Meal-induced insulin sensitization in conscious and anaesthetized rat models comparing liquid mixed meal with glucose and sucrose
Bibliographic record
Abstract
We have recently shown that meal-induced insulin sensitization (MIS) occurs after feeding and decreases progressively to insignificance after 24 h of fasting and is caused by action of a hepatic insulin sensitizing substance (HISS). In order to carry out quantitative studies of MIS, some standardized meal intake is required. Our objective was to establish animal models to be tested in both the conscious and anaesthetized state using intragastric injection of liquid meals in order to quantify MIS. Insulin sensitivity was assessed before and 90 min after the meal using the rapid insulin sensitivity test (RIST) which is a transient euglycaemic clamp. Rats tested in the conscious state were instrumented under anaesthesia 6-9 d prior to testing with catheters in the carotid artery, jugular vein and stomach. Meals, injected into the stomach, consisted of a liquid mixed meal, sucrose, glucose or water. The glucose sequestration in response to insulin increased by 90 % and 61 % following the liquid mixed meal (10 ml/kg) in conscious and anaesthetized rats, respectively. Glucose, sucrose and water did not effectively activate MIS. MIS was completely reversed in the conscious model by atropine and completely prevented from developing in the anaesthetized model that had previously undergone hepatic denervation. Gastric administration of a liquid mixed meal but not glucose or sucrose is capable of activating MIS for purposes of mechanistic studies and quantification of the MIS process. The feeding signal is mediated by the hepatic parasympathetic nerves.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".