Uterine Immunoprivileged Cells Restore Cardiac Function of Male Recipients After Myocardial Infarction
Bibliographic record
Abstract
It has been documented that the uterus plays a key cardio-protective role in pre-menopausal women, which is supported by uterine cell therapy, to preserve cardiac functioning post-myocardial infarction, being effective among females. However, whether such therapies would also be beneficial among males is still largely unknown. In this study, we aimed to fill in this gap in knowledge by examining the effects of transplanted uterine cells on infarcted male hearts. We identified, based on major histocompatibility complex class I (MHC-I) expression levels, 3 uterine reparative cell populations: MHC-I(neg), MHC-I(mix), and MHC-I(pos). In vitro, MHC-I(neg) cells showed higher levels of pro-angiogenic, pro-survival, and anti-inflammatory factors, compared to MHC-I(mix) and MHC-I(pos). Furthermore, when cocultured with allogeneic mixed leukocytes, MHC-I(neg) had lower cytotoxicity and leukocyte proliferation. In particular, CD8+ cytotoxic T cells significantly decreased, while CD4+CD25+ Tregs and CD4-CD8- double-negative T cells significantly increased when cocultured with MHC-I(neg), compared to MHC-I(mix) and MHC-I(pos) cocultures. In vivo, MHC-I(neg) as well as MHC-I(mix) were found under both syngeneic and allogeneic transplantation in infarcted male hearts, to significantly improve cardiac function and reduce the scar size, via promoting angiogenesis in the infarcted area. All of these findings thus support the view that males could also benefit from the cardio-protective effects observed among females, via cell therapy approaches involving the transplantation of immuno-privileged uterine reparative cells in infarcted hearts.
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) | 0.001 | 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) | 0.002 | 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".