Feasibility Trial Exploring Immune-Related Biomarkers Pertaining to Rapid Immune Surveillance and Cytokine Changes after Consuming a Nutraceutical Supplement Containing Colostrum- and Egg-Based Low-Molecular-Weight Peptides
Bibliographic record
Abstract
Immune protection associated with consuming colostrum-based peptides is effective against bacterial and viral insults. The goal for this study was to document acute changes to immune surveillance and cytokine levels after consuming a single dose of a nutraceutical blend in the absence of an immune challenge. A double-blind, randomized, placebo-controlled, cross-over pilot study involved healthy participants attending two clinic visits. Blood draws were performed pre-consumption and at 1, 2, and 24 h after consuming a blend of bovine colostrum- and hen’s egg-based low-molecular-weight peptides (CELMPs) versus a placebo. Immunophenotyping was performed by flow cytometry, and serum cytokines were measured by multiplex cytokine arrays. Consumption of CELMPs triggered increased immune surveillance after 1 h, involving monocytes (p < 0.1), natural killer (NK) cells (p < 0.1), and natural killer T (NKT) cells (p < 0.05). The number of NKT cells expressing the CD25 immunoregulatory marker increased at 1 and 2 h (p < 0.1). Increased serum levels of monocyte chemoattractant protein-1 (MCP-1) was observed at 2 and 24 h (24 h: p < 0.05). Selective reduction in pro-inflammatory cytokines was seen at 1, 2, and 24 h, where the 2-h reduction was highly significant for IL-6, IFN-γ, and IL-13. The rapid, transient increase in immune surveillance, in conjunction with the reduced levels of inflammatory markers, suggests that the CELMP blend of natural peptides provides immune benefits of use in preventive medicine. Further studies are warranted in chronic inflammatory conditions.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".