Almond protein hydrolysate fraction modulates the expression of proinflammatory cytokines and enzymes in activated macrophages
Bibliographic record
Abstract
Simulated gastrointestinal treatment of almond proteins with pepsin and pancreatic proteases resulting in 16.6% degree of hydrolysis or 1.33 milliequivalent leucine per g protein yielded a hydrolysate that modulated excessive nitric oxide production in lipopolysaccharide-activated RAW264.7 macrophages. After fractionation, a resulting fraction of molecular size > 5 kDa retained the nitric oxide modulatory effect observed initially in the crude hydrolysate. The high molecular size fraction was found to modulate levels of proinflammatory cytokines, interleukin (IL)-6, IL-1β, and tumour necrosis factor (TNF)-α in the activated cells. Immunoblotting analysis indicated that the hydrolysate fraction decreased the expression levels of inflammatory enzyme indicators, inducible nitric oxide synthase (iNOS) and cyclooxygenase (COX)-2 in the activated cells. RT-PCR analysis showed that treatment of the activated cells with the hydrolysate fraction resulted in the inhibition of relative gene expressions of proinflammatory IL-6, IL-1β, TNF-α, iNOS and COX-2. These results indicate a potential application of almond protein hydrolysates against inflammatory conditions, and will contribute to delineating the possible contributions of proteins to health benefits attributed to almond consumption.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".