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Record W2391193595

Effects of Resveratrol on Expression of PPARγ and Related Inflammatory Factors in Rabbits with Atherosclerosis

2013· article· en· W2391193595 on OpenAlexaff
Jing Ruan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCircular RNAs in diseases
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsResveratrolApoptosisFas ligandMessenger RNAEndocrinologyTUNEL assayTranscription (linguistics)AgonistInternal medicineReverse transcription polymerase chain reactionPeroxisome proliferator-activated receptorBiologyAndrologyChemistryMedicineReceptorPharmacologyGeneBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

Aim To explore the effect and its possible mechanism of resveratrol on atherosclerosis.Methods 42 Mature male New Zealand white rabbits were randomly divided into three groups: rabbits in blank group treated with normal diet,rabbits in model group treated with high fat diet,rabbits in resveratrol group treated with high fat diet and resveratrol at the dosage 16 mg/(kg·d).All rabbits were fed according to experiment design for 12 weeks.The aortas were harvested for histopathological examination.Apoptosis was detected by TUNEL,the mRNA transcription of PPARγ,Fas,FasL and Caspase-3 were examined by RT-PCR and MCP-1,MMP-9 and TIMP-1 were examined by ELISA. Results Atherosclerosis model was successfully established.Atherosclerotic lesions in the resveratrol group were significantly reduced.Resveratrol inhibited apoptosis of cells in the plaque.In the resveratrol group PPARγ transcription increased,Fas,FasL and Caspase-3 mRNA transcription was significantly decreased.The protein expression levels of MCP-1 and MMP-9 were significantly reduced,TIMP-1 protein expression was increased.Conclusions Resveratrol has anti-atherosclerotic role,which may be as a natural agonist through upregulating the PPARγ gene transcription within the plaque,reducing Fas,FasL and Caspase-3 transcription,and reducing the expression of MCP-1,MMP-9 while promoting TIMP-1 expression.

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 score0.189
Threshold uncertainty score0.283

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 head0.003
GPT teacher head0.189
Teacher spread0.186 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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