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Record W4403902470 · doi:10.14740/jocmr6057

High Blood Glucose After Starch Loading in Young Women With Small Increase in Salivary Amylase: Another Crucial Role of Postprandial Salivary Amylase

2024· article· en· W4403902470 on OpenAlexvenueno aff
Airi Sekine, Kei Nakajima

Bibliographic record

VenueJournal of Clinical Medicine Research · 2024
Typearticle
Languageen
FieldMedicine
TopicSalivary Gland Disorders and Functions
Canadian institutionsnot available
Fundersnot available
KeywordsPostprandialAmylaseMedicineStarchSalivaEndocrinologyInternal medicineFood scienceInsulinBiochemistryEnzymeBiology

Abstract

fetched live from OpenAlex

Background: Salivary α-amylase plays a crucial role in the glucose metabolism. However, postprandial salivary α-amylase activity (SAA) and its relationship with blood glucose (BG) are poorly understood. Therefore, we investigated SAA and BG after starch loading in healthy young women. Methods: In 60 healthy non-obese young women, we investigated SAA, BG, and blood 3-hydroxybutyrate (3HB) after the consumption of 150 g rice (starch 48.8 g). Participants were classified into two groups based on the changes (Δ) in SAA from baseline at 60 min: small- and large-increase in ΔSAA groups (SI-ΔSAA and LI-ΔSAA). Results: BG levels were significantly higher at 60, 90, and 120 min in participants with SI-ΔSAA (n = 31) than LI-ΔSAA (n = 29). Baseline 3HB concentration was also higher in participants with SI-ΔSAA. ΔSAA at 60 min was most closely and inversely correlated with BG and ΔBG at 90 min (r = -0.53 and -0.50, both P < 0.0001). Generalized linear model analysis also indicated that ΔSAA at 60 min was the most predictive of ΔBG at 90 min. Conclusions: Higher levels of BG and ΔBG were observed after starch loading in healthy young women with smaller increase in salivary amylase, suggesting another crucial role of postprandial salivary amylase for the postprandial glucose metabolism.

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)0.010
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.059
GPT teacher head0.398
Teacher spread0.339 · 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.

Study designObservational
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

Citations2
Published2024
Admission routes1
Has abstractyes

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