Induction of IRAK-M Is Associated with Lipopolysaccharide Tolerance in a Human Endotoxemia Model
Bibliographic record
Abstract
Recent in vitro and murine in vivo studies have identified several potential LPS tolerance factors. In this study, we describe the expression kinetics of these LPS tolerance factors in standardized human endotoxemia models using i.v. LPS bolus administration. Responsiveness to LPS as well as the expression of potential regulators of LPS signaling were determined in peripheral whole blood. Intravenous LPS administration (4 ng/kg) resulted in peak plasma levels of TNF-alpha at 1.5 h followed by subsequent peaks of the classic negative feedback inhibitors A20 and IL-10 at 2 and 3 h, respectively. Circulating blood monocyte counts decimated during the initial inflammatory response, but normalized in the period between 4 and 8 h post-LPS. The LPS response as determined by ex vivo TNF release per monocyte in whole blood was profoundly decreased at 6-8 h post-LPS injection despite cessation of A20 and IL-10 expression after 4 h. Analysis of MyD88short, IL-1R-associated kinase (IRAK)-1, IRAK-M, ST2, suppressor of cytokine signaling-1 and -3, SHIP-1, and MAP kinase phosphatase-1 expression indicated that the observed LPS tolerance was associated with decreased IRAK-1 and elevated IRAK-M expression in this human model. Interestingly, a lower dose of LPS (1 ng/kg) induced LPS tolerance accompanied with IRAK-M up-regulation but without depletion of IRAK-1. In vitro studies in whole blood showed that IRAK-M up-regulation by LPS is largely dependent on TNF-alpha. The observed rise of IRAK-M transcription in the human endotoxemia model appeared much greater compared with in vitro-stimulated whole blood. In conclusion, LPS tolerance in human endotoxemia models is associated with IRAK-M up-regulation.
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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".