Responses of Well-Differentiated Airway Epithelial Cell Cultures from Healthy Donors and Patients with Cystic Fibrosis to <i>Burkholderia cenocepacia</i> Infection
Bibliographic record
Abstract
Well-differentiated cultures established from airway epithelia of patients with cystic fibrosis (CF cultures) exhibited goblet cell hyperplasia, increased secretion of mucus, and higher basal levels of interleukin-8 than similarly cultured cells from healthy donors. Upon apical infection with low doses (10(4) to 10(5) CFU) of Burkholderia cenocepacia isolate BC7, the two cultures gave different responses. While normal cultures trapped the added bacteria in the mucus layer, killed and/or inhibited bacterial replication, and prevented bacterial invasion of the cells, CF cultures failed to kill and/or supported the growth of bacteria, leading to invasion of underlying epithelial cells, compromised transepithelial permeability, and cell damage. Depletion of the surface mucus layer prior to bacterial infection rendered the normal cultures susceptible to bacterial invasion, but the invading bacteria were mainly confined to vacuoles within the cells and appeared to be nonviable. In contrast, bacteria that invaded cells in CF cultures were found free in the cytoplasm surrounded by intermediate filaments and also between cells. Cultured CF airway epithelium was therefore more susceptible to infection than normal epithelium. This mimics CF tissue in vivo and illustrates differences in the way epithelia in CF patients and normal subjects handle bacterial infection. In addition, we found that the CF and normal cell cultures responded differently not only to isolate BC7 but also to isolates of other B. cepacia complex species. We therefore conclude that this cell culture model is suitable for investigation of B. cepacia complex pathogenesis in CF patients.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".