Lipopolysaccharide‐induced alteration of mitochondrial morphology induces a metabolic shift in microglia modulating the inflammatory response in vitro and in vivo
Bibliographic record
Abstract
Accumulating evidence suggests that changes in the metabolic signature of microglia underlie their response to inflammation. We sought to increase our knowledge of how pro-inflammatory stimuli induce metabolic changes. Primary microglia exposed to lipopolysaccharide (LPS)-expressed excessive fission leading to more fragmented mitochondria than tubular mitochondria. LPS-mediated Toll-like receptor 4 (TLR4) activation also resulted in metabolic reprogramming from oxidative phosphorylation to glycolysis. Blockade of mitochondrial fission by Mdivi-1, a putative mitochondrial division inhibitor led to the reversal of the metabolic shift. Mdivi-1 treatment also normalized the changes caused by LPS exposure, namely an increase in mitochondrial reactive oxygen species production and mitochondrial membrane potential as well as accumulation of key metabolic intermediate of TCA cycle succinate. Moreover, Mdivi-1 treatment substantially reduced LPS induced cytokine and chemokine production. Finally, we showed that Mdivi-1 treatment attenuated expression of genes related to cytotoxic, repair, and immunomodulatory microglia phenotypes in an in vivo neuroinflammation paradigm. Collectively, our data show that the activation of microglia to a classically pro-inflammatory state is associated with a switch to glycolysis that is mediated by mitochondrial fission, a process which may be a pharmacological target for immunomodulation.
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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".