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Record W3137910612 · doi:10.1139/bcb-2020-0197

Formononetin protects against concanavalin-A-induced autoimmune hepatitis in mice through its anti-apoptotic and anti-inflammatory properties

2021· article· en· W3137910612 on OpenAlexvenueno aff
Guangwei Liu, Wenxia Zhao, Jiameng Bai, Jianjiao Cui, Haowei Liang, Baoping Lu

Bibliographic record

VenueBiochemistry and Cell Biology · 2021
Typearticle
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsnot available
Fundersnot available
KeywordsConcanavalin AProinflammatory cytokineApoptosisChemistryAutoimmune hepatitisInflammasomePharmacologyHepatitisBiochemistryMolecular biologyReceptorImmunologyBiologyInflammation

Abstract

fetched live from OpenAlex

Autoimmune hepatitis (AIH) is a chronic inflammatory liver disease that seriously threatens the health of humans globally. Formononetin (FMN) is a natural herb extract with multiple biological functions. In this study, an experimental model of AIH was established in mice through the use of concanavalin A (ConA). To investigate the effects of FMN on ConA-induced hepatitis, the mice were pretreated with 50 or 100 mg/kg body mass of FMN. The results show that FMN alleviated ConA-induced liver injury of mice in a dose-dependent manner. Moreover, pretreatment with FMN inhibited the apoptosis of hepatocytes in the ConA-treated mice through downregulating the expression of pro-apoptotic proteins (Bax, cleaved caspase 9, and cleaved caspase 3) and upregulating the expression of anti-apoptotic protein (Bcl-2). It was also found that the levels of proinflammatory cytokines were greatly reduced in the serum and liver tissues of mice pretreated with FMN. Further studies showed that FMN reduced the level of phosphorylated nuclear factor kappa B (p-NF-κB) p65 and enhanced the level of IκBα (inhibitor of NF-κB), suggesting that FMN inhibits the activation of the NF-κB signaling pathway. In addition, FMN inhibited activation of the NOD-like receptor protein 3 (NLRP3) inflammasome. Therefore, FMN could be a promising agent for the treatment of AIH.

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 score0.044
Threshold uncertainty score0.657

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 head0.018
GPT teacher head0.230
Teacher spread0.213 · 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

Citations30
Published2021
Admission routes1
Has abstractyes

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