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Record W2884339835 · doi:10.1007/s10238-018-0519-0

Dipeptidyl peptidase-4(DPP-4) inhibitors: promising new agents for autoimmune diabetes

2018· review· en· W2884339835 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical and Experimental Medicine · 2018
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsMinistry of Education and Child Care
FundersNational Science and Technology Infrastructure ProgramNational Key Research and Development Program of ChinaXiangya Hospital, Central South UniversityCentral South UniversityNational Natural Science Foundation of China
KeywordsMedicineDiabetes mellitusDipeptidyl peptidase-4Dipeptidyl peptidaseAlogliptinPharmacologyType 1 diabetesClinical trialHematologyIn vivoAutoimmune diabetesType 2 diabetesImmunologyInternal medicineEndocrinologyBiologyEnzymeBiochemistry

Abstract

fetched live from OpenAlex

Dipeptidyl peptidase-4 (DPP-4) inhibitors constitute a novel class of anti-diabetic agents confirmed to improve glycemic control and preserve β-cell function in type 2 diabetes. Three major large-scale studies, EXAMINE, SAVOR-TIMI 53, and TECOS, have confirmed the cardiovascular safety profile of DPP-4 inhibitors. Based on these results, DPP-4 inhibitors have gained widespread use in type 2 diabetes treatment. It is currently unknown, however, whether DPP-4 inhibitors have similar therapeutic efficacy against autoimmune diabetes. Several in vitro and in vivo studies have addressed this issue, but the results remain controversial. In this review, we summarize experimental findings and preliminary clinical trial results, and identify potentially effective immune modulation targets of DPP-4 inhibitors for autoimmune diabetes.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.834
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.144
GPT teacher head0.446
Teacher spread0.302 · 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