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Record W2039415919 · doi:10.4161/cbt.29482

Kindler syndrome in mice and men

2014· letter· en· W2039415919 on OpenAlexfundno aff
Elizabeth K. Duperret, Todd W. Ridky

Bibliographic record

VenueCancer Biology & Therapy · 2014
Typeletter
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Cancer InstituteNational Institutes of HealthLakehead University
KeywordsIntegrinFocal adhesionWnt signaling pathwayCancer researchCarcinogenesisCell adhesionGenetically modified mouseCell biologyEpidermis (zoology)TransgeneBiologyInflammationCell adhesion moleculeSignal transductionMedicineImmunologyCellCancerReceptorInternal medicineGeneticsAnatomyGene

Abstract

fetched live from OpenAlex

Kindler syndrome (KS) in humans is a severe skin blistering disease associated with inflammation and increased risk of epidermal squamous cell carcinoma (SCC). This disease is known to be caused by loss-of-function mutations in Kindlin-1, a focal adhesion β-integrin binding protein. Thus far, it has been unclear what specific signaling events occur in KS keratinocytes to promote tumorigenesis, especially since loss of β-integrins and focal adhesion complexes has been previously shown to prevent or delay tumor formation. In the April issue of Nature Medicine, Rognoni and colleagues generate a transgenic mouse lacking Kindlin-1 in the epidermis to model the key features of KS, and show that Kindlin-1 regulates Wnt and TGFβ signaling independent of β-integrins. These β1-integrin-independent functions of Kindlin-1 may contribute to the increased SCC risk in KS patients.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.174
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.346
Teacher spread0.305 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations7
Published2014
Admission routes1
Has abstractyes

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