Lactobacillus rhamnosus GG attenuates interferon-γ and tumour necrosis factor-α-induced barrier dysfunction and pro-inflammatory signalling
Bibliographic record
Abstract
The intestinal epithelium forms a protective barrier against luminal contents and the external environment, mediated via intercellular tight junctions (TJs). The TJ can be disrupted via cell signalling induced by either enteric pathogens or pro-inflammatory cytokines, thereby contributing to various intestinal disorders ranging from acute infectious diarrhoea to chronic inflammatory bowel diseases. Probiotics, such as Lactobacillus rhamnosus GG (LGG), are reported to confer beneficial effects on epithelial cells, including antagonizing infections and reducing overt pro-inflammatory responses, but the underlying mechanisms of these observed effects require further characterization. We hypothesized that probiotics preserve barrier function by interfering with pro-inflammatory cytokine signalling. Caco-2bbe cells were seeded into Transwells to attain polarized monolayers with intercellular TJs. Monolayers were inoculated apically with the probiotic LGG 3 h prior to the addition of IFN-γ (100 ng ml(-1)) to the basolateral medium overnight. The monolayers were then placed in fresh basal medium±TNF-α (10 ng ml(-1)) and transepithelial electrical resistance (TER) measurements were taken over the time-course of TNF-α stimulation. To complement the TER findings, cells were processed for zona occludens-1 (ZO-1) immunofluorescence staining. As a measure of TNF-α downstream signalling, cells were immunofluorescently stained for NF-κB p65 subunit and CXCL-8 mRNA was quantified by qRT-PCR. Basal cell culture medium was collected after overnight TNF-α stimulation to measure secreted chemokines, including CXCL-8 (interleukin-8) and CCL-11 (eotaxin). Following LGG inoculation, IFN-γ priming and 24 h TNF-α stimulation, epithelial cells maintained TER and ZO-1 distribution. LGG diminished the nuclear translocation of p65, demonstrated by both immunofluorescence and CXCL-8 mRNA expression. CXCL-8 and CCL-11 protein levels were decreased in LGG-inoculated, cytokine-challenged cells. These findings indicate that LGG alleviates the effects of pro-inflammatory cytokines on epithelial barrier integrity and inflammation, mediated, at least in part, through inhibition of NF-κB signalling.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".