Regulation of blood flow in adipose tissue: involvement of the cholinergic system
Bibliographic record
Abstract
Acetylcholine (Ach) has vasodilatory actions. However, data are conflicting about the role of Ach in regulating blood flow in subcutaneous adipose tissue (ATBF). This may be related to inaccurate ATBF recording or to the responder/nonresponder (R/NR) phenomenon. We showed previously that healthy individuals are R (ATBF increases postprandially by >50% of baseline BF) or NR (ATBF increases ≤50% postprandially). Our objective was to assess the role of the cholinergic system on ATBF in R and NR subjects. ATBF was manipulated by in situ microinfusion of vasoactive agents (VA) in AT and monitored by the (133)Xenon washout technique (both recognized methods) at the VA site and at the control site. We tested incrementally increasing doses of Ach (10(-5), 10(-3), and 10(-1) mol/l; n = 15) and Ach receptor antagonists (Ra) before and after oral administration of 75-g glucose using atropine (muscarinic Ra; 10(-4) mol/l, n = 13; 10(-5) mol/l, n = 22) and mecamylamine (nicotinic Ra; 10(-3) mol/l, n = 15; 10(-4) mol/l, n = 10). Compared with baseline [2.41 (1.36-2.83) ml·100 g(-1)·min(-1)], Ach increased ATBF dose dependently [3.32 (2.80-5.09), 6.46 (4.36-9.51), and 10.31 (7.98-11.52), P < 0.0001], with no difference between R and NR. Compared with control side, atropine (both concentrations) had no effect on fasting ATBF; only atropine 10(-4) mol/l decreased post-glucose ATBF [iAUC: 1.25 (0.32-2.91) vs. 1.98 (0.64-2.94); P = 0.04]. This effect was further apparent in R. Mecamylamine had no impact on fasting and postglucose ATBF in R and NR. Our results suggest that the cholinergic system is implicated in ATBF regulation, although it has no role in the blunting of ATBF response in NR.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".