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Record W4362669146 · doi:10.3390/biology12040556

Tripeptide IRW Improves AMPK/eNOS Signaling Pathway via Activating ACE2 in the Aorta of High-Fat-Diet-Fed C57BL/6 Mice

2023· article· en· W4362669146 on OpenAlexafffund
Fatemeh Ashkar, Khushwant S. Bhullar, Xu Jiang, Jianping Wu

Bibliographic record

VenueBiology · 2023
Typearticle
Languageen
FieldMedicine
TopicDiet, Metabolism, and Disease
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyEnosAMPKEndocrinologyInternal medicineSignal transductionCell biologyNitric oxidePhosphorylationNitric oxide synthaseProtein kinase A

Abstract

fetched live from OpenAlex

This study aims to investigate the effect of tripeptide IRW on the local renin–angiotensin system (RAS), particularly angiotensin-converting enzyme 2 (ACE2), and their association with signaling pathways in the aorta of a high-fat-diet (HFD)-induced insulin-resistant mouse model. C57BL/6 mice were fed HFD (45% of the total calories) for six weeks, and then IRW was added to the diet (45 mg/kg body weight (BW)) for another eight weeks. ACE2 mRNA expression and protein level(s) were increased (p < 0.05), while angiotensin II receptor (AT1R) and angiotensin-converting enzyme (ACE) protein abundance was significantly reduced (p < 0.05) in the aorta of HFD mice treated by IRW. IRW supplementation also improved glucose transporter 4 (GLUT4) abundance (p < 0.05) alongside AMP-activated protein kinase (AMPK) (p < 0.05), Sirtuin 1 (SIRT1) (p < 0.05), and endothelial nitric oxide synthase (eNOS) (p < 0.05) expression. IRW downregulated the levels of endothelin 1 (ET-1) and p38 mitogen-activated protein kinases (p38 MAPK, p < 0.05). Furthermore, the levels of AMPK and eNOS in vascular smooth muscle cells (VSMCs) were significantly reduced in ACE2 knockdown cells treated with or without IRW (p < 0.01). In conclusion, this study provided new evidence of the regulatory role of IRW on the aortic ACE2 against metabolic syndrome (MetS) in an HFD-induced insulin-resistant model.

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)0.001
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 score0.454
Threshold uncertainty score0.486

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.025
GPT teacher head0.291
Teacher spread0.267 · 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

Citations5
Published2023
Admission routes2
Has abstractyes

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