The cardiac repair benefits of inflammation do not persist: evidence from mast cell implantation
Bibliographic record
Abstract
Multiple mechanisms contribute to progressive cardiac dysfunction after myocardial infarction (MI) and inflammation is an important mediator. Mast cells (MCs) trigger inflammation after MI by releasing bio-active factors that contribute to healing. c-Kit-deficient (Kit(W/W-v) ) mice have dysfunctional MCs and develop severe ventricular dilatation post-MI. We explored the role of MCs in post-MI repair. Mouse wild-type (WT) and Kit(W/W-v) MCs were obtained from bone marrow (BM). MC effects on fibroblasts were examined in vitro by proliferation and gel contraction assays. MCs were implanted into infarcted mouse hearts and their effects were evaluated using molecular, cellular and cardiac functional analyses. In contrast to WT, Kit(W/W-v) MC transplantation into Kit(W/W-v) mice did not improve cardiac function or scar size post-MI. Kit(W/W-v) MCs induced significantly reduced fibroblast proliferation and contraction compared to WT MCs. MC influence on fibroblast proliferation was Basic fibroblast growth factor (bFGF)-dependent and MC-induced fibroblast contractility functioned through transforming growth factor (TGF)-β. WT MCs transiently rescue cardiac function early post-MI, but the benefits of BM cell implantation lasted longer. MCs induced increased inflammation compared to the BM-injected mice, with increased neutrophil infiltration and infarct tumour necrosis factor-α (TNF-α) concentration. This augmented inflammation was followed by increased angiogenesis and myofibroblast formation and reduced scar size at early time-points. Similar to the functional data, these beneficial effects were transient, largely vanishing by day 28. Dysfunctional Kit(W/W-v) MCs were unable to rescue cardiac function post-MI. WT MC implantation transiently enhanced angiogenesis and cardiac function. These data suggest that increased inflammation is beneficial to cardiac repair, but these effects are not persistent.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".