A Synergistic, Balanced Antioxidant Cocktail, Protects Aging Rats from Insulin Resistance and Absence of Meal-Induced Insulin Sensitization (AMIS) Syndrome
Bibliographic record
Abstract
A series of in vivo and in vitro studies using animal and human models in the past 15 years have demonstrated that approximately 55% (~66% in humans) of the glucose disposal effect of an i.v. injection of insulin in the fed state is dependent on the action of a second hormone, hepatic insulin sensitizing substance (HISS), which is released from the liver and stimulates glucose uptake in muscle, heart and kidneys. Sensitization of the insulin response by a meal through release of HISS is called meal-induced insulin sensitization (MIS). Absence of HISS action results in postprandial hyperglycemia, hyperinsulinemia, hyperlipidemia, adiposity, increased free radical stress and a cluster of progressive metabolic and cardiovascular dysfunctions referred to as the AMIS (absence of meal-induced insulin sensitization) syndrome. Reduced HISS release accounts for the insulin resistance that occurs with aging and is made worse by physical inactivity and diets high in sucrose or fat. This brief review provides an update of major metabolic disturbances associated with aging due to reduction of HISS release, and the protection against these pathological changes in aging animals using a balanced synergistic antioxidant cocktail SAMEC (S-adenosylmethionine, vitamins E and C). The synergy amongst the components is consistent with the known benefits of antioxidants supplied by a mixed diet and acting through diverse mechanisms. Using only three constituents, SAMEC appears suitable as an antioxidant specifically targeting the AMIS syndrome.
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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 | 0.001 | 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 | 0.001 |
| 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".