Plant immune resilience to a changing climate: molecular insights and biotechnological roadmaps
Bibliographic record
Abstract
Successful resistance to disease-causing pathogens is underpinned by properly regulated immune signalling and defence responses in plants. The plant immune system is controlled at multiple levels of gene and protein regulation-from chromatin-associated epigenetic processes to protein post-translational modifications. Optimal fine-tuning of plant immune signalling and responses is important to prevent plant disease development, which is being exacerbated by a globally changing climate. In this review, we focus on how changing climatic factors mechanistically intercept plant immunity at different levels of regulation (chromatin, transcriptional, post-transcriptional, translational, and post-translational). We specifically highlight recent studies that have provided molecular insights into critically important climate-sensitive nodes and mechanisms of the plant immune system. We then propose several potential future directions to build climate-resilient plant disease resistance using cutting-edge biotechnology. Overall, this conceptual understanding and promising biotechnological advances provide a foundational platform towards novel approaches to engineer plant immune resilience.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".