Biosynthesis and multifaceted roles of reactive species in plant defense mechanisms during environmental cues
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
• Elucidates ROS and RNS biosynthesis and their spatiotemporal signaling dynamics. • Reveals ROS-RNS crosstalk modulating plant immunity and abiotic stress adaptation. • Highlights advanced imaging for in vivo visualization of reactive species in plants. • Identifies gaps in molecular specificity of ROS/RNS signaling and gene regulation. • Integrates ROS/RNS roles with hormonal and epigenetic networks in stress resilience. Reactive oxygen species (ROS) and reactive nitrogen species (RNS) are key components of plant metabolism, acting as cellular damage agents and essential signalling molecules. They play crucial roles in plant growth, development, and responses to environmental cues. This review clarifies their distinct and overlapping functions within plant signalling pathways. ROS and RNS are produced in organelles such as chloroplasts, mitochondria, and peroxisomes, where their concentrations are tightly regulated to balance signalling functions and prevent cellular damage. We explore their signalling roles, mechanisms underlying signal transduction, interactions across plant systems, and influence on plant stress responses. Evidence shows that ROS and RNS regulate adaptation to drought, salinity, pathogens, and herbivores. Advanced imaging techniques have enhanced our understanding of their cellular dynamics in redox signalling pathways, highlighting the need to balance their production and scavenging for optimal plant health. Understanding their biosynthesis, signalling, and interactions is crucial for unravelling their contributions to plant growth and resilience.
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.
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 | 0.000 | 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 | 0.000 |
| 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 it