Effect of Probiotics Lactobacillus and Bifidobacterium on Gut-Derived Lipopolysaccharides and Inflammatory Cytokines: An In Vitro Study Using a Human Colonic Microbiota Model
Bibliographic record
Abstract
Gut-derived lipopolysaccharides (LPS) are critical to the development and progression of chronic low-grade inflammation and metabolic diseases. In this study, the effects of probiotics Lactobacillus and Bifidobacterium on gut-derived lipopolysaccharide and inflammatory cytokine concentrations were evaluated using a human colonic microbiota model. Lactobacillus reuteri, L. rhamnosus, L. plantarum, Bifidobacterium animalis, B. bifidum, B. longum, and B. longum subsp. infantis were identified from the literature for their anti-inflammatory potential. Each bacterial culture was administered daily to a human colonic microbiota model during 14 days. Colonic lipopolysaccharides, and Gram-positive and negative bacteria were quantified. RAW 264.7 macrophage cells were stimulated with supernatant from the human colonic microbiota model. Concentrations of TNF-alpha, IL-1beta, and IL-4 cytokines were measured. Lipopolysaccharide concentrations were significantly reduced with the administration of B. bifidum (-46.45 +/- 5.65%), L. rhamnosus (-30.40 +/- 5.08%), B. longum (-42.50 +/- 1.28%), and B. longum subsp. infantis (-68.85 +/- 5.32%) (p < 0.05). Cell counts of Gram-negative and positive bacteria were distinctly affected by the probiotic administered. There was a probiotic strain-specific effect on immunomodulatory responses of RAW 264.7 macrophage cells. B. longum subsp. infantis demonstrated higher capacities to reduce TNF-alpha concentrations (-69.41 +/- 2.78%; p < 0.05) and to increase IL-4 concentrations (+16.50 +/- 0.59%; p < 0.05). Colonic lipopolysaccharides were significantly correlated with TNF-alpha and IL-1beta concentrations (p < 0.05). These findings suggest that specific probiotic bacteria, such as B. longum subsp. infantis, might decrease colonic lipopolysaccharide concentrations, which might reduce the proinflammatory tone. This study has noteworthy applications in the field of biotherapeutics for the prevention and/or treatment of inflammatory and metabolic diseases.
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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".