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Investigating the Role of the Vascular Endothelium in Insulin Delivery

2017· article· en· W2801048206 on OpenAlexafffundabout
Victoria L. Tokarz, Yizhuo Gao, Michael G. Sugiyama, Amira Klip, Warren Lee

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsHospital for Sick ChildrenSt. Michael's Hospital
FundersBanting and Best Diabetes Centre, University of TorontoCanadian Institutes of Health Research
KeywordsInsulinEndotheliumInternal medicineTranscytosisEndocrinologyPerfusionVasodilationEndothelial stem cellBiologyMedicineIn vitroEndocytosisBiochemistry

Abstract

fetched live from OpenAlex

Introduction Insulin is produced in the pancreas and circulates in the blood before crossing the vascular endothelium to gain access to target tissues. The delivery of insulin from the blood to tissues occurs in two stages: first, blood carrying insulin must perfuse the capillary beds. In arteries, insulin stimulates the endothelial cells to produce nitric oxide, which induces vasodilation of the surrounding vascular smooth muscle to increase blood flow. This in turn recruits capillaries that irrigate peripheral tissues. Second, insulin must cross the endothelial monolayer in order to reach the surrounding tissue (e.g. smooth or striated muscle). Classic studies demonstrated that insulin delivery is rate‐limiting to its metabolic action; notably, capillary recruitment and perfusion are compromised in insulin resistant states, thereby decreasing insulin access to the tissues. However, the contribution of insulin transfer across the endothelial layer to insulin action is unclear. In vivo studies cannot define this contribution due to confounding from vessel dilation or capillary recruitment, which contribute to perfusion. On the other hand, in vitro data from cultured endothelial cells suggest that insulin crosses endothelial monolayers by a saturable transport process (e.g. transcytosis). However, it is uncertain whether cells in culture adequately model normal physiology, as cultured endothelial cells are known to rapidly undergo phenotypic drift. Most of the in vitro work on insulin transcytosis has been performed using endothelial cells derived from large vessels such as the aorta. As mentioned, smooth muscle cells respond to insulin stimulation but how insulin crosses the aortic endothelium is unclear. Rationale Because of inherent limitations of both in vivo and in vitro studies, whether the endothelium constitutes a barrier to insulin and restricts its delivery is unknown. Objective To evaluate the contribution of the endothelial barrier to insulin delivery independent of confounding by hemodynamic forces, through an ex vivo perfusion assay. Methods Murine aortas were isolated and segments perfused ex vivo with insulin alone or in the presence of inducers of endothelial barrier dysfunction (histamine or platelet activating factor). Insulin action in vascular smooth muscle was measured by immunoblotting for Akt phosphorylation; blots were normalized to total Akt and to smooth‐muscle actin. The effectiveness of histamine/PAF to induce endothelial leak was established by perfusion with 70kDa dextran. Results The ex vivo aorta responded to insulin in a time‐ and dose‐dependent manner; insulin (10nM) perfusion elicited significant increases in Akt phosphorylation after 5 min (1.4 fold) that were maintained at 30 min (1.3 fold). Perfusion with histamine and PAF induced rapid endothelial leak, demonstrated by accumulation of dextran in the vascular intima; however there was no change in the kinetics of insulin action. Aortic perfusion with 100 nM insulin showed similar results. Conclusions Our results suggest that the endothelium is not rate‐limiting to insulin delivery in large vessels, contrary to existing literature. We are currently using similar approaches to study the microvascular endothelium. Support or Funding Information This work was supported by Canadian Institutes of Health Research Grant MOP‐130493 to A. Klip and W. Lee. V. Tokarz was supported by a graduate studentship from the Banting and Best Diabetes Centre and a Queen Elizabeth II Graduate Studentship in Science and Technology from the University of Toronto.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.016
GPT teacher head0.235
Teacher spread0.219 · 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 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".

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Citations0
Published2017
Admission routes3
Has abstractyes

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