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Record W4403635199 · doi:10.1016/j.tifs.2024.104757

Effect of polysaccharide-induced viscosity on the digestion of proteins, fats, and carbohydrates in food: A comprehensive review and future perspectives

2024· review· en· W4403635199 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueTrends in Food Science & Technology · 2024
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPolysaccharides Composition and Applications
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDigestion (alchemy)Food sciencePolysaccharideViscosityChemistryFood proteinBiochemistryMaterials scienceChromatography

Abstract

fetched live from OpenAlex

Polysaccharides play a crucial role in slowing macronutrient digestion, contributing to satiety, glycemic control, regulating blood sugar levels, and cholesterol management. Their impact on food digestion and absorption is largely mediated by their ability to increase the viscosity of chyme and digesta, affecting the activity of digestive enzymes. This review examines the effects of polysaccharides on digestive enzymes, focusing on their inhibition of proteolysis, lipolysis, and amylolysis. While other ingredients like gelatin or specific food additives can increase food viscosity, this review specifically emphasizes polysaccharides, particularly soluble fibers. A comprehensive search in Web of Science/ScienceDirect identified 1589 articles published between January 1982 and August 2023. After applying selection criteria, 212 trials from 96 articles that directly examined the influence of polysaccharide viscosity on macronutrient digestibility were included. The review identifies 38 polysaccharides, including pectin, xanthan, guar gum, carboxymethylcellulose, carrageenan, and konjac glucomannan, known for their viscosity-enhancing properties. These polysaccharides impact nutrient digestion through several mechanisms: they reduce diffusion and mass transfer, impede mixing of digestive components, block enzyme active sites, induce conformational changes, and form aggregates and surface bonds that immobilize substrates. The extent of digestion inhibition is influenced by factors such as polysaccharide concentration, viscosity, and molecular structure, as well as the properties of the substrate, including molecular weight and conformation. The review highlights the need for more accurate modeling of digestive processes and in vitro systems that effectively replicate digestive conditions to better understand the impact of polysaccharides on nutrient digestion and absorption. Future research should explore complex systems, including whole foods and fiber-rich by-products like fruit peels or grain husks containing both soluble and insoluble fiber, to gain deeper insights into how polysaccharides affect into nutrient digestion and absorption in real-world scenarios. • Review explores how polysaccharides affect proteolysis, lipolysis, and amylolysis. • Polysaccharides enhance viscosity, impacting macronutrient digestion and absorption. • Viscosity depends on polysaccharide concentration, structure, and substrate properties. • Polysaccharides slow digestion by reducing enzyme diffusion and blocking their action. • Exploration of polysaccharide-rich food waste can boost sustainability and nutrition.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.955
Threshold uncertainty score0.403

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.006
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.035
GPT teacher head0.323
Teacher spread0.288 · 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