Interleukin‐1β‐Induced Fever Does not Alter the Ability of 5‐ to 6‐Day‐Old Rat Pups to Autoresuscitate from Hypoxia‐Induced Apnoea
Bibliographic record
Abstract
Experiments were carried out to determine if endogenous pyrogen-induced fever impairs protective responses of newborn rats to hypoxia. Twenty-seven 5- to 6-day-old conscious rat pups received a subcutaneous injection of 0.20 microg of recombinant rat interleukin-1beta (rrIL-1beta) per kilogram of body weight to induce fever, or an equal volume of vehicle. They were then either exposed to a single period of hypoxia produced by breathing an anoxic gas mixture (97 % N(2)-3 % CO(2)) and their time to last gasp was determined, or they were exposed repeatedly to hypoxia and their ability to autoresuscitate from primary apnoea was determined. Core temperature increased significantly following administration of rrIL-1beta but did not change following administration of vehicle (i.e. vehicle, 0.0 +/- 0.1 degrees C; rrIL-1beta, 0.7 +/- 0.3 degrees C; P < 0.001) before exposure to hypoxia. IL-1beta-induced fever did not alter the time to last gasp when the pups were exposed to a single period of hypoxia or the number of successful autoresuscitations upon repeated exposure to hypoxia. Thus, our data do not support the hypothesis that endogenous pyrogen-induced fever impairs the protective responses in newborns that may prevent death during hypoxia as may occur during single or repeated episodes of prolonged sleep apnoea.
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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) | 0.002 | 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".