Targeting leukocidin-mediated immune evasion protects mice from <i>Staphylococcus aureus</i> bacteremia
Bibliographic record
Abstract
Staphylococcus aureus is responsible for various diseases in humans, and recurrent infections are commonly observed. S. aureus produces an array of bicomponent pore-forming toxins that target and kill leukocytes, known collectively as the leukocidins. The contribution of these leukocidins to impair the development of anti-S. aureus adaptive immunity and facilitate reinfection is unclear. Using a murine model of recurrent bacteremia, we demonstrate that infection with a leukocidin mutant results in increased levels of anti-S. aureus antibodies compared with mice infected with the WT parental strain, indicating that leukocidins negatively impact the generation of anti-S. aureus antibodies in vivo. We hypothesized that neutralizing leukocidin-mediated immune subversion by vaccination may shift this host-pathogen interaction in favor of the host. Leukocidin-immunized mice produce potent leukocidin-neutralizing antibodies and robust Th1 and Th17 responses, which collectively protect against bloodstream infections. Altogether, these results demonstrate that blocking leukocidin-mediated immune evasion can promote host protection against S. aureus bloodstream 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) | 0.001 | 0.000 |
| 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".