Optimization of Preparing Technology of Clam Peptide and Its Enhanced Immunomodulatory Effect
Bibliographic record
Abstract
Objective: Ruditapes philippinarum was used as raw material to investigate the preparation process of peptide and its enhanced immunomodulatory effect. Methods: The hydrolysis degree of protein was used as an evaluation index to screen the optimal protease. The single factor experiment and response surface test were used to determine the best enzymatic hydrolysis condition. The amino acid composition was analyzed using amino acid analyzer. And organ/body weight ratio, spleen lymphocyte transformation test, serum hemolysin experiment, peritoneal macrophage swallowing chicken red blood cell test, and NK cell activation experiment were used to assess the clam peptide enhanced immune activity. Results: Trypsin was the most suitable protease in the preparation of protein peptides from Ruditapes philippinarum. The optimal enzymatic conditions were temperature 48.4 ℃, pH8.0, enzyme concentration 3795 U/g, solid-liquid ratio 1:2, and hydrolysis time 4 hours. The average molecular weight of protein-peptide was 418 Da with 15.33% hydrolysis degree under optimal enzymatic conditions. The amino acid composition of the clam peptide was reasonable and the proportion of essential amino acids reached 41.48%. The organ ratio of BALB/c mice did not change significantly as compared to the control group after receiving various doses of oral clam peptides for 30 days. Furthermore, the serum hemolysin levels were significantly (P<0.05) increased of low dose (700 mg/(kg·d)) and high dose (2800 mg/(kg·d)) groups and the phagocytic rate of peritoneal macrophage swallowing chicken red blood cells was significantly (P<0.01) increased of low dose (700 mg/(kg·d)) and middle dose (1400 mg/(kg·d)) groups, which indicated the enhanced immunomodulatory effect of the clam peptide. Conclusions: The clam peptide produced using this process shows a high degree of hydrolysis, a low molecular weight, and a concentrated distribution with enhanced immune function. It has the potential to produce healthy foods or foods for special dietary uses.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".