MétaCan
Menu
Back to cohort
Record W2911659955 · doi:10.1111/jcmm.14136

Regulation of <scp>CXCL</scp>1 chemokine and <scp>CSF</scp>3 cytokine levels in myometrial cells by the <scp>MAFF</scp> transcription factor

2019· article· en· W2911659955 on OpenAlexaff
James Saliba, Baptiste Coutaud, Vera Solovieva, Fangshi Lu, Volker Blank

Bibliographic record

VenueJournal of Cellular and Molecular Medicine · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive System and Pregnancy
Canadian institutionsMcGill UniversityMcGill University Health CentreJewish General Hospital
FundersMinistry of Agriculture, Forestry and Fisheries
KeywordsChemokineCCL7CytokineCXCL10CCL3BiologyCell biologyTranscription factorImmunologyCCR1InflammationGeneCCL2Chemokine receptorGenetics

Abstract

fetched live from OpenAlex

Cytokines play key roles in a variety of reproductive processes including normal parturition as well as preterm birth. Our previous data have shown that MAFF, a member of the MAF family of bZIP transcription factors, is rapidly induced by pro-inflammatory cytokines in PHM1-31 myometrial cells. We performed loss-of-function studies in PHM1-31 cells to identify MAFF dependent genes. We showed that knockdown of MAFF significantly decreased CXCL1 chemokine and CSF3 cytokine transcript and protein levels. Using chromatin immunoprecipitation analyzes, we confirmed CXCL1 and CSF3 genes as direct MAFF targets. We also demonstrated that MAFF function in PHM1-31 myometrial cells is able to control cytokine and matrix metalloproteinase gene expression in THP-1 monocytic cells in a paracrine fashion. Our studies provide valuable insights into the MAFF dependent transcriptional network governing myometrial cell function. The data suggest a role of MAFF in parturition and/or infection-induced preterm labour through modulation of inflammatory processes in the microenvironment.

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)0.002
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 score0.072
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.224
Teacher spread0.212 · 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

Citations26
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Cellular and Molecular MedicineSame topicReproductive System and PregnancyFrench-language works237,207