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Record W4317233792 · doi:10.1002/2211-5463.13559

The breast cancer microenvironment and lipoprotein lipase: Another negative notch for a beneficial enzyme?

2023· review· en· W4317233792 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFEBS Open Bio · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaMemorial University of NewfoundlandUniversity of WashingtonBeatrice Hunter Cancer Research InstituteCancer Research Institute
KeywordsLipoprotein lipaseLipaseBreast cancerTumor microenvironmentEnzymeLipid metabolismCancer researchLipoproteinBiochemistryCancerChemistryBiologyInternal medicineCholesterolMedicineTumor cells

Abstract

fetched live from OpenAlex

The energy demand of breast cancers is in part met through the β-oxidation of exogenous fatty acids. Fatty acids may also be used to aid in cell signaling and toward the construction of new membranes for rapidly proliferating tumor cells. A significant quantity of fatty acids comes from the hydrolysis of lipoprotein triacylglycerols and phospholipids by lipoprotein lipase (LPL). The lipid obtained via LPL in the breast tumor microenvironment may thus promote breast tumor growth and development. In this hypothesis article, we introduce LPL, provide a meta-analysis of RNAseq data showing that LPL is associated with poor prognosis, and explain how LPL might play a role in breast cancer prognosis over time.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.911
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 science0.0010.001
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 head0.034
GPT teacher head0.326
Teacher spread0.292 · 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