Direct Injection of Kit Ligand-2 Lentivirus Improves Cardiac Repair and Rescues Mice Post–myocardial Infarction
Bibliographic record
Abstract
Myocardial infarction (MI) and subsequent adverse remodeling cause heart failure. Previously we demonstrated a role for Kit ligand (KL) in improving cardiac function post-MI. KL has two major isoforms; KL-1 is secreted whereas KL-2 is predominantly membrane bound. We demonstrate here first that KL-2-deficient mice have worse survival and an increased heart/bodyweight ratio post-MI compared to mice with reduced c-Kit receptor expression. Next we synthesized recombinant lentiviral vectors (LVs) that engineered functional expression of murine KL-1 and KL-2. For in vivo analyses, we directly injected these LVs into the left ventricle of membrane-bound KL-deficient Sl/Sl(d) or wild-type (WT) mice undergoing MI. Control LV/enGFP injection led to measurable reporter gene expression in hearts. Injection of LV/KL-2 attenuated adverse left ventricular remodeling and dramatically improved survival post-MI in both Sl/Sl(d) and WT mice (from 12 to 71% and 35 to 73%, respectively, versus controls). With regard toward beginning to understand the possible salutary mechanisms involved in this effect, differential staining patterns of Sca-1 and Ly49 on peripheral blood (PB) cells from therapeutically treated animals was found. Our data show that LV/KL-2 gene therapy is a promising treatment for MI.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".