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Record W2059439380 · doi:10.1007/s12079-013-0211-9

CCN1 is a novel target to reduce the metastasis of melanoma

2013· article· en· W2059439380 on OpenAlexaff
James Hutchenreuther

Bibliographic record

VenueJournal of Cell Communication and Signaling · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective Tissue Growth Factor Research
Canadian institutionsWestern University
Fundersnot available
KeywordsMetastasisMelanomaMedicineCancer researchComputer scienceCancerBioinformaticsBiologyInternal medicine

Abstract

fetched live from OpenAlex

Melanoma is becoming increasingly common in recent years and has a very high mortality rate, owing largely to its highly metastatic nature. It tends to metastasize early in the course of the disease, and after metastasis is resistant to most current therapies. Preclinical data has indicated that heparin administered to patients as an antithrombotic treatment also has anti-metastatic properties. Heparin has been shown to interfere with the binding of the integrin Very Late Antigen 4 (VLA-4) to its ligand Vascular Cell Adhesion Molecule 1 (VCAM-1) and in a recent paper the laboratory of Bendas (Thrombosis and Haemostasis, Prepublished online) demonstrated that CCN1 binds to VLA-4 and interference in this binding by heparin results in reduced strength of the VLA-4/VCAM-1 binding. This indicates that CCN1 might represent a good target for reducing the metastasis, and thus mortality, of melanoma.

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 score0.012
Threshold uncertainty score0.169

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 head0.031
GPT teacher head0.299
Teacher spread0.269 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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