Identification of a leucine-mediated threshold effect governing macrophage mTOR signalling and cardiovascular risk
Bibliographic record
Abstract
High protein intake is common in western societies and is often promoted as part of a healthy lifestyle; however, amino-acid-mediated mammalian target of rapamycin (mTOR) signalling in macrophages has been implicated in the pathogenesis of ischaemic cardiovascular disease. In a series of clinical studies on male and female participants ( NCT03946774 and NCT03994367 ) that involved graded amounts of protein ingestion together with detailed plasma amino acid analysis and human monocyte/macrophage experiments, we identify leucine as the key activator of mTOR signalling in macrophages. We describe a threshold effect of high protein intake and circulating leucine on monocytes/macrophages wherein only protein in excess of ∼25 g per meal induces mTOR activation and functional effects. By designing specific diets modified in protein and leucine content representative of the intake in the general population, we confirm this threshold effect in mouse models and find ingestion of protein in excess of ∼22% of dietary energy requirements drives atherosclerosis in male mice. These data demonstrate a mechanistic basis for the adverse impact of excessive dietary protein on cardiovascular risk.
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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".