Differential remodeling of the electron transport chain is required to support TLR3 and TLR4 signaling and cytokine production in macrophages
Bibliographic record
Abstract
Increasing evidence suggests that mitochondria play a critical role in driving innate immune responses against bacteria and viruses. However, it is unclear if differential reprogramming of mitochondrial function contributes to the fine tuning of pathogen specific immune responses. Here, we found that TLR3 and TLR4 engagement on murine bone marrow derived macrophages was associated with differential remodeling of electron transport chain complex expression. This remodeling was associated with differential accumulation of mitochondrial and cytosolic ROS, which were required to support ligand specific inflammatory and antiviral cytokine production. We also found that the magnitude of TLR3, but not TLR4, responses were modulated by glucose availability. Under conditions of low glucose, TLR3 engagement was associated with increased ETC complex III expression, increased mitochondrial and cytosolic ROS and increased inflammatory and antiviral cytokine production. This amplification was selectively reversed by targeting superoxide production from the outer Q-binding site of the ETC complex III. These results suggest that ligand specific modulation of the ETC may act as a rheostat that fine tunes innate immune responses via mitochondrial ROS production. Modulation of these processes may represent a novel mechanism to modulate the nature as well as the magnitude of antiviral vs. inflammatory immune responses.
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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".