Resistance and Tolerance to Cryptococcal Infection: An Intricate Balance That Controls the Development of Disease
Bibliographic record
Abstract
Cryptococcus neoformans is a ubiquitous environmental yeast and a leading cause of invasive fungal infection in humans. The most recent estimate of global disease burden includes over 200,000 cases of cryptococcal meningitis each year. C. neoformans expresses several virulence factors that may have originally evolved to protect against environmental threats, and human infection may be an unintended consequence of these acquired defenses. Traditionally, C. neoformans has been viewed as a purely opportunistic pathogen that targets severely immune compromised hosts; however, during the past decade the spectrum of susceptible individuals has grown considerably. In addition, the closely related strain C. gattii has recently emerged in North America and preferentially targets individuals with intact immunity. In parallel to the changing epidemiology of cryptococcosis, an increasing role for host immunity in the pathogenesis of severe disease has been elucidated. Initially, the HIV/AIDS epidemic revealed the capacity of C. neoformans to cause host damage in the absence of adaptive immunity. Subsequently, the development and clinical implementation of highly active antiretroviral treatment (HAART) led to recognition of an immune reconstitution inflammatory syndrome (IRIS) in a subset of HIV+ individuals, demonstrating the pathological role of host immunity in disease. A post-infectious inflammatory syndrome (PIIRS) characterized by abnormal T cell-macrophage activation has also been documented in HIV-negative individuals following antifungal therapy. These novel clinical conditions illustrate the highly complex host-pathogen relationship that underlies severe cryptococcal disease and the intricate balance between tolerance and resistance that is necessary for effective resolution. In this article, we will review current knowledge of the interactions between cryptococci and mammalian hosts that result in a tolerant phenotype and consider how this knowledge may translate into improved therapies for affected individuals.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".