Consequences of low-intensity light at night on cardiovascular and metabolic parameters in spontaneously hypertensive rats
Bibliographic record
Abstract
Circadian rhythms are an inherent property of physiological processes and can be disturbed by irregular environmental cycles, including artificial light at night (ALAN). Circadian disruption may contribute to many pathologies, such as hypertension, obesity, and type 2 diabetes, but the underlying mechanisms are not understood. Our study investigated the consequences of ALAN on cardiovascular and metabolic parameters in spontaneously hypertensive rats, which represent an animal model of essential hypertension and insulin resistance. Adult males were exposed to a 12 h light − 12 h dark cycle and the ALAN group experienced dim light at night (1–2 lx), either for 2 or 5 weeks. Rats on ALAN showed a loss of light–dark variability for systolic blood pressure, but not for heart rate. Moreover, a gradual increase of systolic blood pressure was recorded over 5 weeks of ALAN. Exposure to ALAN increased plasma insulin and hepatic triglyceride levels. An increased expression of metabolic transcription factors, Pparα and Pparγ, in the epididymal fat and a decreased expression of Glut4 in the heart was found in the ALAN group. Our results demonstrate that low-intensity ALAN can disturb blood pressure control and augment insulin resistance in spontaneously hypertensive rats, and may represent a serious risk factor for cardiometabolic diseases.
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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 | 0.000 | 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) | 0.001 | 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".