Chronic stress impacts the cardiovascular system: animal models and clinical outcomes
Bibliographic record
Abstract
Psychological stresses are associated with cardiovascular diseases to the extent that cardiovascular diseases are among the most important group of psychosomatic diseases. The longstanding association between stress and cardiovascular disease exists despite a large ambiguity about the underlying mechanisms. An array of possibilities have been proposed including overactivity of the autonomic nervous system and humoral changes, which then converge on endothelial dysfunction that initiates unwanted cardiovascular consequences. We review some of the features of the two most important stress-activated systems, i.e., the humoral and nervous systems, and focus on alterations in endothelial function that could ensue as a result of these changes. Cardiac and hematologic consequences of stress are also addressed briefly. It is likely that activation of the inflammatory cascade in association with oxidative imbalance represents key pathophysiological components of stress-induced cardiovascular changes. We also review some of the commonly used animal models of stress and discuss the cardiovascular outcomes reported in these models of stress. The unique ability of animals for adaptation under stressful conditions lessens the extrapolation of laboratory findings to conditions of human stress. An animal model of unpredictable chronic stress, which applies various stress modules in a random fashion, might be a useful solution to this predicament. The use of stress markers as indicators of stress intensity is also discussed in various models of animal stress and in clinical studies.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".