Comparative evaluation of metabolic, electrophilic, and immunologic effects of itaconate and its ester derivatives on macrophage activation
Bibliographic record
Abstract
Abstract Following the discovery of itaconate’s immunoregulatory properties, several ester derivatives of this dicarboxylic acid were designed to further examine its role. Here, we compare the metabolic, electrophilic, and immunologic profiles of macrophages treated with unmodified itaconate and a panel of itaconate derivatives. Using WT and Irg1-deficient macrophages, we show that neither dimethyl itaconate (DI) nor 4-octyl itaconate (4OI) are converted into intracellular itaconate in either resting or TLR-activated cells, 4-monoethyl itaconate (4EI) yields only small quantities of intracellular itaconate, while exogenous itaconic acid readily enters macrophages and accumulates to physiologically relevant amounts. We find that both DI and 4OI induce a strong electrophilic stress response, in contrast to itaconate and 4EI. This correlated with their differential immunological impact: DI and 4OI both inhibited IκBζ induction and IL-6 secretion. In contrast, itaconate treatment had minimal impact on IκBζ, IL-6 and pro-IL-1β levels, but demonstrated a distinct defect in IL-1β secretion. Altogether, this systematic evaluation stresses the importance of using unmodified itaconate in future mechanistic studies.
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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 | 0.000 |
| 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".