Protective Immunity to<i>Chlamydia trachomatis</i>Genital Infection: Evidence from Human Studies
Bibliographic record
Abstract
Background. Some screening and treatment programs implemented to control Chlamydia trachomatis genital infections and their complications have shown initial reductions in infection prevalence, followed by increases to preprogram levels or higher. One hypothesis is that treatment shortens duration of infection, attenuates development of protective immunity, and thereby, increases risk of reinfection. Methods. A literature review was undertaken to assess evidence supporting the concept of protective immunity,its characteristics, and its laboratory correlates in human chlamydial infection. The discussion is organized around key questions formulated in preparation for the Chlamydia Immunology and Control Expert Advisory Meeting held by the Centers for Disease Control and Prevention in April 2008. Results. Definitive human studies are not available, but cross-sectional studies show that chlamydia prevalence,organism load, and concordance rates in couples decrease with age, and organism load is lower in those with repeat infections, supporting the concept of protective immunity. The protection appears partial and can be overcome after reexposure, similar to what has been found in rodent models of genital infection. No data are available to define the duration of infection required to confer a degree of immunity or the time course of immunity after resolution of untreated infection. In longitudinal studies involving African sex workers, a group presumed to have frequent and ongoing exposure to chlamydial infection, interferon-g production by peripheral blood mononuclear cells in response to chlamydial heat-shock protein 60 was associated with low risk of incident infection.In cross-sectional studies, relevant T helper 1-type responses were found in infected persons, paralleling the studies in animal models. Conclusions. The data support the concept that some degree of protective immunity against reinfection develops after human genital infection, although it appears, at best, to be partial. It is likely that factors besides population levels of immunity contribute to trends in prevalence observed in screening and treatment programs.Future studies of protective immunity in humans will require longitudinal follow-up of individuals and populations,frequent biological and behavioral sampling, and special cohorts to help control for exposure.
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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 | 0.026 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".