Interactions of<i>Pseudomonas aeruginosa</i>PA-IIL lectin with quail egg white glycoproteins
Bibliographic record
Abstract
Pseudomonas aeruginosa produces several lectins, including the galactophilic PA-IL and the fucose- and mannose-binding PA-IIL. The great advantage of these two lectins is their stability in purified preparations. Following observations that pigeon egg white blocks Escherichia coli P-fimbriae and PA-IL, we examined the interactions of diverse avian egg white components with PA-IIL. This lectin may represent both mannose- and fucose-specific microbial adhesins. For comparison, Con A (which also binds mannose) and Ulex europaeus lectin (UEA-I, which binds fucose) were analyzed in parallel. The lectin interactions with chicken, quail, and pigeon egg whites and several purified chicken egg white glycoproteins were examined by a hemagglutination inhibition test and Western blotting. Both analyses showed that like Con A and unlike UEA-I, which was not sensitive to any of these three egg whites, PA-IIL most strongly reacted with the quail egg white. However, in contrast with Con A, its interactions with the chicken egg white components, excluding avidin, were very poor. The results of this study might indicate the possibility that some of the egg white components that interacted with the above two mannose-binding lectins (exhibiting individual heterogeneity) might be associated with the innate immunity against mannose-specific microbial or viral adhesion during the fowl embryonic period.
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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) | 0.001 | 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".