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Record W1964290392 · doi:10.3109/14756366.2013.858143

Inhibitory effect of collagen-derived tripeptides on dipeptidylpeptidase-IV activity

2014· article· en· W1964290392 on OpenAlexaff
Tadashi Hatanaka, Kayoko Kawakami, Misugi Uraji

Bibliographic record

VenueJournal of Enzyme Inhibition and Medicinal Chemistry · 2014
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsInstitute for Biological Sciences
FundersArtificial Intelligence and Technology Office
KeywordsTripeptideCollagenaseHydrolysateChemistryOligopeptidePeptideEnzymeHydrolysisBiochemistry

Abstract

fetched live from OpenAlex

The collagen tripeptide fragments Gly-Ala-Hyp, Gly-Pro-Ala and Gly-Pro-Hyp were generated by hydrolyzing collagen from pig-skin, cattle-skin, fish-scales and chicken-feet, respectively, with Streptomyces collagenase. Collagenase treatment increased the concentration of tripeptides in the hydrolysates by 13-15% (w/w). Of the three peptides, Gly-Pro-Hyp was a true peptidic inhibitor of dipeptidylpeptidase-IV (DPP-IV), because DPP-IV could not hydrolyze the bond between Pro-Hyp. This tripeptide was a moderately competitive inhibitor (Ki=4.5 mM) of DPP-IV, and its level in the collagen hydrolysates could be greatly increased (4-9% [w/w]) using Streptomyces collagenase.

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 score0.007
Threshold uncertainty score0.915

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 head0.007
GPT teacher head0.256
Teacher spread0.248 · 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

Citations64
Published2014
Admission routes1
Has abstractyes

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