Calcium-Sensing Receptor (CaSR)-Mediated Anti-inflammatory Effects of <scp>l</scp>-Amino Acids in Intestinal Epithelial Cells
Bibliographic record
Abstract
Calcium-sensing receptor (CaSR) plays an essential role in sensing nutrients and monitoring ion balance in the human gut. However, no discovery of CaSR-mediated anti-inflammatory effect of l-amino acids (l-AAs) on the gut system has been reported. The aim of this study is to screen and identify the anti-inflammatory activity of various l-AAs in intestinal epithelial cells (IECs) and stepwise illustrate a possible molecular mechanism for anti-inflammation. We used Caco-2 and HT-29 cell lines to evaluate the anti-inflammatory activity of l-AAs and revealed that l-tryptophan (l-Trp) and l-valine (l-Val) have strong anti-inflammatory activity consistent in both cell lines. l-Trp treatment (5 mM) reduced TNF-α-induced IL-8 secretion from HT-29 or Caco-2 cells to about 50 or 40%, respectively. l-Trp also significantly inhibited the expression of phosphorylation of JNK or IκBα to around 50% in HT-29 cells. However, the above inhibitory effects of l-Trp on inflammatory responses in TNF-α-induced HT-29 cells were abrogated by NPS-2143. The result of CaSR antagonist NPS-2143 pretreatment study suggests l-Trp exerts anti-inflammatory effects on IECs through CaSR activation. The involvement of β-arrestin2 was then found to block tumor necrosis factor (TNF)-α-induced signaling pathways after CaSR activated by l-Trp. These results validate a novel mechanism underlying CaSR agonistic l-AAs exerting anti-inflammatory effects on human intestinal epithelia.
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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 | 0.000 | 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".