Effect of influenza vaccination on resting metabolic rate and c-reactive protein concentrations in healthy young adults
Bibliographic record
Abstract
OBJECTIVES: Chronic immune activation and severe inflammatory states are positively associated with resting metabolic rate (RMR; kcal/day), but the impacts of mild immune stimuli on metabolism are poorly understood. This study investigates the within-individual association between the inflammatory response to influenza vaccination and RMR in young adults. METHODS: We evaluated RMRs through indirect calorimetry and circulating c-reactive protein (CRP) concentrations (mg/L)-a direct measure of inflammation-via high-sensitivity immunoassays of dried blood spots (n = 17) at baseline and two- and seven-days post-vaccine. Wilcoxon matched-pairs signed-rank tests were used to evaluate the magnitude of the CRP and RMR responses. Type II Wald chi-square tests of linear mixed-effect models assessed whether those responses were correlated. RESULTS: Baseline CRP was 1.39 ± 1.26 mg/L. On day two post-vaccine, CRP increased by 1.47 ± 1.37 mg/L (p < 0.0001), representing a 106% increase above baseline values. CRP remained higher on day seven post-vaccine, 1.32 ± 2.47 mg/L (p = 0.05) above baseline values. There were no statistically significant changes in RMR from baseline to day two (p = 0.98) or day seven (p = 0.21). Change in CRP from baseline did not predict RMR variation across days (p = 0.46). CONCLUSIONS: We find no evidence that adult influenza vaccination results in a corresponding increase in RMR. These results suggest that the energetic cost of an influenza vaccine's mild inflammatory stimulus is either too small to detect or is largely compensated by a temporary downregulation of energy allocated to other metabolic tasks.
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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 | 0.001 | 0.002 |
| 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".