Histopathologic characterization of the process of <i>Marssonina brunnea</i> infection in poplar leaves
Bibliographic record
Abstract
Marssonina brunnea (Ellis & Everh.) Magnus, the causative pathogen of Marssonina leaf spot of poplars (MLSP), can lead to complete defoliation and tree death. Although MLSP has been studied for over 30 years, its precise process of infection is currently unclear. In this study, we present the process of M. brunnea infection in detail using several types of microscopy. When the conidia came into contact with the poplar leaves, they developed germ tubes to attach to the leaf surface. During the first 2 days post inoculation (dpi), infection vesicles (IV) and primary hyphae (PH) formed within host cells. The plasma membranes of the host cells penetrated by IV remained unbroken and intact organelles were visible, indicating that the IV did not kill the host cell. At 3 dpi, secondary hyphae (SH) began to appear within and outside the host cells. The ultrastructural evidence indicated that the SH could kill the host cells rapidly, producing black spots on the surfaces of the leaves. These results collectively suggested that M. brunnea is a typical hemibiotrophic fungus. In addition, M. brunnea could develop intercellular infective hyphae (IH) for expansion. Our findings also confirmed that the germ tubes, IV, and SH are crucial structures for the disease interactions and showed that the two formae speciales of M. brunnea share the same infection histopathological features. This provides important insight for further research into M. brunnea.
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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 | 0.001 | 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".