Elevated binding and functional antibody responses to SARS-CoV-2 in infants versus mothers
Bibliographic record
Abstract
Infant antibody responses to viral infection can differ from those in adults. However, data on the specificity and function of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in infants, and direct comparisons between infants and adults are limited. We characterized antibody binding and functionality in convalescent plasma from postpartum women and their infants infected with SARS-CoV-2 from a vaccine-naïve prospective cohort in Nairobi, Kenya. Antibody titers against SARS-CoV-2 Spike, receptor binding domain and N-terminal domain, and Spike-expressing cell-surface staining levels were significantly higher in infants than in mothers. Plasma antibodies from mothers and infants bound to similar regions of the Spike S2 subunit, including the fusion peptide (FP) and stem helix-heptad repeat 2. However, infants displayed higher antibody levels and more consistent antibody escape pathways in the FP region compared to mothers. Finally, infants had significantly higher levels of antibody-dependent cellular cytotoxicity (ADCC), though, surprisingly, neutralization titers between infants and mothers were similar. These results suggest infants develop distinct SARS-CoV-2 binding and functional antibody repertoires and reveal age-related differences in humoral immunity to SARS-CoV-2 infection that could be relevant to protection and COVID-19 disease outcomes.
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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) | 0.003 | 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".