Attaching and Effacing Pathogen Infection Causes an Increase in Functional Connexin 43 Hemichannels to Generate Diarrhea.
Bibliographic record
Abstract
The attaching and effacing (A/E) pathogens enterohemorrhagic Escherichia coli and enteropathogenic E. coli cause serious diarrheal diseases. These organisms colonize the apices of the intestinal mucosa and inject pathogenic effectors into host cells altering sub‐cellular epithelial cell components. During these infections small molecules are released from the cells into the lumen of intestinal tracts, contributing to diarrhea. We investigate the role of gap junctions, a group of intercellular channels involved in the transport of small molecules and water, during A/E pathogen infection. Gap junctions are composed of paired connexon channels; however single connexon hemichannels also exist. Each connexon is formed by connexin (Cx) monomers. Using Citrobacter rodentium , a natural murine A/E pathogen, we show that Cx43 protein levels are increased and re‐localized during infection. Cx43 that normally localizes only to the lateral membrane of colonocytes was also localized at the infected cell apices forming functionally open hemichannels. During C. rodentium infection, Cx43 mutant mice had abolished diarrheal phenotypes while maintaining the bacterial colonization levels of wild‐type infections. These results provide the first evidence of connexon hemichannel formation to generate diarrhea and provides a novel target for future therapeutics to prevent bacterially‐induced diarrheal disease. Grant Funding Source CIHR and NSERC
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".