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Record W4414474864 · doi:10.3390/curroncol32100531

The Role of Intracellular Lipid-Binding Proteins in Digestive System Neoplasms

2025· review· en· W4414474864 on OpenAlexvenueno aff
Christos Kakouratos, Adriana Fernandez Garcia, Pramod Darvin, Hemant M. Kocher

Bibliographic record

VenueCurrent Oncology · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsnot available
FundersNational Institute for Health and Care ResearchNIHR Barts Biomedical Research Centre, Queen Mary University of LondonCancer Research UKBarts Charity
KeywordsIntracellularImmune systemLipid metabolismSecretionSuppressorOxidative phosphorylationGeneProtein–protein interactionCell

Abstract

fetched live from OpenAlex

Intracellular lipid-binding proteins (iLBPs) are key mediators of intracellular transport for fatty acids and retinoids, functioning as lipid chaperones. Beyond lipid transport, iLBPs regulate signalling pathways, gene expression, oxidative balance, and inflammation. Furthermore, they are increasingly recognised for their involvement in gastrointestinal (GI) diseases, especially in cancer. iLBPs are classified into four different subfamilies, each displaying distinct tissue distributions and ligand preferences. Functional roles are context-dependent, for instance, CRABP2 may act as either tumour suppressor or promoter, and FABP4 exhibits metabolic state dependent effects. These proteins also influence drug resistance, immune evasion, and lipid-mediated signalling. Overall, iLBPs extend beyond lipid trafficking to intersect with oncogenic pathways, influence cell fate, and affect treatment response, highlighting their potential as biomarkers and therapeutic targets in GI oncology.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.347
Teacher spread0.317 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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