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Record W2286284765 · doi:10.1242/jcs.185116

Cell polarity defines three distinct domains in pancreatic beta cells

2016· article· en· W2286284765 on OpenAlexaff
Wan Jun Gan, Michael Zavortink, Christine Ludick, Rachel Templin, Robyn Webb, Richard I. Webb, Wei Ma, Philip Poronnik, Robert G. Parton, Herbert Y. Gaisano, Annette M. Shewan, Peter Thorn

Bibliographic record

VenueJournal of Cell Science · 2016
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of Toronto
FundersAustralian Research CouncilAustralian Diabetes SocietyNational Health and Medical Research CouncilCentre of Excellence in Cognition and its Disorders, Australian Research CouncilDiabetes Australia
KeywordsBiologyCell biologyCiliumBETA (programming language)IsletCell polarityExtracellularCellAnatomyBiochemistry

Abstract

fetched live from OpenAlex

The structural organisation of pancreatic β-cells in the islets of Langerhans is relatively unknown. Here, using three-dimensional (3D) two-photon, 3D confocal and 3D block-face serial electron microscopy, we demonstrate a consistent in situ polarisation of β-cells and define three distinct cell surface domains. An apical domain located at the vascular apogee of β-cells, defined by the location of PAR-3 (also known as PARD3) and ZO-1 (also known as TJP1), delineates an extracellular space into which adjacent β-cells project their primary cilia. A separate lateral domain, is enriched in scribble and Dlg, and colocalises with E-cadherin and GLUT2 (also known as SLC2A2). Finally, a distinct basal domain, where the β-cells contact the islet vasculature, is enriched in synaptic scaffold proteins such as liprin. This 3D analysis of β-cells within intact islets, and the definition of distinct domains, provides new insights into understanding β-cell structure and 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 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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

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 communication0.0010.000
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 head0.015
GPT teacher head0.246
Teacher spread0.231 · 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 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

Citations95
Published2016
Admission routes1
Has abstractyes

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