MétaCan
Menu
Back to cohort
Record W2091217195 · doi:10.1074/jbc.m110.170076

Brain Fatty Acid-binding Protein and ω-3/ω-6 Fatty Acids

2010· article· en· W2091217195 on OpenAlexafffund
Raja Mita, Michaël Beaulieu, Catherine J. Field, Roseline Godbout

Bibliographic record

VenueJournal of Biological Chemistry · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPeroxisome Proliferator-Activated Receptors
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsBiochemistryFatty acidChemistryFatty acid-binding proteinGene

Abstract

fetched live from OpenAlex

Malignant gliomas (MG) are highly infiltrative tumors that consistently recur despite aggressive treatment. Brain fatty acid-binding protein (FABP7), which binds docosahexaenoic acid (DHA) and arachidonic acid (AA), localizes to sites of tumor infiltration and is associated with a poor prognosis in MG. Manipulation of FABP7 expression in MG cell lines affects cell migration, suggesting a role for FABP7 in tumor infiltration and recurrence. Here, we show that DHA inhibits and AA stimulates migration in an FABP7-dependent manner in U87 MG cells. We demonstrate that DHA binds to and sequesters FABP7 to the nucleus, resulting in decreased cell migration. This anti-migratory effect is partially dependent on peroxisome proliferator-activated receptor γ, a DHA-activated transcription factor. Conversely, AA-bound FABP7 stimulates cell migration by activating cyclooxygenase-2 and reducing peroxisome proliferator-activated receptor γ levels. Our data provide mechanistic insight as to why FABP7 is associated with a poor prognosis in MG and suggest that relative levels of DHA and AA in the tumor environment can make a profound impact on tumor growth properties. We propose that FABP7 and its fatty acid ligands may be key therapeutic targets for controlling the dissemination of MG cells within the brain.

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)0.001
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 score0.013
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.001
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 head0.013
GPT teacher head0.252
Teacher spread0.239 · 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

Citations115
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Biological ChemistrySame topicPeroxisome Proliferator-Activated ReceptorsFrench-language works237,207