Cardiac ICAM-1 mediates leukocyte-dependent decreased ventricular contractility in endotoxemic mice☆
Bibliographic record
Abstract
OBJECTIVE: Binding of ICAM-1 expressed on cardiomyocytes decreases cardiomyocyte contractility in vitro by altering the intracellular Ca2+ transient. We tested the hypothesis that signaling via ICAM-1 contributes to decreased left ventricular contractility in an in vivo model of systemic inflammation. METHODS: C57B6 wild-type mice and ICAM-1 knock-out mice were treated with intraperitoneal lipopolysaccharide (LPS) then left ventricular contractility was measured 6 h later using a volume-conductance micromanometer catheter. We repeated this experiment in chimeric mice lacking ICAM-1 expression in bone marrow-derived cells (M-) and/or lacking ICAM-1 expression in the heart and other tissues (H-). RESULTS: In C57B6 wild-type mice LPS injection significantly increased cardiac ICAM-1 expression and decreased in vivo measures of left ventricular contractility (end-systolic elastance, Ees decreased 58 +/- 4%, p < 0.05, [dP/dtmax]/EDV decreased 60 +/- 6%, p < 0.05). Cyclophosphamide pretreatment to decrease leukocyte count prevented the LPS-induced decrease in contractility. In ICAM-1 knock-out mice LPS did not decrease any measure of contractility. LPS did not decrease left ventricular contractility in M+/H- mice but decreased contractility in M+/H+ and M-/H+ mice to the same extent as in C57B6 wild-type mice implicating the importance of cardiac ICAM-1. CONCLUSIONS: We conclude that signaling via cardiac ICAM-1 is necessary to mediate leukocyte-dependent decreases of left ventricular contractility in endotoxemic mice.
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) | 0.001 | 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 | 0.000 | 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".