Gap junction hemichannels contribute to the generation of diarrhoea during infectious enteric disease
Bibliographic record
Abstract
OBJECTIVE: The attaching and effacing (A/E) pathogens enterohaemorrhagic Escherichia coli, enteropathogenic E coli and Citrobacter rodentium colonise intestinal tracts, attach to enterocytes, collapse infected cell microvilli and alter numerous host cell processes during infection. Enterocyte alterations result in numerous small molecules being released from host cells that likely contribute to diarrhoeal phenotypes observed during these infections. One possible route for small molecules to be released from intestinal cells may be through functional gap junction hemichannels. Here we examine the involvement of these hemichannels during the diarrhoeal disease caused by A/E pathogens in vivo. DESIGN: Mice were infected with the diarrhoea-causing murine A/E pathogen C rodentium for 7 days. Connexin43 (Cx43) protein levels and immunolocalization in the colon were initially used to determine alterations during A/E bacterial infections in vivo. Connexin mimetic peptides and connexin permeable tracer molecules were used to gage the presence and function of unpaired connexin hemichannels. The role of Cx43 in diarrhoea generation was assessed by comparing infections of wild-type mice to Cx43 mutant mice and determining the water abundance in the colonic luminal material. RESULTS: We demonstrate that Cx43 protein levels are increased in colonocytes during in vivo A/E bacterial infections, resulting in functionally open connexon hemichannels in apical membranes of infected cells. moreover, infected Cx43 +/- mice do not suffer from diarrhoeal disease. CONCLUSIONS: This study provides the first evidence that functional connexon hemichannels can occur in the intestine and are a novel molecular mechanism of water release during infectious diarrhoea.
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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 | 0.000 |
| 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".