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Record W2592596297 · doi:10.1128/msphere.00056-17

Staurosporine Induces Filamentation in the Human Fungal Pathogen Candida albicans via Signaling through Cyr1 and Protein Kinase A

2017· article· en· W2592596297 on OpenAlexafffund
Jinglin Lucy Xie, Teresa R. O’Meara, Elizabeth J. Polvi, Nicole Robbins, Leah E. Cowen

Bibliographic record

VenuemSphere · 2017
Typearticle
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchGovernment of CanadaNational Institutes of HealthNational Institute of Allergy and Infectious DiseasesNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsStaurosporineFilamentationCandida albicansVirulenceBiologyCorpus albicansPhenotypic switchingMicrobiologyFungal proteinPathogenVirulence factorCell biologySignal transductionYeastProtein kinase CPhenotypeGeneticsGeneSaccharomyces cerevisiae

Abstract

fetched live from OpenAlex

The impact of fungal pathogens on human health is devastating. One of the most pervasive fungal pathogens is Candida albicans , which kills ~40% of people suffering from bloodstream infections. Treatment of these infections is extremely difficult, as fungi are closely related to humans, and there are limited drugs that kill the fungus without host toxicity. The capacity of C. albicans to transition between yeast and filamentous forms is a key virulence trait. Thus, understanding the genetic pathways that regulate morphogenesis could provide novel therapeutic targets to treat C. albicans infections. Here, we establish the small molecule staurosporine as an inducer of filamentous growth. We unveil distinct regulatory circuitry required for staurosporine-induced filamentation that appears to be unique to this filament-inducing cue. Thus, this work highlights the fact that small molecules, such as staurosporine, can improve our understanding of the pathways required for key virulence programs, which may lead to the development of novel therapeutics.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.327
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2017
Admission routes2
Has abstractyes

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