Moderate excess of pyruvate augments osteoclastogenesis
Bibliographic record
Abstract
Cell differentiation leads to adaptive changes in energy metabolism. Conversely, hyperglycemia induces malfunction of many body systems, including bone, suggesting that energy metabolism reciprocally affects cell differentiation. We investigated how the differentiation of bone-resorbing osteoclasts, large polykaryons formed through fusion and growth of cells of monocytic origin, is affected by excess of energy substrate pyruvate and how energy metabolism changes during osteoclast differentiation. Surprisingly, small increases in pyruvate (1-2 mM above basal levels) augmented osteoclastogenesis in vitro and in vivo, while larger increases were not effective in vitro. Osteoclast differentiation increased cell mitochondrial activity and ATP levels, which were further augmented in energy-rich conditions. Conversely, the inhibition of respiration significantly reduced osteoclast number and size. AMP-activated protein kinase (AMPK) acts as a metabolic sensor, which is inhibited in energy-rich conditions. We found that osteoclast differentiation was associated with an increase in AMPK levels and a change in AMPK isoform composition. Increased osteoclast size induced by pyruvate (1 mM above basal levels) was prevented in the presence of AMPK activator 5-amino-4-imidazole carboxamide ribonucleotide (AICAR). In keeping, inhibition of AMPK using dorsomorphin or siRNA to AMPKγ increased osteoclast size in control cultures to the level observed in the presence of pyruvate. Thus, we have found that a moderate excess of pyruvate enhances osteoclastogenesis, and that AMPK acts to tailor osteoclastogenesis to a cell's bioenergetics capacity.
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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) | 0.002 | 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".