Osteopontin is associated with Citrobacter rodentium attachment and formation of attaching-effacing lesions.
Bibliographic record
Abstract
Osteopontin (OPN) is a complex glyco-phosphoprotein implicated in a number of biological processes, including inflammatory and autoimmune conditions. OPN is increased in the serum and mucosa of patients with inflammatory bowel diseases (IBD) and mediates innate and adaptive immunity in human disease and animal models of inflammation. However, the role of OPN in IBD pathogenesis is yet to be defined. Recently we showed that OPN−/− mice are partially protected from colitis induced by Citrobacter rodentium (an infectious model of IBD), as indicated by reduced epithelial cell hyperplasia and bacterial colonization of infected mice when OPN was absent. Therefore, our hypothesis was that OPN mediates gut inflammation by promoting bacterial attachment to cells. The objective of this study was to determine the potential effect of OPN on bacterial attachment and the formation of attaching-effacing (A/E) lesions induced by C. rodentium infection. HeLa, NIH 3T3, and HT-29 cells were incubated with C. rodentium for 4 h and then fixed and stained with phalloidin (to visualise actin in A/E lesions), anti-OPN antibody, and DAPI. Co-localization of bacteria, A/E lesions, and OPN was examined using laser confocal immunofluorescence microscopy. Effects of OPN on A/E lesions were assessed by addition of varying concentrations of bovine or recombinant OPN to the growth medium and enumeration of A/E lesions using systematic quantification. HeLa cells were transfected with a FLAG-tagged OPN-expression vector, and then incubated with C. rodentium to assess effects of OPN over-expression on A/E lesions.
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) | 0.001 | 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 | 0.001 | 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".