Distribution and Regulation of Aquaporins in Intestinal Epithelial Cells
Bibliographic record
Abstract
Sodium absorption and chloride secretion create osmotic gradients that drive water transport across intestinal epithelial cells. Aquaporins (AQP) are tetrameric water‐selective channels that may play an important role in facilitating transcellular water movement and maintaining physiological electrolyte balance. In the kidney, key AQPs are regulated by intracellular cAMP. We hypothesized that the cellular distribution of AQPs in the intestinal epithelium is regulated by cAMP. RT‐PCR of three intestinal epithelial cell lines demonstrated mRNA expression of: AQP1, 2, 3, and 5 in SCBN; AQP1, 2, 3, 5, 7, 8, and 9 in T84; and AQP1, 2, 3, 4, and 5 in CMT. Confocal imaging showed immunoreactivity for AQP1, 2, 3, 4, and 7 in SCBN and AQP1, 4, 6, and 9 in T84. Real time confocal live cell imaging tracked intracellular movement of GFP‐linked human AQP1 gene construct transfected into T84 cells. It suggested an increase in apical fluorescence of AQP1 within 20 min of forskolin (FSK) treatment. Cellular fractionation of CMT whole cell lysate by differential centrifugation showed a significant FSK‐dependent increase in AQP1 protein in the plasma membrane and no FSK‐induced change in the intracellular fraction. This study demonstrates that multiple AQPs are expressed in intestinal epithelial cell lines, and provides evidence for cAMP‐dependent regulation of AQP1 trafficking. Supported by 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) | 0.000 | 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 | 0.001 |
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".