cells
Bibliographic record
Abstract
Background: Previous studies have incorporated the oligosaccharide sialyl Lewis X (sLe X ) into an injectable collagen matrix for regeneration of ischemic muscle. It was hypothesized that this material may support differentiation of progenitors towards a cardiac lineage. This study sought to characterize its elastic and hydropolar properties that are conducive towards myogenesis, and its potential for generating cardiomyocytes. Methods: Elastic moduli and water contact angles (WCA) of matrices were measured. Mouse embryonic bodies were cultured on: 1) collagen matrix; or, 2) sLe X -collagen matrix; and compared to 3) tissue culture plastic substrate (TCPS) controls. After 15 days, cells were harvested and analyzed for cardiac markers using immunofluorescence, qPCR and Western blotting. Results: Collagen matrices did not produce a detectable WCA, but incorporation of sLe X reliably produced regions with WCA of P =0.9); values ranged from 9.0-19.9kPa, which supports maximal myogenic differentiation. L-Selectin, the receptor for sLe X , was expressed in cells from days 0 to 15, indicating potential interaction with the sLe X -collagen matrix. Spontaneously beating cells were observed on all substrates. At day 15, cells on both collagen and sLe X -collagen matrices had greater expression of cardiac myogenesis markers GATA4 (1.8-fold; P P X -matrix culture induced increased transcription of cardiac markers Nkx2.5 (2.3-fold; P =0.009) and atrial natriuretic factor (3.1-fold; P =0.02) in cells, compared to TCPS. Immunofluorescence demonstrated a greater presence of cardiac α-actinin on the sLe X -collagen matrix. Conclusions: These results demonstrate that the physical properties of the sLe X -collagen matrix are optimal for myogenesis. In addition to having regenerative effects in vivo , these injectable materials may be useful for generating functional cardiomyocytes for transplantation, without the need for genetic or viral manipulation.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".