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Record W2412540739 · doi:10.1042/bcj20160388

Zinc transporter ZIP10 forms a heteromer with ZIP6 which regulates embryonic development and cell migration

2016· article· en· W2412540739 on OpenAlexafffund
KM Taylor, Issa A. Muraina, Brethour Dylan, Gerold Schmitt‐Ulms, Thirayost Nimmanon, Silvia Ziliotto, Peter Kille, Christer Högstrand

Bibliographic record

VenueBiochemical Journal · 2016
Typearticle
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsOccupational Cancer Research CentreUniversity of Toronto
FundersCanadian Institutes of Health ResearchKing's College LondonTenovusWellcome Trust
KeywordsCell biologyZebrafishGene knockdownEpibolyBiologyGSK-3Cell migrationChemistryCellGastrulationSignal transductionGeneEmbryogenesisEmbryoBiochemistry

Abstract

fetched live from OpenAlex

There is growing evidence that zinc and its transporters are involved in cell migration during development and in cancer. In the present study, we show that zinc transporter ZIP10 (SLC39A10) stimulates cell motility and proliferation, both in mammalian cells and in the zebrafish embryo. This is associated with inactivation of GSK (glycogen synthase kinase)-3α and -3β and down-regulation of E-cadherin (CDH1). Morpholino-mediated knockdown of zip10 causes delayed epiboly and deformities of the head, eye, heart and tail. Furthermore, zip10 deficiency results in overexpression of cdh1, zip6 and stat3, the latter gene product driving transcription of both zip6 and zip10 The non-redundant requirement of Zip6 and Zip10 for epithelial to mesenchymal transition (EMT) is consistent with our finding that they exist as a heteromer. We postulate that a subset of ZIPs carrying prion protein (PrP)-like ectodomains, including ZIP6 and ZIP10, are integral to cellular pathways and plasticity programmes, such as EMT.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.238
Teacher spread0.228 · 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

Citations122
Published2016
Admission routes2
Has abstractyes

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