SIPK signaling controls multiple components of harpin‐induced cell death in tobacco
Bibliographic record
Abstract
Harpin from Pseudomonas syringae pv. phaseolicola (HrpZ) elicits a rapid cell death response in tobacco plants. Multiple signaling components, including mitogen-activated protein kinase (MAPK), reactive oxygen species (ROS) and salicylic acid (SA), have been reported to be involved in this cell death process, but the interaction between these molecules is poorly understood. Here we show through utilizing plants manipulated in SIPK expression levels that lack of SIPK results in increased sensitivity to harpin with concomitant accumulation of higher levels of ROS. Conversely, SIPK-overexpressing plants show reduced sensitivity to harpin relative to wild-type plants, and display reduced ROS accumulation. Harpin-induced cell death was found to be conditional on the ability of the plant to accumulate SA, whereas harpin induction of MAPK activation and ROS accumulation are not. However, harpin-induced ROS accumulation is required for activation of SIPK and wound-induced protein kinase. Transcriptional profiling revealed that suppression of SIPK signaling also affects early expression of a range of pathogen- and stress-responsive genes during harpin challenge.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".