Effects of fermented soybean supplementation on secretory immunoglobulin A, myeloperoxidase, and antioxidant capacity: a randomised, placebo-controlled dietary intervention trial
Bibliographic record
Abstract
Immune health and antioxidant defence play critical roles in protecting the body against infections, oxidative stress and inflammation. Both innate and adaptive immune responses are influenced by nutrition and diet, while antioxidants help maintain cellular homeostasis by mitigating oxidative damage. Fermented soybean (FSB) is rich in bioactive compounds like isoflavones and peptides, which have been shown to support immune function and antioxidant capacity. A randomised, placebo-controlled, 12-week intervention trial was performed on FSB supplementation The effects of FSB on immunological function and antioxidant status were evaluated at baseline and at weeks 4, 8, and 12. FSB intervention group demonstrated significantly higher secretory immunoglobulin A and myeloperoxidase levels compared to the baseline and placebo groups ( p < 0.05). Over the course of the trial, salivary total antioxidant capacity increased significantly ( p < 0.05). Our findings indicated FSB improved innate immunological and mucosal function, as well as antioxidant defence. FSB may serve as a functional food for enhancing immune support and regulating antioxidant status, particularly for younger individuals and specific populations at risk of infection. The study was registered on 29 July 2024 at clinicaltrials.gov (NCT06524271).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".