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Record W1973561492 · doi:10.1371/journal.pone.0071336

Interleukin-10 Inhibits Lipopolysaccharide Induced miR-155 Precursor Stability and Maturation

2013· article· en· W1973561492 on OpenAlexafffund
Sylvia T. Cheung, Eva So, David Chang, Andrew Ming‐Lum, Alice Mui

Bibliographic record

VenuePLoS ONE · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsVancouver Coastal Health Research InstituteUniversity of British ColumbiaVancouver Coastal Health
FundersCanadian Institutes of Health Research
KeywordsmiR-155LipopolysaccharidemicroRNACell biologyTranscription factorCytokineSTAT3Regulation of gene expressionSuppressor of cytokine signaling 1Gene expressionInterleukin 6ChemistryBiologySignal transductionImmunologyGeneGeneticsSuppressor

Abstract

fetched live from OpenAlex

The anti-inflammatory cytokine interleukin-10 (IL-10) is essential for attenuating the inflammatory response, which includes reducing the expression of pro-inflammatory microRNA-155 (miR-155) in lipopolysaccharide (LPS) activated macrophages. miR-155 enhances the expression of pro-inflammatory cytokines such as TNFα and suppresses expression of anti-inflammatory molecules such as SOCS1. Therefore, we examined the mechanism by which IL-10 inhibits miR-155. We found that IL-10 treatment did not affect the transcription of the miR-155 host gene nor the nuclear export of pre-miR-155, but rather destabilized both pri-miR-155 and pre-miR-155 transcripts, as well as interfered with the final maturation of miR-155. This inhibitory effect of IL-10 on miR-155 expression involved the contribution of both the STAT3 transcription factor and the phosphoinositol phosphatase SHIP1. This is the first report showing evidence that IL-10 regulates miRNA expression post-transcriptionally.

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)0.000
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 score0.010
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.028
GPT teacher head0.224
Teacher spread0.196 · 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

Citations43
Published2013
Admission routes2
Has abstractyes

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