OPA1 drives macrophage metabolism and functional commitment via p65 signaling
Bibliographic record
Abstract
Macrophages are essential players for the host response against pathogens, regulation of inflammation and tissue regeneration. The wide range of macrophage functions rely on their heterogeneity and plasticity that enable a dynamic adaptation of their responses according to the surrounding environmental cues. Recent studies suggest that metabolism provides synergistic support for macrophage activation and elicitation of desirable immune responses; however, the metabolic pathways orchestrating macrophage activation are still under scrutiny. Optic atrophy 1 (OPA1) is a mitochondria-shaping protein controlling mitochondrial fusion, cristae biogenesis and respiration; clear evidence shows that the lack or dysfunctional activity of this protein triggers the accumulation of metabolic intermediates of the TCA cycle. In this study, we show that OPA1 has a crucial role in macrophage activation. Selective Opa1 deletion in myeloid cells impairs M1-macrophage commitment. Mechanistically, Opa1 deletion leads to TCA cycle metabolite accumulation and defective NF-κB signaling activation. In an in vivo model of muscle regeneration upon injury, Opa1 knockout macrophages persist within the damaged tissue, leading to excess collagen deposition and impairment in muscle regeneration. Collectively, our data indicate that OPA1 is a key metabolic driver of macrophage functions.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".