A Simple Nematode Infection Model for Studying <i>Candida albicans</i> Pathogenesis
Bibliographic record
Abstract
Candida albicans is an opportunistic fungal pathogen and a model organism to study fungal pathogenesis. It exists as a harmless commensal organism and member of the healthy human microbiome, but can cause life-threatening mucosal and systemic infections. A model host to study C. albicans infection and pathogenesis is the nematode Caenorhabditis elegans. C. elegans is frequently used as a model host to study microbial-host interactions because it can be infected by many human pathogens and there are also close morphological resemblances between the intestinal cells of C. elegans and mammals, where C. albicans infections can occur. This article outlines a detailed methodology for exploiting C. elegans as a host to study C. albicans infection, including a C. elegans egg preparation protocol and an agar-based C. elegans killing protocol to monitor fungal virulence. These protocols can additionally be used to study C. albicans genetic mutants in order to further our understanding of the genes involved in pathogenesis and virulence in C. albicans and the mechanisms of host-microbe interactions. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Preparation of Caenorhabditis elegans eggs Support Protocol 1: Freezing and recovering Caenorhabditis elegans Support Protocol 2: Making superfood agar and OP50 plates Basic Protocol 2: Caenorhabditis elegans/Candida albicans agar killing assay Support Protocol 3: Constructing a worm pick.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".