Low Protein Diets and Energy Balance: Mechanisms of Action on Energy Intake and Expenditure
Bibliographic record
Abstract
Low protein diets are associated with increased lifespan and improved cardiometabolic health primarily in rodents, and likely improve human health. There is strong evidence that moderate to severe reduction in dietary protein content markedly influences caloric intake and energy expenditure, which is often followed by a decrease in body weight and adiposity in animal models. While the neuroendocrine signals that trigger hyperphagic responses to protein restriction are better understood, there is accumulating evidence that increased sympathetic flux to brown adipose tissue, fibroblast growth factor-21 and serotonergic signaling are important for the thermogenic effects of low protein diets. This mini-review specifically focuses on the effect of low protein diets with variable carbohydrate and lipid content on energy intake and expenditure, and the underlying mechanisms of actions by these diets. Understanding the mechanisms by which protein restriction influences energy balance may unveil novel approaches for treating metabolic disorders in humans and improve production efficiency in domestic animals.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".