Insulin enhances the gain of arterial baroreflex control of muscle sympathetic nerve activity in humans
Bibliographic record
Abstract
Recent animal studies indicate that insulin increases arterial baroreflex control of lumbar sympathetic nerve activity; however, the extent to which these findings can be extrapolated to humans is unknown. To begin to address this, muscle sympathetic nerve activity (MSNA) and arterial blood pressure were measured in 19 healthy subjects (27 ± 1 years) before, and for 120 min following, two common methodologies used to evoke sustained increases in plasma insulin: a mixed meal and a hyperinsulinaemic euglycaemic clamp. Weighted linear regression analysis between MSNA and diastolic blood pressure was used to determine the gain (i.e. sensitivity) of arterial baroreflex control of MSNA. Plasma insulin was significantly elevated within 30 min following meal intake (34 ± 6 uIU ml(1); P < 0.05) and remained above baseline for up to 120 min. Similarly, after meal intake, arterial baroreflex-MSNA gain for burst incidence and total MSNA was increased and remained elevated for the duration of the protocol (e.g. burst incidence gain: 3.29 ± 0.54 baseline vs. 5.64 ± 0.67 bursts (100 heart beats)(1) mmHg(1) at 120 min; P < 0.05). During the hyperinsulinaemic euglycaemic clamp, in which insulin was elevated to postprandial concentrations (42 ± 6 μIU ml(1); P < 0.05), while glucose was maintained constant, arterial baroreflex-MSNA gain was similarly enhanced (e.g. burst incidence gain: 2.44 ± 0.29 baseline vs. 4.74 ± 0.71 bursts (100 heart beats)(1) mmHg(1) at 120 min; P < 0.05). Importantly, during time control experiments, with sustained fasting insulin concentrations, the arterial baroreflex-MSNA gain remained unchanged. These findings demonstrate, for the first time in healthy humans, that increases in plasma insulin enhance the gain of arterial baroreflex control of MSNA.
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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 | 0.001 | 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".