Evolutionary Significance of the Neuroendocrine Stress Axis on Vertebrate Immunity and the Influence of the Microbiome on Early-Life Stress Regulation and Health Outcomes
Bibliographic record
Abstract
Stress is broadly defined as the non-specific biological response to changes in homeostatic demands and is mediated by the evolutionarily conserved neuroendocrine networks of the hypothalamus-pituitary-adrenal (HPA) axis and the sympathetic nervous system. Activation of these networks results in transient release of glucocorticoids (cortisol) and catecholamines (epinephrine) into circulation, as well as activation of sympathetic fibers innervating end organs. These interventions thus regulate numerous physiological processes, including energy metabolism, cardiovascular physiology, and immunity, thereby adapting to cope with the perceived stressors. The developmental trajectory of the stress-axis is influenced by a number of factors, including the gut microbiome, which is the community of microbes that colonizes the gastrointestinal tract immediately following birth. The gut microbiome communicates with the brain through the production of metabolites and microbially derived signals, which are essential to human stress response network development. Ecological perturbations to the gut microbiome during early life may result in the alteration of signals implicated in developmental programming during this critical window, predisposing individuals to numerous diseases later in life. The vulnerability of stress response networks to maladaptive development has been exemplified through animal models determining a causal role for gut microbial ecosystems in HPA axis activity, stress reactivity, and brain development. In this review, we explore the evolutionary significance of the stress-axis system for health maintenance and review recent findings that connect early-life microbiome disturbances to alterations in the development of stress response networks.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".