Serine Proteases Decrease Intestinal Epithelial Permeability By A PKCζ‐mediated mechanism
Bibliographic record
Abstract
The transport of ions and the permeability to macromolecules across the epithelium regulates fluid balance in the gastrointestinal tract. The digestive serine proteases trypsin, elastase and chymotrypsin decrease the paracellular permeability of intestinal epithelial cells to Na + , Cl − and 3000MW dextran. We investigated the mechanisms involved in this possible barrier‐protective effect. Changes in transepithelial electrical resistance (R TE ) across intestinal epithelial cells were measured in Ussing chambers, employing several activators and inhibitors of signaling pathways. Activators of protease activated receptors (PARs)‐1,‐2 and ‐4 were without effect. Inhibitors of phosphoinositol‐specific phospholipase‐C (PLC), U73122 (50μM) and ET‐18‐OCH 3 (10μM), attenuated the trypsin‐induced increase in R TE by 92 ± 33 and 78 ± 24 % respectively. Protein kinase C enzymes are downstream effectors of PLC. Activation of typical and novel PKC isoforms with PMA (1μM) did not increase R TE and two broad spectrum inhibitors of PKCs did not inhibit the trypsin‐induced increase in R TE . However, an inhibitor specific for the atypical isoform PKCζ significantly decreased baseline R TE and prevented the trypsin‐induced increase in R TE (786 ± 118 vs.138 ± 36 Ω x cm 2 ; n=18 and 9; p<0.01). In accordance with the Ca 2+ ‐independence of PKCζ activation, pre‐treatment of the epithelial cells with the Ca 2+ ‐modulating agents BAPTA‐AM or 2‐APB did not affect the trypsin‐mediated increase in R TE . These data indicate a novel role for digestive serine proteases in the regulation of intestinal epithelial barrier function. The effect is independent of PARs and is mediated by PLC and PKCζ. Supported by CIHR/CAG‐CCFC
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".