Application of Three-Dimensional Culture Method in the Cardiac Conduction System Research
Bibliographic record
Abstract
Congenital heart defects (CHD) are the most common type of birth defects. Several human case studies and genetically altered animal models have identified abnormalities in the development of ventricular conduction system (VCS) in the heart. While cell-based therapies hold promise for treating CHDs, translational efforts are limited by the lack of suitable in vitro models for feasibility and safety studies. A better understanding of cell differentiation pathways can lead to development of cell-based therapies for individuals living with CHD/VCS disorders. Here, we describe a new and reproducible 3-D cell culture method for studying cardiac cell lineage differentiation in vitro. We used primary ventricular cells isolated from embryonic day 11.5 (E11.5) mouse embryos, which can differentiate into multiple cardiac cell types including VCS cells. We compared 3-D cultures with three types of basement membrane extracts (BME) for their abilities to support E11.5 ventricular cell differentiation. In addition, the effects of atrial natriuretic peptide (ANP) and an inhibitor for its high affinity receptor were tested on cell differentiation in 3-D cultures. Following the cell culture, protocols for immunofluorescence imaging, cell extraction and protein isolation from the 3-D culture matrix and in-cell western methods are described. Further, these approaches can be used to study the effects of various ligands and genetic interventions on VCS cell development. We propose that these methodologies may also be extended for differentiation studies using other sources of stem cells such as induced pluripotent stem cells.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".