<i>Sclerotinia sclerotiorum</i>: When âto be or not to beâ a pathogen?
Bibliographic record
Abstract
Sclerotinia sclerotiorum is unusual among necrotrophic pathogens in its requirement for senescent tissues to establish an infection and to complete the life cycle. A model for the infection process has emerged whereby the pathogenic phase is bounded by saprophytic phases; the distinction being that the dead tissues in the latter are generated by the actions of the pathogen. Initial colonization of dead tissue provides nutrients for pathogen establishment and resources to infect healthy plant tissue. The early pathogenicity stage involves production of oxalic acid and the expression of cell wall degrading enzymes, such as specific isoforms of polygalacturonase (SSPG1) and protease (ASPS), at the expanding edge of the lesion. Such activities release small molecules (oligo-galacturonides and peptides) that serve to induce the expression of a second wave of degradative enzymes that collectively bring about the total dissolution of the plant tissue. Oxalic acid and other metabolites and enzymes suppress host defences during the pathogenic phase, while other components initiate host cell death responses leading to the formation of necrotic tissue. The pathogenic phase is followed by a second saprophytic phase, the transition to which is effected by declining cAMP levels as glucose becomes available and further hydrolytic enzyme synthesis is repressed. Low cAMP levels and an acidic environment generated by the secretion of oxalic acid promote sclerotial development and completion of the life cycle. This review brings together histological, biochemical and molecular information gathered over the past several decades to develop this tri-phasic model for infection. In several instances, studies with Botrytis species are drawn upon for supplemental and supportive evidence for this model. In this process, we attempt to outline how the interplay between glucose levels, cAMP and ambient pH serves to coordinate the transition between these phases and dictate the biochemical and developmental events that define them.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".