Cardiac Fibroblasts Contribute to Myocardial Dysfunction in Mice with Sepsis: The Role of NLRP3 Inflammasome Activation
Bibliographic record
Abstract
Myocardial contractile dysfunction in sepsis is associated with the increased morbidity and mortality. Although the underlying mechanisms of the cardiac depression have not been fully elucidated, an exaggerated inflammatory response is believed to be responsible. Nucleotide-binding oligomerization domain-like receptor containing pyrin domain 3 (NLRP3) inflammasome is an intracellular platform that is involved in the maturation and release of interleukin (IL)-1β. The aim of the present study is to evaluate whether sepsis activates NLRP3 inflammasome/caspase-1/IL-1β pathway in cardiac fibroblasts (CFs) and whether this cytokine can subsequently impact the function of cardiomyocytes (cardiac fibroblast-myocyte cross-talk). We show that treatment of CFs with lipopolysaccharide (LPS) induces upregulation of NLRP3, activation of caspase-1, as well as the maturation (activation) and release of IL-1β. In addition, the genetic (small interfering ribonucleic acid [siRNA]) and pharmacological (glyburide) inhibition of the NLRP3 inflammasome in CFs can block this signaling pathway. Furthermore, the inhibition of the NLRP3 inflammasome in cardiac fibroblasts ameliorated the ability of LPS-challenged CFs to impact cardiomyocyte function as assessed by intracellular cyclic adenosine monophosphate (cAMP) responses in cardiomyocytes. Salient features of this the NLP3 inflammasome/ caspase-1 pathway were confirmed in in vivo models of endotoxemia/sepsis. We found that inhibition of the NLRP3 inflammasome attenuated myocardial dysfunction in mice with LPS and increased the survival rate in mice with feces-induced peritonitis. Our results indicate that the activation of the NLRP3 inflammasome in cardiac fibroblasts is pivotal in the induction of myocardial dysfunction in sepsis.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".