MétaCan
Menu
Back to cohort
Record W2149896027 · doi:10.1128/ec.3.5.1272-1286.2004

Functional Characterization of Myosin I Tail Regions in <i>Candida albicans</i>

2004· article· en· W2149896027 on OpenAlexafffund
Ursula Oberholzer, Tatiana Iouk, David Y. Thomas, Malcolm Whiteway

Bibliographic record

VenueEukaryotic Cell · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFungal and yeast genetics research
Canadian institutionsMcGill UniversityBiotechnology Research Institute
FundersCanadian Institutes of Health Research
KeywordsMyosinBiologyCell biologyHyphaActinCandida albicansEndocytosisFungal proteinMutantBiochemistryCellMicrobiologyGene

Abstract

fetched live from OpenAlex

The molecular motor myosin I is required for hyphal growth in the pathogenic yeast Candida albicans. Specific myosin I functions were investigated by a deletion analysis of five neck and tail regions. Hyphal formation requires both the TH1 region and the IQ motifs. The TH2 region is important for optimal hyphal growth. All of the regions, except for the SH3 and acidic (A) regions that were examined individually, were required for the localization of myosin I at the hyphal tip. Similarly, all of the domains were required for the association of myosin I with pelletable actin-bound complexes. Moreover, the hyphal tip localization of cortical actin patches, identified by both rhodamine-phalloidin staining and Arp3-green fluorescent protein signals, was dependent on myosin I. Double deletion of the A and SH3 domains depolarized the distribution of the cortical actin patches without affecting the ability of the mutant to form hyphae, suggesting that myosin I has distinct functions in these processes. Among the six myosin I tail domain mutants, the ability to form hyphae was strictly correlated with endocytosis. We propose that the uptake of cell wall remodeling enzymes and excess plasma membrane is critical for hyphal formation.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.347

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 head0.010
GPT teacher head0.218
Teacher spread0.208 · 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 designBench or experimental
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

Citations26
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueEukaryotic CellSame topicFungal and yeast genetics researchFrench-language works237,207