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Record W4295951489 · doi:10.26685/urncst.379

Reducing Atherosclerotic Plaque Development and Endothelial Hemichannel Activity with WIN-55,212-2: A Research Protocol

2022· article· en· W4295951489 on OpenAlexaff
Sidra M. Bharmal

Bibliographic record

VenueUndergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Disease and Adiposity
Canadian institutionsWestern University
Fundersnot available
KeywordsProinflammatory cytokineEndothelial dysfunctionInflammationPharmacologyApolipoprotein EMonocyteReceptorAgonistMacrophageMedicineIn vitroEndocrinologyInternal medicineBiologyBiochemistry

Abstract

fetched live from OpenAlex

Introduction: Endothelial cells (ECs) are critical regulators of vascular homeostasis, and their dysfunction leads to the development of atherosclerosis – the main underlying cause of cardiovascular diseases (CVDs). This dysfunction can be promoted by prolonged endothelial connexin43 hemichannel activity, which is caused by the combination of high glucose levels and cytokines IL-1β/TNF-α. WIN-55,212-2 (WIN) is a synthetic agonist of CB1/CB2 receptors and can counteract the proinflammatory effects of high glucose and IL-1β/TNF-α. We hypothesize that WIN treatment on ECs will reduce connexin43 hemichannel activity, thus preventing endothelial dysfunction and atherosclerotic progression. Methods: We will use the Apolipoprotein E Knockout (ApoE-/-) mouse model to assess the impact on atherosclerotic lesions. Hyperglycemia will be generated in these mice with Streptozotocin injections. The increased levels of glucose should induce IL-1β expression and stimulate prolonged hemichannel activity. ECs will be isolated from a subset of mice and cultured to test WIN-efficacy. ATP release will be assessed through an ATP viability assay. More in vitro assessments on subsets of ApoE-/- mice treated or not with WIN will be performed. Flow cytometry will evaluate monocyte-derived macrophage concentration and other pro and anti-inflammatory cytokines in tissue samples. Furthermore, atherosclerotic plaque volume in the aortic sinus will be quantified and characterized. Results: We expect that WIN-treated ECs will reduce ATP synthesis compared to those from the control group. Moreover, we expect to see a reduction in the inflammatory response with a consequent decrease in atherosclerotic progression. Discussion: This manuscript outlines the use of a novel compound that could prevent atherosclerosis progression. The results of this study could outline a potential mechanism that may be targeted to treat or forestall atherosclerosis progression. Conclusion: Overall, we aim to determine if WIN may not only hinder this pervasive condition but inhibit CVDs through curtailing atherosclerotic plaque development. The following steps include performing the experiment, confirming results through repetition, and using other animal models.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0160.006

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 head0.086
GPT teacher head0.423
Teacher spread0.337 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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
Published2022
Admission routes1
Has abstractyes

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