Interactions among mTORC, AMPK, and SIRT: A Computational Model for Cell Energy Balance and Metabolism
Bibliographic record
Abstract
Abstract Key proteins such as mTORC, AMPK, and sirtuins are known to play an essential role in the management of metabolic stress and ageing mechanisms. An impairment in these mechanisms is commonly associated with cellular ageing and degenerative diseases. To understand the complex interactions of ageing□related signalling pathways and environmental signals, and the impacts on lifespan and health-span, we developed a computational model of ageing signalling pathways. The model includes (i) the insulin/IGF-1 pathway, which couples energy and nutrient abundance to the execution of cell growth and division, (ii) mTORC1 and amino acid sensors, (iii) the Preiss-Handler and salvage pathways, which regulate the metabolism of NAD+ and the NAD+-consuming factor SIRT1, (iv) the energy sensor AMPK, and (v) transcription factors FOXO and PGC-1α. Key findings include the clinically important role of PRAS40, sestrin2, and diet in the treatment of cancers and other diseases, and a potential link between SIRT1-activating compounds and premature autophagy. The model can be used as an essential component to simulate gene manipulation, therapies (e.g., rapamycin and wortmannin), calorie restrictions, and chronic stress, and to assess their functional implications on longevity and ageing□related diseases. Author Summary In cellular ageing, mitochondrial function declines over time, which affects normal mechanisms of cells and organisms and leads to myriad of degenerative diseases and other health problems. To investigate the mechanisms that affect the ageing process, we focus on pathways that play a key role in the management of metabolic stress: the mTORC, AMPK, and sirtuins pathways. Our goal is to understand the complex interactions of ageing and metabolism related signalling pathways and environmental signals, and the impacts on lifespan and health-span. To accomplish that goal, we developed a computational model of signalling pathways related to ageing and metabolism. By conducting model simulations, we have unraveled the clinically important role of PRAS40, sestrin2, and diet in the treatment of cancers and other diseases, and a double-edged sword effect of SIRT1-activating compounds in their use as a health remedy. We view this model as an essential step towards a tool for studying metabolism, longevity, and ageing-related diseases. By extending the present model as appropriate, we can simulate gene manipulation, therapies (e.g., rapamycin and wortmannin), calorie restrictions, and chronic stress,.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".