Twenty-five years since the discovery of endothelium-derived relaxing factor (EDRF): does a dysfunctional endothelium contribute to the development of type 2 diabetes?
Bibliographic record
Abstract
Twenty-five years ago, the discovery of endothelium-derived relaxing factor opened a door that revealed a new and exciting role for the endothelium in the regulation of blood flow and led to the discovery that nitric oxide (NO) multi-tasked as a novel cell-signalling molecule. During the next 25 years, our understanding of both the importance of the endothelium as well as NO has greatly expanded. No longer simply a barrier between the blood and vascular smooth muscle, the endothelium is now recognized as a complex tissue with heterogeneous properties. The endothelium is the source of not only NO but also numerous vasoactive molecules and signalling pathways, some of which are still not fully characterized such as the putative endothelium-derived relaxing factor. Dysfunction of the endothelium is a key risk factor for the development of macro- and microvascular disease and, by coincidence, the discovery that NO was generated in the endothelium corresponds approximately in time with the increased incidence of type 2 diabetes. Primarily linked to dietary and lifestyle changes, we are now facing a global pandemic of type 2 diabetes. Characterized by insulin resistance and hyperglycaemia, type 2 diabetes is increasingly being diagnosed in adolescents as well as children. Is there a link between dietary-related hyperglycaemic insults to the endothelium, blood flow changes, and the development of insulin resistance? This review explores the evidence for and against this hypothesis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".