Hypersensitive response-like cell death and its key related genes in the <i>lmd</i> lesion mimic mutant of birch
Bibliographic record
Abstract
Lesion mimic mutants (LMMs) often display hypersensitive response-like (HR-like) cell death and enhanced resistance to pathogens. LMMs have been viewed as useful for the study of the mechanism of cell death and plant immunity. To date, few LMMs have been found in woody plants. We previously identified an LMM termed lmd, which showed spontaneous cell death in birch. In the current study, we investigated lmd, oe21 (transgenic control), and NT (nontransgenic control), focusing on cell death and gene expression profile of lmd. We found that cell death in the lmd occurred gradually during leaf development. The number of necrotic spots increased as the leaf developed, with no significant change in spot size. Subcellular observations showed degradation of both mitochondria and chloroplasts in lmd cells but not in NT and oe21 cells. Autophagosomes were visible in dying cells of lmd. We then performed RNA-seq of the four most apical leaves of lmd and oe21 to explore the gene expression profile during cell death. Genes that were functional in signal perception, respiratory burst, signal transduction, and defense were enriched. TGA1, WRKY33, WRKY40, Chitinase, FLS2, RbohA/D, and SBT were identified as key genes involved in cell death in lmd.
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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 | 0.001 |
| 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".