Bifidobacterium breve DSM 32583 and Limosilactobacillus fermentum CECT5716 postbiotics attenuate S. aureus and IL-33-induced Th2 responses
Bibliographic record
Abstract
Over the past decades, the prevalence of allergic diseases noticeably increased in industrialized countries. The Th2 immune response plays a central role in these pathologies and its modulation using pro-/postbiotics constitutes a promising approach to prevent or alleviate disease symptoms. The aim of this in vitro study, was to investigate the ability of human milk-derived Bifidobacterium breve DSM 32583 (Bb) and Limosilactobacillus fermentum CECT5716 (Lf), to modulate the Th2 induced responses. To this end, Th2 cells were generated by co-culturing of human naïve Th cells with monocyte-derived dendritic cells (moDCs) either stimulated with Staphylococcus aureus or IL-33. The immunomodulatory effects of pro-/postbiotic preparations of Bb and Lf on moDCs and Th2 cells were evaluated in terms of maturation markers expression and cytokines production. Remarkably, the tested strains induced the anti-inflammatory cytokine IL-10 in moDCs, in a strain-, dose- and viability-dependent manner with no significant upregulation of IL-12p70 nor CD83, CD86 or HLA-DR. Interestingly, Bb and Lf postbiotics were able to dampen the Th2/Th1 response induced upon S. aureus- or IL-33 stimulation. They were also able to synergistically induce IL-10 in moDCs and T cells, upon co-stimulation with LPS. Finally, we observed that live probiotics triggered a mild Th1 response that was attenuated in the presence of galacto-oligosaccharides. Altogether, Bb and Lf pro-/postbiotics exhibited remarkable immune regulatory effects on both moDCs and Th2 cells. Therefore, further in vivo studies should be considered to validate these findings and assess their ability to prevent allergy or alleviate its symptoms in affected patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".