<i>Candida albicans</i>: a historical overview of investigations into an important human pathogen
Bibliographic record
Abstract
In recent decades, the study of the opportunistic pathogenic fungus, Candida albicans, has been revolutionized by genomics, transforming our understanding of its molecular biology, pathogenicity, and modes of drug resistance. In this review, our effort is to trace the historical development of C. albicans research, from early clinical observations to modern high-throughput genomic techniques. Advances in molecular biology, transcriptomics, and genome editing, including CRISPR-Cas9, have had a significant impact on the genetic tools available for studying this pathogen. The impact of whole-genome sequencing, functional genomics, and single-cell transcriptomics on the study of C. albicans, alongside the role of fungal population genomics in tracking evolutionary adaptations, have resulted in key insights. Here we discuss the ongoing challenge of antifungal resistance and the implications of new technologies in combating invasive candidiasis. As we move into a new era of precision mycology, integrating multi-omics approaches will further enhance our ability to understand and control C. albicans infections.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".