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Record W2082522809 · doi:10.1534/genetics.111.132449

Cell Architecture: Surrounding Muscle Cells Shape Gland Cell Morphology in the <i>Caenorhabditis elegans</i> Pharynx

2011· article· en· W2082522809 on OpenAlexafffund
Wahyu Hendrati Raharjo, Vikas Ghai, Aidan Dineen, Michael J. Bastiani, Jeb Gaudet

Bibliographic record

VenueGenetics · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsUniversity of CalgaryAlberta Children's Hospital
FundersNational Institutes of HealthCanadian Institutes of Health ResearchAlberta InnovatesNational Center for Research ResourcesCanada Research Chairs
KeywordsBiologyCaenorhabditis elegansPharynxPharyngeal musclesAnatomyMutantCell biologyGeneticsGene

Abstract

fetched live from OpenAlex

The acquisition and maintenance of shape is critical for the normal function of most cells. Here we investigate the morphology of the pharyngeal glands of Caenorhabditis elegans. These unicellular glands have long cellular processes that extend discrete lengths through the pharyngeal musculature and terminate at ducts connected to the pharyngeal lumen. From a genetic screen we identified several mutants that affect pharyngeal gland morphology. The most severe such mutant is an allele of sma-1, which encodes a β-spectrin required for embryonic elongation, including elongation of the pharynx. In sma-1 mutants, gland projections form normally but become increasingly abnormal over time, acquiring additional branches, outgrowths, and swelling, suggestive of hypertrophy. Rather than acting in pharyngeal glands, sma-1 functions in the surrounding musculature, suggesting that pharyngeal muscles play a critical role in maintenance of gland morphology by restricting their growth, and analysis of other mutants known to affect pharyngeal muscles supports this hypothesis. We suggest that gland morphology is maintained by a balance of forces from the muscles and the glands.

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 categoriesMeta-epidemiology (narrow)
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 score0.047
Threshold uncertainty score1.000

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 science0.0010.000
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 head0.014
GPT teacher head0.205
Teacher spread0.191 · 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.

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

Citations16
Published2011
Admission routes2
Has abstractyes

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