After the storm: an objective appraisal of the efficacy of c-kit+ cardiac progenitor cells in preclinical models of heart disease
Bibliographic record
Abstract
The falsification of data related to c-kit+ cardiac progenitor cells (CPCs) by a Harvard laboratory has been a veritable tragedy. Does this fraud mean that CPCs are not beneficial in models of ischemic cardiomyopathy? At least 50 studies from 26 laboratories independent of the Harvard group have reported beneficial effects of CPCs in mice, rats, pigs, and cats. The mechanism of action remains unclear. Our group has shown that CPCs do not engraft in the diseased heart, do not differentiate into new cardiac myocytes, do not regenerate dead myocardium, and thus work via paracrine mechanisms. A casualty of the misconduct at Harvard has been the SCIPIO trial, a collaboration between the Harvard group and the group in Louisville. The retraction of the SCIPIO paper was caused exclusively by issues with data generated at Harvard, not those generated in Louisville. In the retraction notice, the Lancet editors stated: “Although we do not have any reservations about the clinical work in Louisville that used the preparations from Anversa's laboratory in good faith, the lack of reliability regarding the laboratory work at Harvard means that we are now retracting this paper”. We must be careful not to dismiss all work on CPCs because of one laboratory’s misconduct. An unbiased review of the literature supports the therapeutic potential of CPCs for heart failure at the preclinical level.
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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 | 0.036 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".