Insulin’s Role in Diabetes Management: After 90 Years, Still Considered the Essential “Black Dress”
Bibliographic record
Abstract
It has been 93 years since Banting and Best extracted insulin in Scottish physiologist J.J.R. Macleod’s laboratory and, with the help of their fellow Canadian chemist James B. Collip, used it to successfully treat a cachectic boy, Leonard Thompson, who suffered from life-threatening diabetes. Since that time, insulin therapy has become the mainstay of treatment for patients with type 1 diabetes and a cornerstone therapy for many individuals with type 2 diabetes. Over the years, many changes in insulin therapy have occurred, including new formulations, new delivery systems, and additional therapeutic tactics. We are on the brink of a new and exciting era with increasingly reliable and easy-to-use continuous glucose monitoring as part of a closed-loop delivery system. This new “artificial pancreas” system, with its carefully modulated insulin (which remains the key component), may soon be ready for clinical use. In addition, an impressive array of new oral and injectable agents for type 2 diabetes has been developed over the past 20 years. Many thought that these could replace injected insulin in a therapeutic regimen, or at least delay its use. Yet, the reality is that insulin will always be needed for type 1 diabetes until a cure is found and progressive insulin deficiency is a fundamental defect of type 2 diabetes. Furthermore, supplementation of endogenous insulin continues to be necessary for large numbers of individuals with type 2 diabetes. Meanwhile, the other classes of therapeutic agents are vying for a strategic position alongside insulin in clinical regimens for type 2 diabetes, and there is an unmet need for adjuvant therapies to mitigate the treatment challenges in type 1 diabetes as well. To dramatize the continuing role of insulin in the management of diabetes, we propose an analogy from the world of clothing and fashion: Insulin is and will remain …
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".