Odyssey between Scylla and Charybdis through storms of carbohydrate metabolism and diabetes: a career retrospective
Bibliographic record
Abstract
This research perspective allows me to summarize some of my work completed over 50 years, and it is organized in seven sections. 1) The treatment of diabetes concentrates on the liver and/or the periphery. We quantified hormonal and metabolic interactions involved in physiology and the pathogenesis of diabetes by developing tracer methods to separate the effects of diabetes on both. We collaborated in the first tracer clinical studies on insulin resistance, hypertriglyceridemia, and the Cori cycle. 2) Diabetes reflects insulin deficiency and glucagon abundance. Extrapancreatic glucagon changed the prevailing dogma and permitted precise exploration of the roles of insulin and glucagon in physiology and diabetes. 3) We established the critical role of glucagon-insulin interaction and the control of glucose metabolism during moderate exercise and of catecholamines during strenuous exercise. Deficiencies of the release and effects of these hormones were quantified in diabetes. We also revealed how acute and chronic hyperglycemia affects the expression of GLUT2 gene and protein in diabetes. 4) We outlined molecular and physiological mechanisms whereby exercise training and repetitive neurogenic stress can prevent diabetes in ZDF rats. 5) We and others established that the indirect effect of insulin plays an important role in the regulation of glucose production in dogs. We confirmed this effect in humans and demonstrated that in type 2 diabetes it is mainly the indirect effect. 6) We indicated that the muscle and the liver protected against glucose changes. 7) We described molecular mechanisms responsible for increased HPA axis in diabetes and for the diminished responses of HPA axis, catecholamines, and glucagon to hypoglycemia. We proposed a new approach to decrease the threat of hypoglycemia.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.015 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".