TLR2 Plays a Pivotal Role in Mediating Mucosal Serotonin Production in the Gut
Bibliographic record
Abstract
Abstract Serotonin (5-hydroxytryptamine [5-HT]) is a key enteric signaling molecule that mediates various physiological processes in the gut. Enterochromaffin (EC) cells in the mucosal layer of the gut are the main source of 5-HT in the body and are situated in close proximity to the gut microbiota. In this study, we identify a pivotal role of TLR2 in 5-HT production in the gut. Antibiotic treatment reduces EC cell numbers and 5-HT levels in naive C57BL/6 mice, which is associated with downregulation of TLR2 expression but not TLR1 or TLR4. TLR2-deficient (Tlr2−/−) and Myd88−/− mice express lower EC cell numbers and 5-HT levels, whereas treatment with TLR2/1 agonist upregulates 5-HT production in irradiated C57BL/6 mice, which are reconstituted with Tlr2−/− bone marrow cells, and in germ-free mice. Human EC cell line (BON-1 cells) release higher 5-HT upon TLR2/1 agonist via NF-κB pathway. Tlr2−/− mice and anti-TLR2 Ab–treated mice infected with enteric parasite, Trichuris muris, exhibited attenuated 5-HT production, compared with infected wild-type mice. Moreover, excretory-secretory products from T. muris induce higher 5-HT production in BON-1 cells via TLR2 in a dose-dependent manner, whereby the effect of excretory-secretory products is abrogated by TLR2 antagonist. These findings not only suggest an important role of TLR2 in mucosal 5-HT production in the gut by resident microbiota as well as by a nematode parasite but also provide, to our knowledge, novel information on the potential benefits of targeting TLR2 in various gut disorders that exhibit aberrant 5-HT signaling.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".