Severe Acute Respiratory Syndrome Coronavirus 2 Infection Induces Greater T-Cell Responses Compared to Vaccination in Solid Organ Transplant Recipients
Bibliographic record
Abstract
T-cell immunity associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or vaccination in solid organ transplant recipients (SOTRs) is poorly understood. To address this, we measured T-cell responses in 50 SOTRs with prior SARS-CoV-2 infection. The majority of patients mounted SARS-CoV-2-specific CD4+ T-cell responses against spike (S), nucleocapsid, and membrane proteins; CD8+ T-cell responses were generated to a lesser extent. CD4+ T-cell responses correlated with antibody levels. Severity of disease and mycophenolate dose were moderately associated with lower proportions of antigen-specific T cells. Relative to nontransplant controls, SOTRs had perturbations in both total and antigen-specific T cells, including higher frequencies of total PD-1+ CD4+ T cells. Vaccinated SOTRs (n = 55) mounted significantly lower proportions of S-specific polyfunctional CD4+ T cells after 2 doses, relative to unvaccinated SOTRs with prior coronavirus disease 2019. Together, these results suggest that SOTRs generate robust T-cell responses following natural infection that correlate with disease severity but generate comparatively lower T-cell responses following mRNA vaccination.
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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".