Uncovering cellular circuitry controlling temperature-dependent fungal morphogenesis
Bibliographic record
Abstract
Temperature change is a ubiquitous environmental signal, which exerts powerful control over the development and virulence of microbial pathogens. For Candida albicans, the leading fungal pathogen of humans, temperature influences mating, phenotypic switching, resistance to antifungal drugs and the morphogenetic transition from yeast to filamentous growth. C. albicans morphogenesis is profoundly influenced by temperature, and most filament-inducing cues depend on a concurrent increase in temperature to 37°C before morphogenesis can occur, although the molecular mechanisms underpinning this temperature-dependent developmental transition remain largely unknown. We established that the thermally responsive molecular chaperone Hsp90 orchestrates temperature-dependent morphogenesis, via previously uncharacterized cellular circuitry, comprised of the cyclin-dependent kinase Pho85, the cyclin Pcl1 and the transcriptional regulator Hms1. Here we elaborate on Hsp90's pleiotropic effects on temperature-dependent morphogenetic circuitry, and highlight how changes in protein form and function in response to stress complements the diverse repertoire of mechanisms of microbial temperature sensing.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".