Expansion of tissue-resident CD8+ T cells and CD4+ Th17 cells in the nasal mucosa following mRNA COVID-19 vaccination
Bibliographic record
Abstract
Abstract Vaccines against SARS-CoV-2 have shown high efficacy in clinical trials, yet a full immunologic characterization of these vaccines, particularly within the upper respiratory tract, remains lacking. We enumerated and phenotyped T cells in nasal mucosa and blood before and after vaccination with the Pfizer-BioNTech COVID-19 vaccine (n =21). Tissue-resident memory (Trm) CD8+ T cells expressing CD69+CD103+ expanded ∼12 days following the first and second doses, by 0.31 and 0.43 log 10 cells per swab respectively (p=0.058 and p=0.009 in adjusted linear mixed models). CD69+CD103+CD8+ T cells in the blood decreased post-vaccination. Similar increases in nasal CD8+CD69+CD103-T cells were observed, particularly following the second dose. CD4+ Th17 cells were also increased in abundance following both doses. Following stimulation with SARS-CoV-2 spike peptides, CD8+ T cells increased expression of CD107a and CD154. These data suggest that nasal T cells may be induced and contribute to the protective immunity afforded by this vaccine.
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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) | 0.004 | 0.001 |
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".