Age-associated metabolic dysregulation in bone marrow-derived macrophages stimulated with lipopolysaccharide
Bibliographic record
Abstract
Macrophages are major contributors to age-associated inflammation. Metabolic processes such as oxidative phosphorylation, glycolysis and the urea cycle regulate inflammatory responses by macrophages. Metabolic profiles changes with age; therefore, we hypothesized that dysregulation of metabolic processes could contribute to macrophage hyporesponsiveness to LPS. We examined the intracellular metabolome of bone marrow-derived macrophages from young (6-8 wk) and old (18-22 mo) mice following lipopolysaccharide (LPS) stimulation and tolerance. We discovered known and novel metabolites that were associated with the LPS response of macrophages from young mice, which were not inducible in macrophages from old mice. Macrophages from old mice were largely non-responsive towards LPS stimulation, and we did not observe a shift from oxidative phosphorylation to glycolysis. The critical regulatory metabolites succinate, γ-aminobutyric acid, arginine, ornithine and adenosine were increased in LPS-stimulated macrophages from young mice, but not macrophages from old mice. A shift between glycolysis and oxidative phosphorylation was not observed during LPS tolerance in macrophages from either young or old mice. Metabolic bottlenecks may be one of the mechanisms that contribute to the dysregulation of LPS responses with age.
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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".