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Record W2142189167 · doi:10.1091/mbc.e05-11-1019

Delineation of the Roles Played by RasG and RasC in cAMP-dependent Signal Transduction during the Early Development of<i>Dictyostelium discoideum</i>

2006· article· en· W2142189167 on OpenAlexaff
Parvin Bolourani, George B. Spiegelman, Gerald Weeks

Bibliographic record

VenueMolecular Biology of the Cell · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsUniversity of British Columbia
FundersMinistry of Science Research and Technology
KeywordsDictyostelium discoideumChemotaxisBiologyAdenylyl cyclaseDictyosteliumSignal transductionCell biologyTransduction (biophysics)GeneGeneticsBiochemistryReceptor

Abstract

fetched live from OpenAlex

On starvation, the cellular slime mold Dictyostelium discoideum initiates a program of development leading to formation of multicellular structures. The initial cell aggregation requires chemotaxis to cyclic AMP (cAMP) and relay of the cAMP signal by the activation of adenylyl cyclase (ACA), and it has been shown previously that the Ras protein RasC is involved in both processes. Insertional inactivation of the rasG gene resulted in delayed aggregation and a partial inhibition of early gene expression, suggesting that RasG also has a role in early development. Both chemotaxis and ACA activation were reduced in the rasG- cells, but the effect on chemotaxis was more pronounced. When the responses of rasG- cells to cAMP were compared with the responses of rasC- and rasC- rasG- strains, generated in otherwise isogenic backgrounds, these studies revealed that signal transduction through RasG is more important in chemotaxis and early gene expression, but that signal transduction through RasC is more important in ACA activation. Because the loss of either of the two Ras proteins alone did not result in a total loss of signal output down either of the branches of the cAMP signal-response pathway, there appears to be some overlap of function.

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 score0.011
Threshold uncertainty score0.260

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 head0.002
GPT teacher head0.188
Teacher spread0.186 · 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

Citations82
Published2006
Admission routes1
Has abstractyes

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