Bacterial peptidoglycan breaks down intestinal tolerance via mast cell activation: The role of TLR2 and NOD2
Bibliographic record
Abstract
Intestinal microbes are believed to be involved in the pathogenesis of inflammatory bowel disease. Microbes and their products are generally well tolerated by intestinal epithelial cells in the intestinal tract of healthy individuals. It is of significance to understand what breaks down the established tolerance leading to intestinal barrier dysfunction and intestinal inflammation. T84 monolayer transported peptidoglycan (PGN) was determined by enzyme-linked immune assay. Mast cell line HMC-1 cell activation in response to PGN stimulation was observed with electron microscopy and measurement of histamine release. T84 monolayer barrier function was determined by recording the transepithelial electric resistance (TER) and measuring the permeability in response to PGN-induced HMC-1 cell activation. Expression of Toll-like receptor (TLR) 2 and nucleotide-binding oligomerization domain (NOD) 2 were determined by immunocytochemistry, real-time reverse transcription (RT)-PCR and Western blot. Exposure to PGN alone did not alter TER and permeability of T84 monolayers. T84 monolayers transported PGN from the apical chamber to the basal chamber of transwell system. TLR2 expressed on the surface of HMC-1 cells. HMC-1 cells absorbed PGN. HMC-1 cells released histamine in response to the PGN stimulation, which was blocked by pretreatment with antibodies or small interfering RNA against TLR2 or NOD2. In a co-culture system, T84 monolayer transported PGN activated HMC-1 cells and increased the horseradish peroxidase flux. TLR2 mediated the PGN-absorption in HMC-1 cells. Blockade of TLR2 or NOD2 abolished PGN-induced HMC-1 cell activation and T84 monolayer barrier dysfunction. T84 monolayer transported PGN activates HMC-1 cells to release chemical mediators to induce T84 monolayer dysfunction that are mediated by TLR2 and NOD2.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".