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Record W2772059359 · doi:10.1172/jci97233

Discovery, characterization, and clinical development of the glucagon-like peptides

2017· review· en· W2772059359 on OpenAlexfundno aff
Daniel J. Drucker, Joel F. Habener, Jens J. Holst

Bibliographic record

VenueJournal of Clinical Investigation · 2017
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
FundersCanada Research Chairs
KeywordsGlucagon-like peptide-2Translational scienceShort bowel syndromeRelevance (law)Computational biologyMedicineData scienceBioinformaticsBiologyComputer scienceInternal medicinePolitical sciencePathologyBiochemistryPeptide

Abstract

fetched live from OpenAlex

The discovery, characterization, and clinical development of glucagon-like-peptide-1 (GLP-1) spans more than 30 years and includes contributions from multiple investigators, science recognized by the 2017 Harrington Award Prize for Innovation in Medicine. Herein, we provide perspectives on the historical events and key experimental findings establishing the biology of GLP-1 as an insulin-stimulating glucoregulatory hormone. Important attributes of GLP-1 action and enteroendocrine science are reviewed, with emphasis on mechanistic advances and clinical proof-of-concept studies. The discovery that GLP-2 promotes mucosal growth in the intestine is described, and key findings from both preclinical studies and the GLP-2 clinical development program for short bowel syndrome (SBS) are reviewed. Finally, we summarize recent progress in GLP biology, highlighting emerging concepts and scientific insights with translational relevance.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.253
GPT teacher head0.463
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations399
Published2017
Admission routes1
Has abstractyes

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