First Extensive Microscopic Study of Butternut Defense Mechanisms Following Inoculation with the Canker Pathogen <i>Ophiognomonia clavigignenti-juglandacearum</i> Reveals Compartmentalization of Tissue Damage
Bibliographic record
Abstract
Ophiognomonia clavigignenti-juglandacearum endangers the survival of butternut (Juglans cinerea) throughout its native range. While screening for disease resistance, we found that artificial inoculations of 48 butternut seedlings with O. clavigignenti-juglandacearum induced the expression of external symptoms, but only after a period of dormancy. Before dormancy, compartmentalized tissues such as necrophylactic periderms (NPs) and xylem reaction zones (RZs) contributed to limiting pathogen invasion. Phenols were regularly detected in RZs, often in continuity with NPs during wound closure, and confocal microscopy revealed their presence in parenchyma cells, vessel plugs and cell walls. Vessels were blocked with tyloses and gels, particularly those present in RZs. Suberin was also detected in cells formed over the affected xylem by the callus at the inoculation point, in a few tylosis walls, and in longitudinal tubes that formed near NPs. Following dormancy, in all inoculated seedlings but one, defensive barriers were breached by O. clavigignenti-juglandacearum and then additional ones were produced in response to this new invasion. The results of this histopathological study indicate that trees inoculated in selection programs to test butternut canker resistance should go through at least one period of dormancy and that asymptomatic individuals should be dissected to better assess how they defend themselves against O. clavigignenti-juglandacearum.
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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".