Myometrial cells induce angiogenesis and salvage damaged myocardium
Bibliographic record
Abstract
Characteristically, uterine myometrial cells (MCs) are proliferative, inducing angiogenesis within the female reproductive organ. We evaluated whether MCs implanted into myocardium could also induce angiogenesis and restore heart function after injury. MCs were isolated from the adult rat uterus and cultured for three studies: 1) Intracellular VEGF levels were measured in MCs cultured with progesterone (10(-11), 10(-9), and 10(-7) M) (n = 6 tests per group). 2) Blood vessel density was evaluated 8 days after MCs (3 x 10(6) or 6 x 10(6)), smooth muscle cells (SMCs), or endothelial cells (n = 6 rats per group) were injected with matrigel into the subcutaneous tissue of adult rats. 3) MCs, SMCs (5 x 10(6)/rat), or media were injected into a transmural scar 3 wk after cryoinjury in rat hearts (n = 12 rats per group), and heart function, blood vessel density, and myocardial scar size and thickness were evaluated 5 wk later. In study 1, cultured MCs expressed VEGF, with levels significantly (P < 0.05) upregulated by progesterone at an optimal dose of 10(-11) M. In study 2, MCs injected into the subcutaneous tissue with matrigel induced significantly more blood vessels, especially large-diameter vessels, than did SMCs or endothelial cells (P < 0.01 for all groups). This angiogenic effect was greatest (P < 0.01) at higher doses of MCs and was enhanced by progesterone (10(-11) M). In study 3, MCs implanted into the injured myocardium increased blood vessel density at the implant area, reduced scar size, and improved cardiac function relative to SMCs and media. Overall, MCs induced angiogenesis in vitro and in vivo, prevented cardiac remodeling, and improved heart functional recovery after cardiac injury.
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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) | 0.001 | 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".