Fibronectin enhances<i>Campylobacter fetus</i>interaction with extracellular matrix components and INT 407 cells
Bibliographic record
Abstract
Campylobacter fetus is a recognized pathogen of cattle and sheep that can also infect humans. No adhesins specific for C. fetus have to date been identified; however, bacterial attachment is essential to establish an infecting population. Scanning electron microscopy revealed C. fetus attachment to the serosal surface of human colonic biopsy explants, a location consistent with the presence of the extracellular matrix (ECM). To determine whether the ECM mediated C. fetus adherence, 7 C. fetus strains were assessed in a solid-phase binding assay for their ability to bind to immobilized ECM components. Of the ECM components assayed, adherence to fibronectin was noted for all strains. Attachment to ECM components was neither correlated with S-layer expression nor with cell-surface hydrophobicity. Ligand immunoblots, however, identified the S-layer protein as a major site of fibronectin binding, and modified ECM binding assays revealed that soluble fibronectin significantly enhanced the attachment of S-layer-expressing C. fetus strains to other ECM components. Soluble fibronectin also increased C. fetus adherence to INT 407 cells. This adherence was inhibited when INT 407 cells were incubated with synthetic peptides containing an RGD sequence, indicating that integrin receptors were involved in fibronectin-mediated attachment. Together, this data suggests that C. fetus can bind to immobilized fibronectin and use soluble fibronectin to enhance attachment to other ECM components and intestinal epithelial cells. In vivo, fibronectin would promote bacterial adherence, thereby, contributing to the initial interaction of C. fetus with mucosal and submucosal surfaces.
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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) | 0.001 | 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 | 0.001 |
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".