Isolation of human explant derived cardiac stem cells from cryopreserved heart tissue
Bibliographic record
Abstract
The value of preserving high quality bio specimens for fundamental research is significant as linking cellular and molecular changes to clinical and epidemiological data has fueled many recent advances in medicine. Unfortunately, storage of traditional biospecimens is limited to fixed samples or isolated genetic material. Here, we report the effect of cryopreservation of routine myocardial biopsies on explant derived cardiac stem cell (EDC) culture outcomes. We demonstrate that immediate cryopreservation or delayed cryopreservation after suspension within cardioplegia for 12 hours did not alter EDC yields, proliferative capacity, antigenic phenotype or paracrine signature. Cryopreservation had negligible effects on the ability of EDCs to adopt a cardiac lineage, stimulate new vessel growth, attract circulating angiogenic cells and repair injured myocardium. Finally, cryopreservation did not influence the ability of EDCs to undergo genetic reprogramming into inducible pluripotent stem cells. This study establishes a means of storing cardiac samples as a retrievable live cell source for cardiac repair or disease modeling.
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.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".