Impact of SARS-CoV-2 vaccination and of seasonal variations on the innate immune inflammatory response
Bibliographic record
Abstract
Introduction: The innate immune response is an important first checkpoint in the evolution of an infection. Although adaptive immunity is generally considered the immune component that retains antigenic memory, innate immune responses can also be affected by previous stimulations. This study evaluated the impact of vaccination on innate cell activation by TLR7/8 agonist R848, as well as seasonal variations. Methods: To this end, blood samples from a cohort of 304 food and retail workers from the Quebec City region were collected during three visits at 12-week intervals. Peripheral blood mononuclear cells and polymorphonuclear neutrophils were isolated during the first and third visits and were stimulated with R848 to assess the innate immune response. Results: Our results show that IL-8 production after stimulation decreased after vaccination. In addition, the IL-8 response was significantly different depending on the season when the visit occurred, for both COVID-19 vaccinated and unvaccinated individuals. Discussion: This study highlights that innate immune responses can be affected by SARS-CoV-2 vaccination and fluctuate seasonally.
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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".