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Record W2188965845 · doi:10.1038/srep17699

Mouse Crumbs3 sustains epithelial tissue morphogenesis in vivo

2015· article· en· W2188965845 on OpenAlexafffund
Lucie Charrier, Elise Loie, Patrick Laprise

Bibliographic record

VenueScientific Reports · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRenal and related cancers
Canadian institutionsUniversité Laval
FundersCanadian Cancer Society Research InstituteCancer Research Society
KeywordsWnt signaling pathwayCell biologyCell polarityEpithelial polarityEpitheliumBiologyIn vivoCellSignal transductionGenetics

Abstract

fetched live from OpenAlex

The human apical protein CRB3 (Crb3 in mouse) organizes epithelial cell polarity. Loss of CRB3 expression increases the tumorogenic potential of cultured epithelial cells and favors metastasis formation in nude mice. These data emphasize the need of in vivo models to study CRB3 functions. Here, we report the phenotypic analysis of a novel Crb3 knockout mouse model. Crb3-deficient newborn mice show improper clearance of airways, suffer from respiratory distress and display perinatal lethality. Crb3 is also essential to maintain apical membrane identity in kidney epithelial cells. Numerous kidney cysts accompany these polarity defects. Impaired differentiation of the apical membrane is also observed in a subset of cells of the intestinal epithelium. This results in improper remodeling of adhesive contacts in the developing intestinal epithelium, thereby leading to villus fusion. We also noted a strong increase in cytoplasmic β-catenin levels in intestinal epithelial cells. β-catenin is a mediator of the Wnt signaling pathway, which is overactivated in the majority of colon cancers. In addition to clarifying the physiologic roles of Crb3, our study highlights that further functional analysis of this protein is likely to provide insights into the etiology of diverse pathologies, including respiratory distress syndrome, polycystic kidney disease and cancer.

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)0.001
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 score0.243
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.010
GPT teacher head0.246
Teacher spread0.236 · 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

Citations56
Published2015
Admission routes2
Has abstractyes

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