Dairy proteins and branched‐chain amino acids stimulate GLP‐1 release and downregulate genes involved in fatty acid and cholesterol metabolism in the human NCI‐H716 cell line
Bibliographic record
Abstract
The possibility that increased dairy intake can reduce body weight or exaggerate weight loss is attracting an increasing amount of attention. The objective of this work is to test the hypothesis that dairy proteins and branched‐chain amino acids (BCAA) regulate satiety hormone secretion, and modulate selective genes involved in fatty acid and cholesterol metabolism. A human intestinal cell line was used to determine the dose effects of skim milk, casein, whey, leucine, isoleucine and valine on glucagon‐like peptide‐1 (GLP‐1) release and the mRNA expression of i‐FABP (intestinal type fatty acid binding protein), FATP4 (fatty acid transport protein), NPC1L1 (Niemann‐Pick C1 like protein), ACC (acetyl CoA carboxylase), FAS (fatty acid synthase), SREBP‐2 (sterol regulatory element‐binding protein‐2) and HMGCR [3‐hydroxy‐3‐methylglutary‐CoA (HMG‐CoA) reductase]. The results showed that skim milk, casein, leucine and isoleucine stimulated GLP‐1 release. Whey and isoleucine down‐regulated the expressions of i‐FABP, FATP4, NPC1L1, ACC, FAS, SREBP‐2 and HMGCR. Skim milk and casein down‐regulated the expression of ACC, FAS, and SREBP‐2, but not i‐FABP, FATP4 and NPC1L1. Leucine and valine down‐regulated the expressions of NPC1L1, ACC, FAS, SREBP‐2 and HMGCR, but not i‐FABP, FATP4. The findings suggested that the anti‐obesity effect of dairy may be mediated, in part, by integration of events that promote GLP‐1 secretion and inhibit expression of genes involved in fatty acid and cholesterol absorption and synthesis. (Supported by CIHR and NSERC)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".