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Record W4295123404 · doi:10.1002/ppp3.10315

(Poly)phenols of apples contribute to in vitro antidiabetic properties: Assessment of Canada's Apple Biodiversity Collection

2022· article· en· W4295123404 on OpenAlexafffundabout
Cindy H. J. Yu, Zoë Migicovsky, Jun Song, H.P. Vasantha Rupasinghe

Bibliographic record

VenuePlants People Planet · 2022
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsNova Scotia Department of AgricultureAgriculture and Agri-Food CanadaDalhousie University
FundersAgriculture and Agri-Food CanadaNatural Sciences and Engineering Research Council of CanadaResearch Nova ScotiaNational Science Foundation
KeywordsPhenolsGlycemicFood scienceDiabetes mellitusCultivarMedicineHorticultureChemistryBiologyBiochemistryEndocrinology

Abstract

fetched live from OpenAlex

Societal Impact Statement Apples are affordable and accessible fruit with tremendous biodiversity. Among over 10,000 identified apple cultivars, only a few are commercially available. Habitual fruit consumption is correlated with the prevention of Type 2 diabetes and related complications. Particularly, (poly)phenols found in apples are major contributors to their antidiabetic properties. Here, we have screened (poly)phenol‐rich extracts of 476 apple accessions in Canada's Apple Biodiversity Collection for antidiabetic properties. The results of this work provide insights into the prevention and management of Type 2 diabetes by identifying high (poly)phenol‐containing specialty apples for use in fresh fruit form or value‐added functional food ingredients. Summary The recent trend in sedentary lifestyles and nutritionally‐imbalanced diets has elevated the prevalence of Type 2 diabetes in many parts of the world. Some pharmacological glycemic management can cause undesirable gastrointestinal side effects or hypoglycemia. Thus, there is a growing interest in safe glycemic management using dietary (poly)phenols. In this study, (poly)phenol‐rich extracts of 476 apple accessions from Canada's Apple Biodiversity Collection (ABC) and six major apple (poly)phenols were assessed for in vitro antidiabetic properties against the activities of α‐glucosidase, α‐amylase, and dipeptidyl peptidase‐4 (DPP‐4) and the formation of advanced glycation end products (AGE). Apple (poly)phenol extracts varied in their antidiabetic activities in a dose‐dependent manner. High (poly)phenol‐containing apples demonstrated that their total phenolic contents (TPC) were inversely correlated with the IC 50 values of α‐glucosidase, α‐amylase, and AGE formation, but not DPP‐4. Concentrations of major (poly)phenol compounds such as procyanidin B2, phloridzin, and epicatechin in apples were significantly inversely correlated with IC 50 values of α‐glucosidase in the high (poly)phenol‐containing apples. High TPC apples are not suitable for marketing for fresh fruit consumption due to bitterness and astringency; however, these apples show potential to use in the development of value‐added functional food ingredients or nutraceuticals for blood glucose management. The high TPC apple, “S23‐03‐749,” an advanced breeding line of dessert apple, presents a novel option as a specialty apple cultivar for the dietary management of glycemia.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score0.932

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 head0.011
GPT teacher head0.211
Teacher spread0.201 · 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

Citations16
Published2022
Admission routes3
Has abstractyes

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