A New Paradigm for Diabetes and Obesity: the Hepatic Insulin Sensitizing Substance (HISS) Hypothesis
Bibliographic record
Abstract
The glucose disposal effect of insulin after a meal is accounted for in approximately equal measure by the direct action of insulin and the action of HISS (hepatic insulin sensitizing substance) released from the liver and acting on skeletal muscle to stimulate glucose storage as glycogen. The ability of insulin to cause HISS release is determined by hepatic parasympathetic nerves. Eliminating the parasympathetic signal by surgical denervation of the liver or by blockade of hepatic muscarinic receptors, hepatic nitric oxide synthase, or hepatic cyclooxygenase results in insulin resistance that can be accounted for by the absence of HISS action and is referred to as HISS-dependent insulin resistance (HDIR). Animal models in which the insulin resistance has been shown to be HDIR includes the spontaneously hypertensive rat, sucrose fed rats, animals with liver disease, adult offspring of fetal alcohol exposure, acute stress, and ageing. We suggest that HDIR accounts for the major metabolic disturbances in type 2 diabetes, including the postprandial hyperglycemia that results in the majority of pathologies related to diabetes. The observation of meal-induced insulin sensitization (MIS) and the role of HISS allows for consideration of a new paradigm relating meal processing, diabetes, obesity, and insulin resistance. New diagnostic approaches and therapeutic targets are described.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".