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Record W3000328267 · doi:10.1038/s41598-019-57294-x

HDAC10 deletion promotes Foxp3+ T-regulatory cell function

2020· article· en· W3000328267 on OpenAlexfundno aff
Satinder Dahiya, Ulf H. Beier, Liqing Wang, Rongxiang Han, Jing Jiao, Tatiana Akimova, Alessia Angelin, Douglas C. Wallace, Wayne W. Hancock

Bibliographic record

VenueScientific Reports · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHistone Deacetylase Inhibitors Research
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesU.S. Department of Health and Human ServicesNational Institutes of HealthMcGill UniversityAmerican Society of NephrologyNational Institute of Neurological Disorders and StrokeNational Institute of Mental Health
KeywordsHDAC10FOXP3Cancer researchHistone deacetylaseHistoneBiologyImmune systemImmunologyGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Foxp3 + T-regulatory (Treg) cells are capable of suppressing immune responses. Lysine acetylation is a key mechanism of post-translational control of various transcription factors, and when acetylated, Foxp3 is stabilized and transcriptionally active. Therefore, understanding the roles of various histone/protein deacetylases (HDAC) are key to promoting Treg-based immunotherapy. Several of the 11 classical HDAC enzymes are necessary for optimal Treg function while others are dispensable. We investigated the effect of HDAC10 in murine Tregs. HDAC10 deletion had no adverse effect on the health of mice, which retained normal CD4 + and CD8 + T cell function. However, HDAC10 −/− Treg exhibited increased suppressive function in vitro and in vivo . C57BL/6 Rag1 −/− mice adoptively transferred with HDAC10 −/− but not wild Treg, were protected from developing colitis. HDAC10 −/− but not wild-type mice receiving fully MHC-mismatched cardiac transplants became tolerant and showed long-term allograft survival (>100 d). We conclude that targeting of HDAC10 may be of therapeutic value for inflammatory disorders including colitis and also for transplantation.

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)0.001
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 score0.140
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.012
GPT teacher head0.236
Teacher spread0.224 · 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

Citations77
Published2020
Admission routes1
Has abstractyes

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