Immunomodulating effects of milks fermented by <i>Lactobacillus helveticus</i> and its non-proteolytic variant
Bibliographic record
Abstract
The effect of milks fermented by Lactobacillus helveticus and its non-proteolytic variant on mucosal and tumoral immunity was studied. Milks fermented by Lb. helveticus wild type or its non-proteolytic variant were administered orally to mice for different periods (3, 5 and 7 d). The immune response was assessed by analysing the activity of the peritoneal macrophages, the number of cells secreting IgA associated with the gut-associated lymphoid tissue and with the bronchial-associated lymphoid tissue. The number of cells was determined by direct immunofluorescence. The antitumour activity was monitored by studying the regression of the subcutaneously implanted fibrosarcomas. After 3 d feeding of milk fermented by Lb. helveticus wild type, the number of sIgA increased significantly at both the intestinal and bronchial levels, indicating that a cellular migration had occurred. This effect was not noticeable when milk fermented by Lb. helveticus Protease (-) was orally administered. Both fermented milks (wild type or its variant) exhibited an effect on the activity of the peritoneal macrophages, which might be indirectly correlated to the regression of the fibrosarcoma. Although the mechanism by which the lactic acid bacteria enhance the immune system is not clear, this study clearly suggests that the bioactive compounds released during milk fermentation might contribute to the immunoenhancing properties of these products. By releasing biopeptide, lactic acid bacteria have important implications in modulation of the host's immune response, more specifically its cellular immune response.
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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".