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Record W3033183284 · doi:10.1111/jcmm.15365

SIRT2 suppresses expression of inflammatory factors via Hsp90‐glucocorticoid receptor signalling

2020· article· en· W3033183284 on OpenAlexaff
Kai Sun, Xuan Wang, Na Fang, Ao Xu, Yao Lin, Xiaofang Zhao, Adil J. Nazarali, Shaoping Ji

Bibliographic record

VenueJournal of Cellular and Molecular Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicSirtuins and Resveratrol in Medicine
Canadian institutionsUniversity of Saskatchewan
FundersNatural Science Foundation of Henan ProvinceNational Natural Science Foundation of China
KeywordsGlucocorticoid receptorHsp90GlucocorticoidSignallingCell biologyReceptorInflammationCancer researchSIRT2Signal transductionBiologyMedicineEndocrinologyInternal medicineImmunologyHeat shock proteinGeneGeneticsSirtuin

Abstract

fetched live from OpenAlex

-dependent deacetylase that deacetylates a diverse array of protein substrates and is involved in many cellular processes, including regulation of inflammation. However, its precise role in the inflammatory process has not completely been elucidated. Here, we identify heat-shock protein 90α (Hsp90α) as novel substrate of SIRT2. Functional investigation suggests that Hsp90 is deacetylated by SIRT2, such that overexpression and knock-down of SIRT2 altered the acetylation level of Hsp90. This subsequently resulted in disassociation of Hsp90 with glucocorticoid receptor (GR), and translocation of GR to the nucleus. This observation was further confirmed by glucocorticoid response element (GRE)-driven reporter assay. Nuclear translocation of GR induced by SIRT2 overexpression repressed the expression of inflammatory cytokines, which were even more prominent under lipopolysaccharide (LPS) stimulation. Conversely, SIRT2 knock-down resulted in the up-regulation of cytokine expression. Mutation analysis indicated that deacetylation of Hsp90 at K294 is critical for SIRT2-mediated regulation of cytokine expression. These data suggest that SIRT2 reduces the extent of LPS-induced inflammation by suppressing the expression of inflammatory factors via SIRT2-Hsp90-GR axis.

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 score0.042
Threshold uncertainty score0.642

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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

Citations28
Published2020
Admission routes1
Has abstractyes

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