The viral mimic, polyinosinic:polycytidylic acid, induces fever in rats via an interleukin-1-dependent mechanism
Bibliographic record
Abstract
Polyinosinic:polycytidylic acid (poly I:C) is a synthetic double-stranded RNA that is used experimentally to model viral infections in vivo. Previous studies investigating the inflammatory properties of this agent in rodents demonstrated that it is a potent pyrogen. However, the mechanisms underlying this response have not been fully elucidated. In the current study, we examined the effects of peripheral administration of poly I:C on body temperature and cytokine production. Male rats were implanted with biotelemetry devices and randomly assigned to one of the following three groups: poly I:C + saline, poly I:C + interleukin-1 receptor antagonist (IL-1ra), or saline + saline. Maximal fever of 1.6 degrees C above baseline was observed 3 h after an intraperitoneal injection of poly I:C (750 microg/kg). Pretreatment with IL-1ra diminished this response by >50% (maximum body temperature = 0.6 degrees C above baseline). Plasma IL-6 concentration increased fivefold 2 h post-poly I:C compared with saline-injected rats; levels returned to baseline 4 h postinjection. Pretreatment with IL-1ra prevented this rise in IL-6. Plasma tumor necrosis factor (TNF)-alpha was also increased more than fourfold 2 h postinjection but remained unaffected by IL-1ra treatment. IL-1beta and cyclooxygenase-2 mRNA were significantly upregulated in the hypothalamus of poly I:C-treated animals. Finally, poly I:C decreased food intake by 30%, but this response was not altered by pretreatment with IL-1ra. These results suggest that poly I:C induces fever, but not anorexia, through an IL-1 and prostaglandin-dependent mechanism.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".