Avidity of pertussis toxin antibodies following vaccination with genetically versus chemically detoxified pertussis toxin-containing vaccines during pregnancy
Bibliographic record
Abstract
Background Both the quantity and quality of circulating anti-pertussis toxin antibodies are important for protection against severe pertussis. We compared the avidity of PT-IgG antibodies in pregnant women and their infants following vaccination during pregnancy with pertussis vaccines containing genetically-detoxified pertussis toxin (PTgen) or chemically-detoxified PT (PTchem). Methods We analyzed serum samples collected earlier from pregnant women (at delivery) and their infants (at birth and 2 months of age) participating in a clinical trial where pregnant women had been vaccinated during pregnancy with recombinant acellular pertussis vaccine containing 1 µg PTgen (standalone, ap1gen, [n=37], or combined to tetanus and diphtheria, Tdap1gen [n=34]), 2 µg PTgen (Tdap2gen, n=35), or 5 µg PTgen (TdaP5gen, n=34), or acellular pertussis vaccine containing 8 µg PTchem (Tdap8chem, n=35). Avidity was assessed by adding increasing concentrations (0.25, 0.5, 1, 1.5, 2, and 3 M) of NH4SCN as a bond-breaking agent and measuring PT-IgG levels by ELISA. Findings Compared with Tdap8chem, TdaP5gen vaccination was associated with significantly higher total absolute avidity (p<0.001) and medium-high to very-high avidity PT-IgG levels (p≤0.02) in mothers at delivery, infants at birth and infants at 2 months of age. Avidity was comparable to Tdap8chem after vaccination with the low-dose PTgen formulations (ap1gen, Tdap1gen or Tdap2gen). There were no differences for vaccination during the 2nd or 3rd trimester of pregnancy. Interpretation Compared with chemically detoxified vaccines, vaccination during pregnancy with recombinant genetically detoxified acellular pertussis vaccine at lower PT concentration provides infants with at least similar or higher quality PT-IgG antibodies. Consequently, recombinant pertussis vaccines may offer comparable or better protection against pertussis.
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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 | 0.002 |
| 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) | 0.001 | 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".