Alcohol Effects on Stress Pathways
Bibliographic record
Abstract
A significant amount of neurobiological research regarding the development of alcohol use disorders (AUDs) has focused on alcohol-related activation and long-term alterations in the mesocortical dopaminergic reward pathways. However, alcohol does not only interact with brain reward systems. Many of its acute and chronic effects may be related to allostatic adaptations in hypothalamic and extrahypothalamic stress regulation pathways. For example, acute binge intoxication is associated with hypothalamically driven increases in blood cortisol, norepinephrine, and sex steroid metabolite levels. This may contribute to the development of mesocortical sensitization to alcohol. Furthermore, chronic alcohol exposure is associated with systemic dysregulation of the hypothalamic pituitary adrenal axis, sympathetic adrenal medullary system, and sex steroid systems. This dysregulation appears to manifest as neuroendocrine tolerance. In this review, we first summarize the literature suggesting that alcohol-induced alterations in these hypothalamic systems influence craving and contribute to the development of AUDs. We note that for women, the effects of alcohol on these neuroendocrine stress regulation systems may be influenced by the rhythmic variations of hormones and steroids across the menstrual cycle. Second, we discuss how changes in these systems may indicate progression of AUDs and increased risk of relapse in both sexes. Specifically, neuroendocrine tolerance may contribute to mesocortical sensitization, which in turn may lead to decreased prefrontal inhibitory control of the dopaminergic reward and hypothalamic stress systems. Thus, pharmacological strategies that counteract alcohol-associated changes in hypothalamic and extrahypothalamic stress regulation pathways may slow the development and progression of AUDs.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".