Selection for a CEACAM Receptor-Specific Binding Phenotype during Neisseria gonorrhoeae Infection of the Human Genital Tract
Bibliographic record
Abstract
Infections by Neisseria gonorrhoeae are increasingly common, are often caused by antibiotic-resistant strains, and can result in serious and lasting sequelae, prompting the reemergence of gonococcal disease as a leading global health concern. N. gonorrhoeae is a human-restricted pathogen that primarily colonizes urogenital mucosal surfaces. Disease progression varies greatly between the sexes: men usually present with symptomatic infection characterized by a painful purulent urethral discharge, while in women, the infection is often asymptomatic, with the most severe pathology occurring when the bacteria ascend from the lower genital tract into the uterus and fallopian tubes. Classical clinical studies demonstrated that clinically infectious strains uniformly express Opa adhesins; however, their specificities were unknown at the time. While in vitro studies have since identified CEACAM proteins as the primary target of Opa proteins, the gonococcal specificity for this human family of receptors has not been addressed in the context of natural infection. In this study, we characterize a collection of low-passage-number clinical-specimen-derived N. gonorrhoeae isolates for Opa expression and assess their CEACAM-binding profiles. We report marked in vivo selection for expression of phase-variable Opa proteins that bind CEACAM1 and CEACAM5 but selection against expression of Opa variants that bind to the neutrophil-restricted decoy receptor CEACAM3. This is the first study showing phenotypic selection for distinct CEACAM-binding phenotypes in vivo, and it supports the opposing functions of CEACAMs that facilitate infection versus driving inflammation within the genital tract.
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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 | 0.000 |
| 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".