Humoral immunity to commensal oral bacteria in human infants: evidence that <i>Streptococcus mitis</i> biovar 1 colonization induces strain-specific salivary immunoglobulin A antibodies
Bibliographic record
Abstract
To define the relationship between salivary SIgA antibodies and commensal oral bacteria, we examined the reactivity of SIgA antibodies from the saliva of four infants with their own colonizing Streptococcus mitis biovar 1 (S. mitis bv 1) clones (ribotypes). Immunoblot analysis was used to examine reactivity of these antibodies with persistent ribotypes isolated from the mouths of the infants over the first year postpartum. Results showed that the pattern of SIgA antibody reactivity with the majority of clones increased in complexity after colonization but that most additional bands were common to other clones, indicating that they represented shared antigens. However, unique bands were identified in 75% of the selected persistent clones. We hypothesized that if strain-specific SIgA antibody was induced in response to colonization of a particular clone and contributed to its elimination from the mouth, then the appearance of unique bands would immediately precede the disappearance of the strain. Seventy-three percent of all unique bands identified in the study fulfilled this criterion. Because the mouth is an open, dynamic environment and multiple factors are believed to play a role in the immune response at mucosal surfaces, it may not be possible to conclusively define the relationship between SIgA antibody and commensal bacteria. However, our data provide evidence that SIgA antibody, reactive with unique antigens of their own colonizing strains, is produced in infants and may point to a role of this antibody in regulating colonization by S. mitis bv 1.
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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".