Cardiac myocytes are a cellular source of chemokines in sepsis: role of NAD(P)H oxidase
Bibliographic record
Abstract
Neutrophil accumulation within the heart during sepsis is an important contributing factor involved in sepsis‐induced myocardial dysfunction. We have previously shown that cardiac myocytes challenged with septic plasma are converted to a proinflammatory phenotype; these myocytes generate chemokines and promote neutrophil (PMN) transendothelial migration. The aim of present study was to assess the role of NADPH oxidase in the sepsis‐induced conversion of cardiac myocytes to a proinflammatory phenotype. Feces‐induced peritonitis (FIP) was used as murine sepsis model. Cardiac myocytes were treated with plasma isolated from either sham or septic mice. Supernatants collected from plasma‐conditioned cardiac myocytes were used for determination of chemokine production (ELISA) and PMN transendothelial migration (cell culture inserts). Cardiac myocyte NADPH oxidase activity increased after exposure of the cells to septic plasma (increased production of superoxide; lucigenin‐enhanced chemiluminesence). Supernatants from cardiac myocytes conditioned with septic plasma 1) contained higher levels of the chemokine, KC, and 2) increased PMN transendothelial migration. Both chemokine production and PMN migration were prevented when the myocytes were pretreated with NADPH oxidase inhibitors (diphenylene iodonium;10 μM or apocynin;1 mM) or when myocytes from mice deficient in gp 91phox were used. Collectively, these findings indicate that the NADPH oxidase signaling pathway plays an important role in the conversion of cardiac myocytes to a proinflammatory phenotype in sepsis. (CIHR MOP‐13668, MGC‐12816)
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".