The influence of simple sugars, salts, and<i>Botrytis</i>-specific monoclonal antibodies on the binding of bacteria and yeast to germlings of<i>Botrytis cinerea</i>
Bibliographic record
Abstract
The influence of simple sugars, salts, and Botrytis-specific monoclonal antibodies on the binding of three bacteria (Enterobacter aerogenes Hormaeche & Edwards, Enterobacter cloacae (Jordan) Hormaeche & Edwards, and Ochrobactrum anthropii gen.nov.) and three yeasts (Candida sake (Sarto & Ota) van Uden & Buckley, Candida pulcherrima (Lindner) Windisch, and Trichosporon pullulans (Lindner) Diddens & Lodder) to Botrytis cinerea (Persoon:Fr) was examined. Solutions of 0.1 M D(+)-galactose, L-fucose, or Botrytis-specific monoclonal antibodies significantly reduced populations of E. aerogenes and E. cloacae adhering to pathogen germlings, whereas 0.1 M raffinose significantly reduced C. sake or C. pulcherrima adhesion. In cytochemical studies, lectin-gold labeling demonstrated the presence of galactose moieties in the walls or matrix of E. aerogenes, and this labeling was diminished in bacteria that were attached to B. cinerea. Immunolabeling with a Botrytis-specific monoclonal antibody that recognizes a glycoprotein was particularly intense in condensed regions of the pathogen matrix associated with adherent E. aerogenes, whereas C. sake - B. cinerea interactions revealed a loose encapsulation of adherent yeast cells by the matrix of B. cinerea. Results from this study suggest the presence of several adhesion mechanisms that can be distinguished according to yeast or bacterial binding and further defined according to the genus.Key words: adhesion, bacteria, biocontrol, Botrytis cinerea, ultrastructure, yeast.
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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 | 0.001 |
| 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".