Genetic background affects genetically modified ethylene sensing in birch–insect interaction
Bibliographic record
Abstract
Several studies suggest that ethylene is involved in the responses and resistance of plants against herbivores and pathogens, but the role of ethylene seems to vary depending on the system studied. Here we extend the studies of introduced Arabidopsis thaliana (L.) Heynh. ethylene receptor gene (etr1-1) to a new type of interaction: a woody plant, Betula pendula Roth (silver birch) and its herbivore, Epirrita autumnata (Borkhausen) (autumnal moth). We studied constitutive insect resistance of two wild-type birch genotypes, V and J, which were very different hosts for E. autumnata. On the J background, genetically modified ethylene insensitivity decreased the performance of E. autumnata, measured as leaf damage, larval mass, or pupal mass. However, hardly any changes were detectable in the V background, which is an inferior wild-type genotype for autumnal moth performance, except increased leaf damage caused by E. autumnata in ethylene-insensitive trees. Ethylene insensitivity caused clear side effects on birch phenology and morphology, especially in the J background. In this background, ethylene modification mainly acted via accelerating phenology, but this was hardly detectable in the V genotype. Also, the number of long shoots increased only in the modified J background. Taken together, it seems that the effects of ethylene on several birch traits relevant for E. autumnata and birch morphology depend on the birch genetic background.
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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".