Invasion of human epithelial cells by<i>Campylobacter upsaliensis</i>
Bibliographic record
Abstract
Few data exist on the interaction of Campylobacter upsaliensis with host cells, and the potential for this emerging enteropathogen to invade epithelial cells has not been explored. We have characterized the ability of C. upsaliensis to invade both cultured epithelial cell lines and primary human small intestinal cells. Epithelial cell lines of intestinal origin appeared to be more susceptible to invasion than non-intestinal-derived cells. Of three bacterial isolates studied, a human clinical isolate, CU1887, entered cells most efficiently. Although there was a trend towards more efficient invasion of Caco-2 cells by C. upsaliensis CU1887 at lower initial inocula, actual numbers of intracellular organisms increased with increasing multiplicity of infection and with prolonged incubation period. Confocal microscopy revealed C. upsaliensis within primary human small intestinal cells. Both Caco-2 and primary cells in non-confluent areas of the infected monolayers were substantially more susceptible to infection than confluent cells. The specific cytoskeletal inhibitors cytochalasin B, cytochalasin D and vinblastine attenuated invasion of Caco-2 cells in a concentration-dependent manner, providing evidence for both microtubule- and microfilament-dependent uptake of C. upsaliensis. Electron microscopy revealed the presence of organisms within Caco-2 cell cytoplasmic vacuoles. C. upsaliensis is capable of invading epithelial cells and appears to interact with host cell cytoskeletal structures in order to gain entry to the intracellular environment. Entry into cultured primary intestinal cells ex vivo provides strong support for the role of host cell invasion during human enteric C. upsaliensis infection.
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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) | 0.003 | 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".