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Record W4405915305 · doi:10.1002/cche.10866

High amylose maize starch can produce an inclusion complex with extract of medicinal plants of <i>Amphipterygium adstringent</i>

2024· article· en· W4405915305 on OpenAlexaff
Josué Moreno-Zaragoza, Daniela F. Pecina‐Ornelas, Edith Agama‐Acevedo, Cristina M. Rosell, Luís A. Bello‐Pérez

Bibliographic record

VenueCereal Chemistry · 2024
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsChemistryAmyloseStarchFood scienceInclusion (mineral)BotanyMineralogy

Abstract

fetched live from OpenAlex

Abstract Background and Objective The interaction between starch and polyphenol would increase the bioaccessibility of those bioactive compounds. Previous studies have been conducted with pure polyphenols, but the use of medicinal plants, rich in bioactive compounds, able to complex with starch, is growing. The present study aimed to analyze the complex formation between the extract of a medicinal plant ( Amphipterygium adstringent , AA) and high amylose starch (HA). The total polyphenol content (TPC), and antioxidant capacity (AC), besides X‐ray diffraction pattern, differential scanning calorimetry, Fourier transform infrared spectroscopy (FTIR), and starch hydrolysis rate were evaluated in the AA‐HA and compared with those of the complex gallic acid (GA)‐HA. Findings The AA‐HA complex had higher TPC than GA‐HA, despite their rather similar AC. The increased crystallinity and short‐range order of the HA confirmed the formation of the complex with AA. This complex required higher enthalpy (2.0 J/g) than its respective HA control (0.52 J/g) for the gelatinization and the in vitro starch hydrolysis suggests the formation of resistant starch. Conclusion The extract of medicinal plants can form complexes with amylose, which has antioxidant properties, besides increasing the resistant starch. Significance and Novelty Complex formation between HA and extract of medicinal plants is feasible for increasing the release of the bioactive compounds after digestion.

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 score0.012
Threshold uncertainty score0.532

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 head0.025
GPT teacher head0.264
Teacher spread0.239 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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