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Milk Proteins and Amino Acids Modulate Inflammatory Gene Expression in Vascular Endothelial Cells

2016· article· en· W4389007613 on OpenAlexaff
Marine S. Da Silva, Cyril Bigo, Olivier Barbier, Iwona Rudkowska

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsUniversité LavalCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsValineIsoleucineAmino acidGlutamineLeucineHydrolysateChemistryBiochemistryTumor necrosis factor alphaInflammationGene expressionGeneBiologyImmunology

Abstract

fetched live from OpenAlex

The digestion of milk proteins releases bioactive peptides and amino acids which may be beneficial for cardiovascular protection. However, mechanisms underlying the lowering effect of milk proteins on systemic inflammation, a cardiovascular disease (CVD) risk factor, remain to be elucidated. Objective To investigate the effect of milk proteins and their major amino acid components on inflammatory gene expression in vitro . Methods Human umbilical vein endothelial cells (HUVEC), stimulated or not with TNFα to trigger inflammation, were incubated for 24h with 1‐ milk proteins: whey protein (0.5 or 5 mg/ml); isolate (WPI) or hydrolysate ((WPH) a mixture of bioactive peptides and amino acids); caseins (CN, 1 mg/ml); a mixture of WPI and CN (WPCN, 1:4 w/w); or 2‐ amino acids (0.2–20 mM): branched‐chain amino acids ((BCAA) including leucine, isoleucine and valine), glutamine or proline. Expression of pro‐inflammatory genes TNF and VCAM‐1 was measured by RT‐PCR. Results WPI caused a down‐regulation of the two pro‐inflammatory genes, whereas WPH and its major BCAA, leucine and isoleucine, had no effect in unstimulated cells. Furthermore in these cells, both CN and WPCN decreased VCAM‐1 expression; however, TNF expression was increased by the mixture WPCN. Glutamine‐ the major amino acid of CN, and valine‐ a BCAA found in both milk proteins, up‐regulated the pro‐inflammatory genes in unstimulated cells. Stimulation of HUVEC with TNFα caused increased expression of TNF and VCAM‐1 . This effect was partially inhibited by WPH and the three BCAA; whereas WPI had no effect in stimulated cells. In addition, CN and WPCN lowered VCAM‐1 together with an increased TNF gene expression in stimulated cells. Glutamine increased VCAM‐1 expression in stimulated cells. Proline had no effects. Conclusion Whey proteins (WPI and WPH) and BCAA exerted anti‐inflammatory effects; whereas CN, the mixture WPCN and glutamine showed pro‐inflammatory properties according to the inflammatory state of endothelial cells. These results support the potential of whey proteins for CVD prevention.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), 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".

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Citations1
Published2016
Admission routes1
Has abstractyes

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