Exposure-, infection, and vaccine-induced immune responses to SARS-COV-2
Bibliographic record
Abstract
There is tremendous diversity in the way individuals experience severe acute respiratory coronavirus 2 (SARS-CoV-2) infection. We analyzed immune responses to SARS-CoV-2 in the context of susceptibility to infection before and after vaccination. Within a cohort of subjects who were highly exposed to SARS-CoV-2 prior to vaccination and seronegative against the immunodominant spike (S) protein, there was evidence of cross-reactive immunoglobulin (Ig) G to nucleocapsid (N) from common -coronavirus exposure and specific cellular immune responses against SARS-CoV-2 envelope (E), membrane (Mem), N, and S proteins. There was no evidence of underlying innate protection or natural immunity against SARS-CoV-2. Considering that the strength of the cellular immune responses correlated with time since exposure, we speculated that either rapid cellular immune responses or abortive infection resulted in infection being contained below the threshold for direct viral detection or generation of a humoral immune response. We analyzed the characteristics and significance of circulating vaccine-induced IgA in a post-vaccination cohort with a relatively high incidence of breakthrough infection. Higher levels of vaccine-induced IgA were negatively associated with breakthrough infection. Breakthrough Omicron infection increased anti-ancestral S IgA responses more than booster vaccines. Longitudinal analysis of post-infection anti-S IgA decay showcased the durability of infection-induced responses. As reported for IgG responses, vaccination with ancestral SARS-CoV-2 S antigen-imposed imprinting on circulating IgA responses. This research addressees the variability in humoral and cellular immune responses to SARS-CoV-2 and illustrates how the timing and nature of exposure to viral antigens impact the responses generated.
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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 | 0.001 |
| 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".