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Record W2906086927 · doi:10.1016/j.tice.2018.12.005

Non-integrin laminin receptors in epithelia

2018· review· en· W2906086927 on OpenAlexafffund
Gabriel Cloutier, Amélie Sallenbach-Morrissette, Jean‐François Beaulieu

Bibliographic record

VenueTissue and Cell · 2018
Typereview
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsDystroglycanLamininBiologyIntegrinCell biologyExtracellular matrixReceptorCollagen receptorCell adhesionBasement membraneGlycoproteinContext (archaeology)CellMolecular biologyBiochemistry

Abstract

fetched live from OpenAlex

The interactions between cells and the extracellular matrix (ECM) play a major role in normal and pathological conditions. The ECM can modulate several biological functions including cell proliferation, adhesion, differentiation and survival through its interactions with cell receptors. Laminins are one of the most important glycoproteins present in basement membranes, a type of ECM. The pattern of expression of its different isoforms depends on the spatiotemporal organization of each tissue. While integrins are the most studied laminin receptors, other non-integrin laminin receptors are also involved. This review focuses on two particular non-integrin laminin receptors in the epithelial context: dystroglycan and 37/67 laminin receptor (37/67LR). Dystroglycan is a two-subunit protein discovered in the muscle as part of the dystrophin-associated glycoprotein complex. This protein can also be found in many epithelia where its roles are variable. The 37/67LR is a still incompletely understood laminin receptor that is important to regulate intestinal epithelial cell function and could be involved in various pathological conditions.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.043
GPT teacher head0.364
Teacher spread0.321 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2018
Admission routes2
Has abstractyes

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