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Protein clustering for cell polarity: Par-3 as a paradigm

2017· preprint· en· W2752651598 on OpenAlexaff
Tony Harris

Bibliographic record

VenueF1000Research · 2017
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCell polarityCentrosomeCaenorhabditis elegansScaffold proteinMicrotubuleCell biologyBiologyCytoskeletonPolarity (international relations)PhosphoproteomicsPhosphorylationCellNeuroscienceProtein kinase ASignal transductionProtein phosphorylationGeneticsCell cycleGene

Abstract

fetched live from OpenAlex

The scaffold protein Par-3 (Drosophila Bazooka) is a central organizer of cell polarity across animals. This review focuses on how the clustering of Par-3 contributes to cell polarity. It begins with the Par-3 homo-oligomerization mechanism and its regulation by Par-1 phosphorylation. The role of polarized cytoskeletal networks in distributing Par-3 clusters to one end of the cell is then discussed, as is the subsequent maintenance of polarized Par-3 clusters through hindered mobility and inhibition from the opposite pole. Finally, specific roles of Par-3 clusters are reviewed, including the bundling of microtubules, the cortical docking of centrosomes, the growth and positioning of cadherin–catenin clusters, and the inhibition of the Par-6–aPKC kinase cassette. Examples are drawn from Drosophila, Caenorhabditis elegans, mammalian cell culture, and biochemical studies.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0010.004
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.002

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 head0.048
GPT teacher head0.359
Teacher spread0.310 · 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 source (direct Gemma or distilled Codex), 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

Citations33
Published2017
Admission routes1
Has abstractyes

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