Effects of nutrition on neuro-endocrine stress responses
Bibliographic record
Abstract
PURPOSE OF REVIEW: Past studies in humans and animals have shown that low blood glucose concentrations due to fasting negatively interfere with the ability to mount a hypothalamus-pituitary-adrenal (HPA) axis response to psychological stress or to pharmacological activation, respectively. This contradicts the classical view of the proposed primary glucocorticoid function of providing the individual with energy in fight-or-flight situations. RECENT FINDINGS: Not many studies have followed up on this phenomenon in recent years, but our understanding of how appetite and satiety is regulated has significantly improved. Many of the neuropeptides involved in regulation of energy homeostasis interact with key areas of the HPA axis. The majority of orexigenic peptides have been shown to activate the HPA axis, while some anorexic peptides negatively modulate HPA axis activation and others also stimulate it. SUMMARY: The effects of orexigenic peptides on the HPA axis are incompatible with the phenomenon of blunted HPA axis activity in states of low energy available, while the fact that some anorexigenic peptides activate the HPA axis might point to a permissive role. In conclusion, current data insufficiently explain negative HPA axis modulation by low glucose levels.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.004 | 0.003 |
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".