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Record W4285796565 · doi:10.1007/s00592-022-01938-4

Insulin: evolution of insulin formulations and their application in clinical practice over 100 years

2022· review· en· W4285796565 on OpenAlexaffabout
Geremia B. Bolli, Alice Cheng, David R. Owens

Bibliographic record

VenueActa Diabetologica · 2022
Typereview
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsUniversity of Toronto
FundersSanofi
KeywordsInsulinDiabetes mellitusGlucose homeostasisMedicineIntensive care medicineInternal medicineEndocrinologyInsulin resistance

Abstract

fetched live from OpenAlex

The first preparation of insulin extracted from a pancreas and made suitable for use in humans after purification was achieved 100 years ago in Toronto, an epoch-making achievement, which has ultimately provided a life-giving treatment for millions of people worldwide. The earliest animal-derived formulations were short-acting and contained many impurities that caused adverse reactions, thereby limiting their therapeutic potential. However, since then, insulin production and purification improved with enhanced technologies, along with a full understanding of the insulin molecule structure. The availability of radio-immunoassays contributed to the unravelling of the physiology of glucose homeostasis, ultimately leading to the adoption of rational models of insulin replacement. The introduction of recombinant DNA technologies has since resulted in the era of both rapid- and long-acting human insulin analogues administered via the subcutaneous route which better mimic the physiology of insulin secretion, leading to the modern basal-bolus regimen. These advances, in combination with improved education and technologies for glucose monitoring, enable people with diabetes to better meet individual glycaemic goals with a lower risk of hypoglycaemia. While the prevalence of diabetes continues to rise globally, it is important to recognise the scientific endeavour that has led to insulin remaining the cornerstone of diabetes management, on the centenary of its first successful use in humans.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.663

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.093
GPT teacher head0.418
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations39
Published2022
Admission routes2
Has abstractyes

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