Chronic noise exposure in the spontaneously hypertensive rat
Bibliographic record
Abstract
INTRODUCTION: Epidemiological studies have suggested an association between the relative risk for developing cardiovascular disease (CVD) and long-term exposure to elevated levels of transportation noise. The contention is that this association is largely owing to an increase in stress-related biomarkers that are thought to be associated with CVD. Animal models have demonstrated that acute noise exposure is capable of triggering a stress response; however, similar studies using chronic noise models are less common. MATERIALS AND METHODS: The current study assessed the effects of intermittent daily exposure to broadband 80 kHz bandwidth noise of 87.3 dBA for a period of 21 consecutive days in spontaneously hypertensive rats. RESULTS: Twenty-one days of exposure to noise significantly reduced body weight relative to the sham and unhandled control groups; however, noise had no statistically significant impact on plasma adrenocorticotropic hormone (or adrenal gland weights). Noise was associated with a significant, albeit modest, increase in both corticosterone and aldosterone concentrations following the 21 days of exposure. Interleukin 1 and interleukin 6 levels were unchanged in the noise group, whereas both tumour necrosis factor alpha and C-reactive protein were significantly reduced in noise exposed rats. Tail blood sampling for corticosterone throughout the exposure period showed no appreciable difference between the noise and sham exposed animals, largely due to the sizeable variation for each group as well as the observed fluctuations over time. DISCUSSION: The current pilot study provides only modest support that chronic noise may promote stress-related biological and/or developmental effects. More research is required to verify the current findings and resolve some of the unexpected observations.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".