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Record W2278501697 · doi:10.1089/jmf.2015.3535

Coenzyme Q10 Exerts Anti-Inflammatory Activity and Induces Treg in Graft Versus Host Disease

2016· article· en· W2278501697 on OpenAlexaff
Seung‐Hoon Lee, Min-Jung Park, Sung-hee Lee, Mi‐La Cho

Bibliographic record

VenueJournal of Medicinal Food · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCoenzyme Q10 studies and effects
Canadian institutionsImpact
Fundersnot available
KeywordsCoenzyme Q10Flow cytometryGraft-versus-host diseaseImmunologyTumor necrosis factor alphaInterferonReal-time polymerase chain reactionDiseaseBiologyMedicineGeneInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

The objective of this study was to determine whether coenzyme Q10 (CoQ10) can reduce the severity of graft versus host disease (GVHD) by inducing regulatory T cells (Tregs). CoQ10 or vehicle was orally administrated once a day for 22 days to mice with GVHD. We measured the alloresponse of the T cells and the GVHD clinical scores. Real-time polymerase chain reaction was used to examine messenger RNA (mRNA) level. Flow cytometry and enzyme-linked immunosorbent assay were used to evaluate protein expression. CoQ10 reduced the T-cell alloresponse and the expression of interferon (IFN)-γ and interleukin (IL)-17. The severity of GVHD and gene expressions of IL-6 and tumor necrosis factor (TNF)-α decreased with CoQ10 treatment. Furthermore, CoQ10 promoted weight gain and survival in GVHD mice. Flow cytometry revealed that CoQ10 dose dependently induced Treg differentiation, but FK506, an immunosuppressive drug, decreased Treg differentiation dose dependently. In conclusion, CoQ10 downregulates the alloreactivity of T cells and reduces GVHD severity, enhancing the differentiation of Tregs.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.753
Threshold uncertainty score0.334

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 head0.012
GPT teacher head0.253
Teacher spread0.241 · 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

Citations13
Published2016
Admission routes1
Has abstractyes

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