The Impact of Inflammation on Thermal Hyperpnea: Relevance for Heat Stress and Febrile Seizures
Bibliographic record
Abstract
Abstract Extreme heat caused by climate change is increasing the transmission of infectious diseases, resulting in a sharp rise in heat-related illness and mortality. Understanding the mechanistic link between heat, inflammation, and disease is thus important for public health. Thermal hyperpnea, and consequent respiratory alkalosis, is crucial in febrile seizures and convulsions induced by heat stress in humans. Here, we address what causes thermal hyperpnea in neonates and how it is affected by inflammation. Transient receptor potential cation channel subfamily V member 1 (TRPV1), a heat-activated channel, is sensitized by inflammation and modulates breathing and thus may play a key role. To investigate whether inflammatory sensitization of TRPV1 modifies neonatal ventilatory responses to heat stress, leading to respiratory alkalosis and an increased susceptibility to hyperthermic seizures, we treated neonatal rats with bacterial LPS, and breathing, arterial pH, in vitro vagus nerve activity, and seizure susceptibility were assessed during heat stress in the presence or absence of a TRPV1 antagonist (AMG-9810) or shRNA-mediated TRPV1 suppression. LPS-induced inflammatory preconditioning lowered the threshold temperature and latency of hyperthermic seizures. This was accompanied by increased tidal volume, minute ventilation, expired CO2, and arterial pH (alkalosis). LPS exposure also elevated vagal spiking and intracellular calcium concentrations in response to hyperthermia. TRPV1 inhibition with AMG-9810 or shRNA reduced the LPS-induced susceptibility to hyperthermic seizures and altered the breathing pattern to fast shallow breaths (tachypnea), making each breath less efficient and restoring arterial pH. These results indicate that inflammation exacerbates thermal hyperpnea-induced respiratory alkalosis associated with increased susceptibility to hyperthermic seizures, primarily mediated by TRPV1 localized to vagus neurons.
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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".