Disruption of Physiological Rhythms Persist Following Cessation of Cigarette Smoke Exposure in Mice
Bibliographic record
Abstract
BACKGROUND: Physiological rhythms in mammals are essential for maintaining health, whereas disruptions may cause or exacerbate disease pathogenesis. As such, our objective was to characterize how cigarette smoke exposure affects physiological rhythms of otherwise healthy mice using telemetry and cosinor analysis. METHODS: Female BALB/c mice were implanted with telemetry devices to measure body temperature, heart rate, systolic blood pressure (SBP), and activity. Following baseline measurements, mice were exposed to cigarette smoke for approximately 50 min twice daily during weekdays over 24 weeks. Physiological parameters were recorded after 1, 4, 8, and 24 weeks of exposure or after 4 weeks cessation following 4 weeks of cigarette smoke exposure. RESULTS: Acute cigarette smoke exposure resulted in anapyrexia, and bradycardia, with divergent effects on SBP. Long term, cigarette smoke exposure disrupted physiological rhythms after just 1 week, which persisted across 24 weeks of exposure (as shown by mixed effects on mesor, amplitude, acrophase, and goodness-of-fit using cosinor analysis). Four weeks of cessation was insufficient to allow full recovery of rhythms. CONCLUSION: Our characterization of the pathophysiology of cigarette smoke exposure on physiological rhythms of mice suggests that rhythm disruption may precede and contribute to disease pathogenesis. These findings provide a clear rationale and guide for the future use of chronotherapeutics.
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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 | 0.000 |
| 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) | 0.001 | 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".