Humoral Immune Correlates for Prevention of Postnatal Cytomegalovirus Acquisition
Bibliographic record
Abstract
BACKGROUND: Development of a cytomegalovirus (CMV) vaccine is a high priority. However, the ability of antibodies to protect against CMV infection is not well characterized. Studies of maternal antibodies in infants offer the potential to identify humoral correlates of protection against postnatal acquisition. METHODS: This hypothesis-generating study analyzed 29 Ugandan mother-infant pairs that were followed weekly for CMV acquisition. Seventeen mothers and no infants were infected with human immunodeficiency virus (HIV). We evaluated the association between CMV-specific immunoglobulin G (IgG) responses in mothers at the time of delivery and their infants' CMV status at 6 months of age. We also assessed levels of CMV-specific IgG in infants at 6 weeks of age. CMV-specific IgG responses in the mother-infant pairs were then analyzed on the basis of perinatal HIV exposure. RESULTS: We found similar levels of multiple CMV glycoprotein-specific IgG binding specificities and functions in mothers and infants, irrespective of perinatal HIV exposure or infant CMV status at 6 months of age. However, the glycoprotein B-specific IgG titer, measured by 2 distinct assays, was higher in infants without CMV infection and was moderately associated with delayed CMV acquisition. CONCLUSIONS: These data suggest that high levels of glycoprotein B-specific IgG may contribute to the partial protection against postnatal CMV infection afforded by maternal antibodies, and they support the continued inclusion of glycoprotein B antigens in CMV vaccine candidates.
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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 | 0.001 | 0.002 |
| 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) | 0.002 | 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".