A CARD9 deficiency mouse model recapitulates human chronic CNS candidiasis identifying defective monocytic cell responses in immunopathogenesis
Bibliographic record
Abstract
Human Caspase Recruitment Domain Containing Protein 9 (CARD9) deficiency predisposes to invasive fungal disease, particularly by Candida spp. CARD9 deficiency causes chronic central nervous system (CNS) candidiasis. Currently, no animal model recapitulates the chronicity of disease, precluding a better understanding of immunopathogenesis. We established a knock-in mouse homozygous for the recurring p.Y91H mutation (Y91HKI) and, in parallel to Card9-/- mice, titrated the intravenous fungal inoculum to the CARD9 genotype to develop a model of chronic invasive candidiasis. Strikingly, CARD9-deficient mice had predominantly CNS involvement, with neurological symptoms appearing late during infection and progressive brain fungal burden in the absence of fulminant sepsis, reflecting the human syndrome. Mononuclear cell aggregation at fungal lesions in the brain correlated with increased MHCII+Ly6C+ monocyte numbers at day 1 after infection in WT and Y91HKI mice, but not in Card9-/- mice. At day 4 after infection, neutrophils and additional Ly6C+ monocytes were recruited to the CARD9-deficient brain. As in humans, Y91HKI mutant mice demonstrated cerebral multinucleated giant cells and granulomata. Subtle immunologic differences between the hypomorphic (p.Y91H) and null mice were noted, perhaps explaining some of the variability seen in humans. Our work established a disease-recapitulating animal model to specifically decipher chronic CNS candidiasis due to CARD9 deficiency.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".