Drawing Inspiration from Developmental Biology for Cardiac Tissue Engineers
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
A sound understanding of developmental biology is part of the foundation of effective stem cell-derived tissue engineering. Here, the key concepts of cardiac development that are successfully applied in a bioinspired approach to growing engineered cardiac tissues, are reviewed. The native cardiac milieu is studied extensively from embryonic to adult phenotypes, as it provides a resource of factors, mechanisms, and protocols to consider when working toward establishing living tissues in vitro. It begins with the various cell types that constitute the cardiac tissue. It is discussed how myocytes interact with other cell types and their microenvironment and how they change over time from the embryonic to the adult states, with a view on how such changes affect the tissue function and may be used in engineered tissue models. Key embryonic signaling pathways that have been leveraged in the design of culture media and differentiation protocols are presented. The cellular microenvironment, from extracellular matrix chemical and physical properties, to the dynamic mechanical and electrical forces that are exerted on tissues is explored. It is shown that how such microenvironmental factors can inform the design of biomaterials, scaffolds, stimulation bioreactors, and maturation readouts, and suggest considerations for ongoing biomimetic advancement of engineered cardiac tissues and regeneration strategies for the future.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 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 it