<i>Trichomonas vaginalis</i>Infection Induces Vaginal CD4<sup>+</sup>T-Cell Infiltration in a Mouse Model: A Vaccine Strategy to Reduce Vaginal Infection and HIV Transmission
Bibliographic record
Abstract
BACKGROUND: Complications related to the diagnosis and treatment of Trichomonas vaginalis infection, as well as the association between T. vaginalis infection and increased transmission of and susceptibility to human immunodeficiency virus, highlight the need for alternative interventions. We tested a human-safe, aluminum hydroxide-adjuvanted whole-cell T. vaginalis vaccine for efficacy in a BALB/c mouse model of vaginal infection. METHODS: A whole-cell T. vaginalis vaccine was administered subcutaneously to BALB/c mice, using a prime-boost vaccination schedule. CD4(+) T-cell infiltration in the murine vaginal tissue and local and systemic levels of immunoglobulins were measured at time points up to 4 weeks following infection. RESULTS: Vaccination reduced the incidence and increased the clearance of T. vaginalis infection and induced both systemic and local humoral immune responses. CD4(+) T cells were detected in vaginal tissues following intravaginal infection with T. vaginalis but were not seen in uninfected mice. The presence of CD4(+) T cells following T. vaginalis infection can potentially increase susceptibility to and transmission of human immunodeficiency virus. CONCLUSIONS: The vaccine induces local and systemic immune responses and confers significantly greater protection against vaginal infection than seen in unvaccinated mice (P < .005). These data support the potential for a human vaccine against T. vaginalis infection that could also influence the incidence of human immunodeficiency virus infection.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".