Stimulation of innate immune resistance leads to clearance of C. neoformans infection in zebrafish \n
Bibliographic record
Abstract
Cryptococcus neoformans is an opportunistic pathogen and a leading cause of life-threatening fungal infections in the immunocompromised.Individuals that are at greater risk are those with defective T-cell mediated immunity such as those with HIV/AIDS.Despite treatment with anti-fungal drugs, mortality remains excessively high and patients experience serious side effects hence the need to explore new therapeutic strategies.Activation of macrophages is essential for the control of cryptococcal infection.However, in the absence of T-cell mediated immunity, activation of macrophages is disrupted and clearance of cryptococcal infection is abrogated.Herein I first report a zebrafish-C.neoformans model of infection and show that zebrafish can clear, control or fail to control cryptococcal infection.I then go on to test whether cytokines or PRR ligands are capable of stimulating innate immune resistance to C. neoformans in zebrafish.I demonstrate that concomitant injection of IFNγ with C. neoformans results in reduced fungal burden and increased fungal clearance.IFNγ increases the recruitment of phagocytes to the site of infection and enhances phagocytosis by macrophages.Macrophage deficient larvae fail to clear or suppress cryptococcal infection despite treatment with IFNγ.In addition, infected macrophages display low lysosomal pH and elevated expression of IL-1β in IFNγ-treated larvae.Although neutrophils take up the fungus, their depletion does not alter cryptococcal burden.Secondly, I demonstrate that S. aureus CWP is a potent inducer of innate defences against C. neoformans.Using chemically digested S. aureus CWP to remove wall teichoic acid or mutants that do not produce wall teichoic acid (tarO) or lipoproteins (lgt), I establish that protective effects of S. aureus CWP require wall teichoic acid but not lipoproteins.Protection by S. aureus CWP are associated with increased recruitment of macrophages but not enhanced phagocytosis or TNFα expression.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".