Alternative Routes of Insulin Delivery
Bibliographic record
Abstract
Abstract Identification of the pancreas as the site of the defect in diabetes mellitus by von Mehring and Minkowski in 1889 led eventually to the identification and successful extraction of insulin in 1921 by Banting and Best. The availability of insulin for therapy shortly afterwards dramatically changed the lives of patients with diabetes who previously had a life expectancy of less than 2 years. In the 80 years since, major benefits have accrued. In the year 2000 alone, it is estimated that about 4.8 million years of life were gained for patients with type 1 diabetes as a result of insulin treatment, assuming a life expectancy of 1.5 years in its absence and a global prevalence of 5.1 million. Since insulin was first introduced into clinical practice there have been major developments in its production, purification, pharmaceutical formulation, and methods of delivery. However, despite these advances, microvascular and premature macrovascular complications persist as the main cause of morbidity and mortality in both type 1 and type 2 diabetes and represent a constant reminder that current therapeutic and management strategies, for the vast majority of our patients, remain woefully inadequate. In this chapter, we describe the many attempts made to develop alternative, less invasive routes for the delivery of insulin while focusing on recent progress achieved with inhaled insulins, which may provide the first opportunity for at least partial independence from subcutaneous injections.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".