Transcriptional regulation of carbohydrate metabolism in «Candida albicans»
Bibliographic record
Abstract
Glycolysis is a key metabolic pathway that is fundamental to the ability of organisms to assimilate carbon sources. Transcriptional control is a significant mechanism of regulation of glycolysis, although the transcription factors controlling this process in eukaryotes are largely unknown outside the facultative anaerobe Saccharomyces cerevisiae. Since S. cerevisiae exhibits a uniquely fermentative lifestyle due to an evolutionarily-driven glucose repression circuit, carbohydrate regulation needs to be studied in aerobic species such the facultative aerobe Candida albicans. This human pathogen is known to rely on glycolysis for the progression of systemic infections. In this thesis I 1) validate constructs that can be used for location profiling in C. albicans, 2) demonstrate the conservation of protein-protein interactions between the SAGA chromatin remodeling complex and Gal4p even though Gal4p has altered its role within the Saccharomycotina subphylum, and 3) characterize two key glycolytic regulators in C. albicans, demonstrating their importance for fermentative growth and virulence. My findings further illustrate the plasticity of regulatory circuits and highlight differences in the regulation of carbohydrate metabolism between S. cerevisiae and aerobic eukaryotic cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".