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Record W4221065891 · doi:10.1016/j.jff.2022.105044

Anti-inflammatory effect of lentil hull (Lens culinaris) extract via MAPK/NF-κB signaling pathways and effects of digestive products on intestinal barrier and inflammation in Caco-2 and Raw264.7 co-culture

2022· article· en· W4221065891 on OpenAlexafffund
Peng Li, Fanghua Guo, Minjia Pei, Rong Tsao, Xiaoya Wang, Li Jiang, Yong Sun, Hua Xiong

Bibliographic record

VenueJournal of Functional Foods · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaNational Natural Science Foundation of ChinaSaskatchewan Pulse GrowersChina Postdoctoral Science FoundationAccelerate Brain Cancer Cure
KeywordsPolyphenolCaco-2MAPK/ERK pathwayChemistrySecretionDigestion (alchemy)Food scienceBiochemistryIn vitroSignal transductionAntioxidantChromatography

Abstract

fetched live from OpenAlex

The polyphenol-rich lentil hulls are the by-product of lentils hulling process. In this manuscript, in vitro digestion, Caco-2 cell monolayer and Caco-2/RAW264.7 cell co-culture model were established to explore their anti-inflammatory mechanism, absorption of digestive products (RLD), and impact on the intestinal barrier. Results shown that high dose RLE and GLE could significantly inhibit the secretion of NO (30.23% and 31.08%, respectively), IL-6 (81.48% and 56.82%, respectively) and IL-1β (88.05% and 91.67%, respectively), and down-regulate the protein and mRNA expression of iNOS (56.46% and 45.69%, respectively) and COX-2 (76.53% and 46.65%, respectively), and inhibit the activation of MAPK and NF-κB signaling pathways. Polyphenols can be released from lentil hulls and protocatechuic acid glycoside derivative has the highest content (2205.09 ± 7.02 μg/g DW). Digestive products can be absorbed by intestine to maintain intestinal barrier and play anti-inflammatory effect. Above all, lentil hulls may be a potentially valuable functional dietary resource.

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)0.001
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 score0.020
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.006
GPT teacher head0.219
Teacher spread0.212 · 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

Citations37
Published2022
Admission routes2
Has abstractyes

Explore more

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