ClC-2 Contributes to Native Chloride Secretion by a Human Intestinal Cell Line, Caco-2
Bibliographic record
Abstract
It has been previously determined that ClC-2, a member of the ClC chloride channel superfamily, is expressed in certain epithelial tissues. These findings fueled speculation that ClC-2 can compensate for impaired chloride transport in epithelial tissues affected by cystic fibrosis and lacking the cystic fibrosis transmembrane conductance regulator. However, direct evidence linking ClC-2 channel expression to epithelial chloride secretion was lacking. In the present studies, we show that ClC-2 transcripts and protein are present endogenously in the Caco-2 cell line, a cell line that models the human small intestine. Using an antisense strategy we show that ClC-2 contributes to native chloride currents in Caco-2 cells measured by patch clamp electrophysiology. Antisense ClC-2-transfected monolayers of Caco-2 cells exhibited less chloride secretion (monitored as iodide efflux) than did mock transfected monolayers, providing the first direct molecular evidence that ClC-2 can contribute to chloride secretion by the human intestinal epithelium. Further, examination of ClC-2 localization by confocal microscopy revealed that ClC-2 contributes to secretion from a unique location in this epithelium, from the apical aspect of the tight junction complex. Hence, these studies provide the necessary rationale for considering ClC-2 as a possible therapeutic target for diseases affecting intestinal chloride secretion such as cystic fibrosis.
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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 | 0.001 | 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".