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Record W2327723244 · doi:10.2741/3937

A distinctive role for galectin-7 in cancer ?

2011· review· en· W2327723244 on OpenAlexafffund
Yves St‐Pierre

Bibliographic record

VenueFrontiers in bioscience · 2011
Typereview
Languageen
FieldImmunology and Microbiology
TopicGalectins and Cancer Biology
Canadian institutionsInstitut National de la Recherche Scientifique
FundersCanadian Institutes of Health Research
KeywordsGalectinGalectin-3CancerMetastasisBiologyCell adhesionCancer researchTumor progressionCancer cellCell biologyCellImmunologyGenetics

Abstract

fetched live from OpenAlex

The galectins are a family of evolutionay-conserved carbohydrate-binding proteins. They are distributed widely in all living organisms and have been implicated in many essential functions including development, differentiation, cell-cell adhesion, cell-matrix interaction, growth regulation, apoptosis. Several members of the galectin family have also been shown to be involved in cancer progression and metastasis. In the case of galectin-7, several studies have reported alterations in its expression pattern during cancer progression. In a variety of tumors, its expression can range from being completely down-regulated to highly up-regulated. Accordingly, its precise role in this field is still debated. The evidence shows that galectin-7 may promote or inhibit cancer development. In this article, we review the data concerning expression and roles of galectin-7 in cancer and propose a comprehensive view of its contribution during cancer progression.

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)0.001
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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.042
GPT teacher head0.323
Teacher spread0.281 · 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

Citations27
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in bioscienceSame topicGalectins and Cancer BiologyFrench-language works237,207