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Record W2491908576 · doi:10.1530/joe-16-0056

Targeting the gastrointestinal tract to treat type 2 diabetes

2016· review· en· W2491908576 on OpenAlexafffund
Paige V. Bauer, Frank A. Duca

Bibliographic record

VenueJournal of Endocrinology · 2016
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsToronto General HospitalUniversity of Toronto
FundersBanting and Best Diabetes Centre, University of Toronto
KeywordsType 2 diabetesGut floraMetforminGlucose homeostasisMedicineGastrointestinal tractDiabetes mellitusGlucagon-like peptide-1ObesityBioinformaticsInternal medicineEndocrinologyBiologyInsulin resistanceImmunology

Abstract

fetched live from OpenAlex

The rising global rates of type 2 diabetes and obesity present a significant economic and social burden, underscoring the importance for effective and safe therapeutic options. The success of glucagon-like-peptide-1 receptor agonists in the treatment of type 2 diabetes, along with the potent glucose-lowering effects of bariatric surgery, highlight the gastrointestinal tract as a potential target for diabetes treatment. Furthermore, recent evidence suggests that the gut plays a prominent role in the ability of metformin to lower glucose levels. As such, the current review highlights some of the current and potential pathways in the gut that could be targeted to improve glucose homeostasis, such as changes in nutrient sensing, gut peptides, gut microbiota and bile acids. A better understanding of these pathways will lay the groundwork for novel gut-targeted antidiabetic therapies, some of which have already shown initial promise.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.975
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.040
GPT teacher head0.333
Teacher spread0.293 · 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 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

Citations26
Published2016
Admission routes2
Has abstractyes

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