Interactive effects of maternal cigarette smoke, heat stress, hypoxia, and lipopolysaccharide on neonatal cardiorespiratory and cytokine responses
Bibliographic record
Abstract
Maternal cigarette smoke (CS) exposure exhibits a strong epidemiological association with Sudden Infant Death Syndrome, but other environmental stressors, including infection, hyperthermia, and hypoxia, have also been postulated as important risk factors. This study examines whether maternal CS exposure causes maladaptations within homeostatic control networks by influencing the response to lipopolysaccharide, heat stress, and/or hypoxia in neonatal rats. Pregnant dams were exposed to CS or parallel sham treatments daily for the length of gestation. Offspring were studied at postnatal days 6–8 at ambient temperatures (Ta) of 33°C or 38°C. Within each group, rats were allocated to control, saline, or LPS (200 µg/kg) treatments. Cardiorespiratory patterns were examined using head-out plethysmography and ECG surface electrodes during normoxia and hypoxia (10% O2). Serum cytokine concentrations were quantified from samples taken at the end of each experiment. Our results suggest maternal CS exposure does not alter minute ventilation (V̇e) or heart rate (HR) response to infection or high temperature, but independently increases apnea frequency. CS also primes the inflammatory system to elicit a stronger cytokine response to bacterial insult. High Taindependently depresses V̇e but augments the hypoxia-induced increase in V̇e. Moreover, higher Taincreases HR during normoxia and hypoxia, and in the presence of an immune challenge, increases HR during normoxia, and reduces the increase normally associated with hypoxia. Thus, while most environmental risk factors increase the burden on the cardiorespiratory system in early life, hyperthermia and infection blunt the normal HR response to hypoxia, and gestational CS independently destabilizes breathing by increasing apneas.
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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 | 0.000 |
| 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".