Dendritic Cell-Based Immunization Ameliorates Pulmonary Infection with Highly Virulent Cryptococcus gattii
Bibliographic record
Abstract
Cryptococcosis due to a highly virulent fungus, Cryptococcus gattii, emerged as an infectious disease on Vancouver Island in Canada and surrounding areas in 1999, causing deaths among immunocompetent individuals. Previous studies indicated that C. gattii strain R265 isolated from the Canadian outbreak had immune avoidance or immune suppression capabilities. However, protective immunity against C. gattii has not been identified. In this study, we used a gain-of-function approach to investigate the protective immunity against C. gattii infection using a dendritic cell (DC)-based vaccine. Bone marrow-derived dendritic cells (BMDCs) efficiently engulfed acapsular C. gattii (Δcap60 strain), which resulted in their expression of costimulatory molecules and inflammatory cytokines. This was not observed for BMDCs that were cultured with encapsulated strains. When Δcap60 strain-pulsed BMDCs were transferred to mice prior to intratracheal R265 infection, significant amelioration of pathology, fungal burden, and the survival rate resulted compared with those in controls. Multinucleated giant cells (MGCs) that engulfed fungal cells were significantly increased in the lungs of immunized mice. Interleukin 17A (IL-17A)-, gamma interferon (IFN-γ)-, and tumor necrosis factor alpha (TNF-α)-producing lymphocytes were significantly increased in the spleens and lungs of immunized mice. The protective effect of this DC vaccine was significantly reduced in IFN-γ knockout mice. These results demonstrated that an increase in cytokine-producing lymphocytes and the development of MGCs that engulfed fungal cells were associated with the protection against pulmonary infection with highly virulent C. gattii and suggested that IFN-γ may have been an important mediator for this vaccine-induced protection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".