Preventing <i>Ralstonia solanacearum</i> adhesion with glycans from cashew, cocoa, coffee, pumpkin, and tomato seed extract
Bibliographic record
Abstract
Ralstonia solanacearum wilts many plants, causing heavy agricultural losses. Its pathogenic strain ATCC 11696 produces 2 hemagglutinating lectins: RSL and RS-IIL. These lectins may bind to terminal l-fucose-, d-arabinose-, and d-mannose-bearing seedling xylem cell wall glycans, thus enabling pathogen adhesion to them, with devastating infection establishment. Blocking the active sites of these lectins with seed embryo-surrounding oligo- and poly-saccharides hampers binding of the lectins to the embryos. The current study shows that seeds of cashew, cocoa, coffee, pumpkin, and tomato contain low and high molecular mass glycans that block RSL and RS-IIL (like its homologous Pseudomonas aeruginosa PA-IIL lectin). The blocking of the pathogen lectins, which is attributable to the documented composition of the oligo- and poly-saccharides of these seeds, is similar to that observed with animal glycoproteins of avian egg whites (protecting their embryos from infections) and of milk and royal jelly, which likewise protect mammal and bee neonates, respectively. RSL was most strongly inhibited by cashew seed glycans, and RS-IIL by coffee seed glycans. Western blot analyses with these lectins instead of antibodies revealed the hitherto undescribed presence of lectin-binding glycoproteins in the coffee, pumpkin, tomato, and cashew (but not cocoa) seeds. The use of these lectins for unveiling potent embryo-protecting seed glycans might be helpful for seedling-bioprotection projects similar to those planned for animal protection against antibiotic-resistant infections.
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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".