Vasoactive Intestinal Peptide: Another Player in Adipose Tissue Blood Flow Regulation?
Bibliographic record
Abstract
ABSTRACT Objectives In healthy people, adipose tissue blood flow (ATBF) rises postprandially; however, in one third of them, this response is altered. These people are characterized by prolonged postprandial lipemia and higher cardiometabolic risk. Vasoactive intestinal peptide (VIP) is a gut neurotransmitter with a vasodilatory effect. The aim of the study was to assess the role of VIP in ATBF regulation and its postprandial blunting. Methods Plasma VIP and ATBF ( 133 Xenon washout technique) were measured during a 75 g oral glucose load in 16 healthy participants. ATBF was monitored in 12 individuals during in situ microinfusion of incremental doses of VIP (10 −7 , 10 −6 , 10 −5 mol L −1 ). Results Oral glucose induced no change in plasma VIP. Post‐glucose ATBF measures identified 7 non‐responders (peak blood flow < 50% of fasting values) and 9 responders. Compared to baseline (2.50 [1.96–3.59] mL·100 g −1 min −1 ), local microinfusion of VIP increased ATBF dose‐dependently: 2.67 [2.18–3.89]; 4.35 [3.33–4.65]; and 7.91 [6.59–9.88] mL·100 g −1 min −1 ( p < 0.0001) with a non‐significant lower response to VIP in non‐responders. Conclusions Our findings show a potent vasodilatory effect of VIP in adipose tissue and suggest that individuals with a blunted ATBF response to glucose load have a lower response. Whether the local unresponsiveness to VIP participates in this non‐responder status has to be confirmed in larger studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".