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Record W4408776977 · doi:10.1002/star.70006

Extraction, Structure, Physiological Functions, and Perspectives of Soybean Non‐Starch Polysaccharides: A Review

2025· review· en· W4408776977 on OpenAlexaff
Xianbo Cheng, Baoxiang Wu, Jiayuan Ma, N Chen, Yifeng Rang

Bibliographic record

VenueStarch - Stärke · 2025
Typereview
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsMinistry of Agriculture
FundersNatural Science Foundation of Guangxi ProvinceNational Natural Science Foundation of China
KeywordsPolysaccharideStarchExtraction (chemistry)ChemistryPolymer scienceFood scienceBiochemistryChromatography

Abstract

fetched live from OpenAlex

ABSTRACT Soybean ( Glycine max ) and its byproducts, such as soybean hull, soybean meal, and okara, are good sources of non‐starch polysaccharides (NSP), a kind of potential functional food ingredient. According to in vitro and in vivo studies, this study reviewed the extraction, purification, structure, and physiological functions of soybean NSP. Currently, the preparation technology of soybean NSP was mature, and their structure–function relationship was preliminarily clear. Furthermore, soybean NSP were indicated to exert a variety of physiological functions, including gut probiotic effect, anti‐oxidant effect, anti‐diabetes, anti‐obesity, anti‐cancer, anti‐inflammation, anti‐radiation, and so on. Nevertheless, the mechanisms underlying the physiological functions of soybean NSP have not been comprehensively clarified. On the other hand, the standardization of raw materials of soybean NSP was necessary. The higher structure–function relationship of soybean NSP needed to be elucidated. Moreover, the mechanisms underlying the bioactivities of soybean NSP might be revealed based on the interaction between soybean NSP and gut microbiota. Therefore, this review indicated the potential of soybean NSP for the prevention and treatment of diseases and may help to promote the value‐added utilization of soybean byproducts.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.921
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.065
GPT teacher head0.362
Teacher spread0.297 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2025
Admission routes1
Has abstractyes

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