Intestinal Expression of Fas and Fas Ligand Is Upregulated by Bacterial Signaling through TLR4 and TLR5, with Activation of Fas Modulating Intestinal TLR-Mediated Inflammation
Bibliographic record
Abstract
TLRs play an important role in mediating intestinal inflammation and homeostasis. Fas is best studied in terms of its function in apoptosis, but recent studies demonstrate that Fas signaling may mediate additional functions such as inflammation. The role of Fas, and the Fas ligand (FasL), in the intestine is poorly understood. The aim of this study was to evaluate potential cross-talk between TLRs and Fas/FasL system in intestinal epithelial cells (IECs). IECs were stimulated with TLR ligands, and expression of Fas and FasL was investigated. Treatment with TLR4 and TLR5 ligands, but not TLR2 and 9 ligands, increased expression of Fas and FasL in IECs in vitro. Consistent with this finding, expression of intestinal Fas and FasL was reduced in vivo in the epithelium of TLR4 knockout (KO), 5KO, and germ-free mice, but not in TLR2KO mice. Modulating Fas signaling using agonistic anti-Fas augmented TLR4- and TLR5-mediated TNF-α and IL-8 production by IECs. In addition, suppression of Fas in IECs reduced the ability of TLR4 and TLR5 ligands and the intestinal pathogens Salmonella typhimurium and Listeria monocytogenes to induce the expression of IL-8. In conclusion, this study demonstrates that extensive cross-talk in IECs occurs between the Fas and TLR signaling pathways, with the FasL/Fas system playing a role in TLR-mediated inflammatory responses in the intestine.
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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 | 0.001 | 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) | 0.003 | 0.001 |
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".