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Record W2586825521 · doi:10.1021/acs.jmedchem.6b01668

Synthesis and Characterization of Urofuranoic Acids: In Vivo Metabolism of 2-(2-Carboxyethyl)-4-methyl-5-propylfuran-3-carboxylic Acid (CMPF) and Effects on in Vitro Insulin Secretion

2017· article· en· W2586825521 on OpenAlexafffund
E Nagy, Ying Liu, Kacey J. Prentice, Kyle W. Sloop, P E Sanders, Battsetseg Batchuluun, Craig D. Hammond, Michael B. Wheeler, Timothy B. Durham

Bibliographic record

VenueJournal of Medicinal Chemistry · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsUniversity of Toronto
FundersDivision of Graduate EducationBanting and Best Diabetes Centre, University of TorontoCanadian Institutes of Health Research
KeywordsMetaboliteIn vivoChemistryIn vitroInsulinSecretionCarboxylic acidMetabolismBiochemistryInternal medicineEndocrinologyBiologyMedicine

Abstract

fetched live from OpenAlex

CMPF (2-(2-carboxyethyl)-4-methyl-5-propylfuran-3-carboxylic acid) is a metabolite that circulates at high concentrations in type 2 and gestational diabetes patients. Further, human clinical studies suggest it might have a causal role in these diseases. CMPF inhibits insulin secretion in mouse and human islets in vitro and in vivo in rodents. However, the metabolic fate of CMPF and the relationship of structure to effects on insulin secretion have not been significantly studied. The syntheses of CMPF and analogues are described. These include isotopically labeled molecules. Study of these materials in vivo has led to the first observation of a metabolite of CMPF. In addition, a wide range of CMPF analogues have been prepared and characterized in insulin secretion assays using both mouse and human islets. Several molecules that influence insulin secretion in vitro were identified. The molecules described should serve as interesting probes to further study the biology of CMPF.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.005
GPT teacher head0.231
Teacher spread0.226 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations25
Published2017
Admission routes2
Has abstractyes

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