Antibody responses to Chlamydia trachomatis vaccine candidate antigens in Chlamydia-infected women and correlation with antibody-mediated phagocytosis of elementary bodies
Bibliographic record
Abstract
(CT) antigens in humans in the context of presumed clinical correlates of protection, we used both an IgG1-based ELISA and a conventional total IgG ELISA to evaluate antibody responses. We evaluated responses to five CT outer membrane proteins (PmpE, PmpF, PmpG, PmpH, and MOMP), along with other promising CT antigens (Pgp3 and HSP60), negative control antigens (RecO and AtpE), and CT elementary bodies (EBs) in sera from a well-characterized cohort of 60 women with different CT infection outcomes, including two outcomes that are likely clinical correlates of protective immunity: spontaneous resolution of infection and absence of reinfection after treatment. Furthermore, we used a flow cytometry-based assay to measure antibody-mediated phagocytosis by neutrophils in these sera. Results demonstrated that IgG1 ELISA displayed higher sensitivity than conventional total IgG ELISA in assessing antibody responses to CT EBs and antigens. Pgp3 IgG1 ELISA exhibited the highest sensitivity compared to IgG1 ELISA incorporating CT EBs or other antigens, confirming Pgp3 IgG1 ELISA as an ideal assay for CT antibody detection. Most (95%) sera from women with CT infection outcomes exhibited antibody-mediated phagocytosis of CT EBs, which was significantly correlated with IgG1 antibody responses to MOMP, Pgp3, HSP60, and PmpF. However, neither IgG1 responses to CT antigens and EBs nor antibody-mediated phagocytosis were associated with clinical correlates of protection. These findings suggest that neither CT IgG1 antibody detection nor antibody-mediated phagocytosis will be useful as immune correlates of protection against CT infection in humans.
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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 | 0.001 | 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".