MétaCan
Menu
Back to cohort
Record W2734797206 · doi:10.1039/c7fo00900c

Cranberries improve postprandial glucose excursions in type 2 diabetes

2017· article· en· W2734797206 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

VenueFood & Function · 2017
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsStillwater (Canada)
FundersNational Institute of General Medical Sciences
KeywordsPostprandialType 2 diabetesCrossover studyMedicineInsulin resistanceInternal medicineEndocrinologyMealMalondialdehydeDiabetes mellitusGlucose homeostasisLipid oxidationInsulinFood scienceChemistryOxidative stressAntioxidantBiochemistry

Abstract

fetched live from OpenAlex

) (mean ± s.d.) = 39.5 ± 6.5; age (years) = 56 ± 6) revealed that postprandial increases in glucose were significantly lower in the cranberry vs. control at 2 & 4 h (p < 0.05). No significant differences were noted in insulin, insulin resistance evaluated by homeostasis model assessment, lipid profiles and blood pressure between the cranberry and control groups. Among the biomarkers of inflammation and oxidation, postprandial serum interleukin-18 and malondialdehyde were significantly lower at 4 h, and serum total nitrite was higher at 2 h in the cranberry vs. control group (all p < 0.05). No effects were noted on C-reactive protein or interlukin-6. Overall, dietary cranberries had notable effects in improving high-fat breakfast induced postprandial glucose and selected biomarkers of inflammation and oxidation in participants with T2DM. These findings provide evidence that adding whole cranberries to a high-fat meal may improve postprandial blood glucose management and warrant further investigation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.339

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 head0.017
GPT teacher head0.259
Teacher spread0.242 · 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