MétaCan
Menu
Back to cohort
Record W2064284871 · doi:10.1002/cbic.200700470

The Search for Novel Human Pancreatic α‐Amylase Inhibitors: High‐Throughput Screening of Terrestrial and Marine Natural Product Extracts

2008· article· en· W2064284871 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemBioChem · 2008
Typearticle
Languageen
FieldMedicine
TopicNatural Antidiabetic Agents Studies
Canadian institutionsUniversity of British Columbia
FundersNational Cancer InstituteNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsNatural productChemistryNon-competitive inhibitionMyricetinBiochemistryEnzymeAmylaseBioassayFlavonolsBiologyAntioxidantQuercetin

Abstract

fetched live from OpenAlex

Specific inhibitors of human pancreatic alpha-amylase (HPA) have potential as oral agents for the control of blood glucose levels in the treatment of diabetes and obesity. In a search for novel inhibitors, a library of 30 000 crude biological extracts of terrestrial and marine origin has been screened. A number of inhibitory extracts were identified, of which the most potent was subjected to bioassay-guided purification. A family of three glycosylated acyl flavonols, montbretins A-C, was thereby identified and characterized as competitive amylase inhibitors, with K(i) values ranging from 8.1-6100 nM. Competitive inhibition by myricetin, which corresponds to the flavone core, and noncompetitive inhibition by a second fragment, ethyl caffeiate, suggest a binding mode for these inhibitors.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.043
GPT teacher head0.295
Teacher spread0.252 · 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