The binding of<i>Proteus mirabilis</i>nonagglutinating fimbriae to ganglio-series asialoglycolipids and lactosyl ceramide
Bibliographic record
Abstract
Proteus mirabilis is a common opportunistic Gram-negative uropathogen that infects the upper urinary tract. We have examined the role of the nonagglutinating fimbriae (NAF) of P. mirabilis in mediating bacterial adhesion to cell surface receptors. Purified NAF of P. mirabilis were demonstrated to bind to a number of glycolipids, including asialo-GM1, asialo-GM2, and lactosyl ceramide (LacCer) in solid-phase binding assays and in thin layer chromatography (TLC) overlay assays. Furthermore, preincubation of the biotinylated NAF (Bt-NAF) with anti-NAF monoclonal antibodies resulted in inhibition of NAF binding to immobilized asialo-GM1, asialo-GM2, and LacCer. In adherence assays, P. mirabilis binding to Madin-Darby canine kidney (MDCK) cells was inhibited by murine anti-asialo-GM1 monoclonal antibodies H2G10 to about 50% of the binding level in the absence of the antibody, specific for the terminal beta-galactopyranosyl residue of asialo-GM1 (Harrison et al. 1998). The results of this study suggest that NAF of P. mirabilis recognize a GalNAc beta 1-4Gal moiety present in the ganglio-series of asialoglycolipids, and that the terminal beta-galactopyranosyl-containing glycoconjugates play a role in NAF-mediated adherence of P. mirabilis to MDCK cells. Similarly to other bacteria, P. mirabilis NAF was also shown to express the LacCer specificity.
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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) | 0.001 | 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".