Glyphosate resistance in <i>Ambrosia trifida:</i> Part 2. Rapid response physiology and non‐target‐site resistance
Bibliographic record
Abstract
BACKGROUND: The glyphosate-resistant rapid response (GR RR) resistance mechanism in Ambrosia trifida is not due to target-site resistance (TSR) mechanisms. This study explores the physiology of the rapid response and the possibility of reduced translocation and vacuolar sequestration as non-target-site resistance (NTSR) mechanisms. RESULTS: GR RR leaf discs accumulated hydrogen peroxide within minutes of glyphosate exposure, but only in mature leaf tissue. The rapid response required energy either as light or exogenous sucrose. The combination of phenylalanine and tyrosine inhibited the rapid response in a dose-dependent manner. Reduced glyphosate translocation was observed in GR RR, but only when associated with tissue death caused by the rapid response. Nuclear magnetic resonance studies indicated that glyphosate enters the cytoplasm and reaches chloroplasts, and it is not moved into the vacuole of GR RR, GR non-rapid response or glyphosate-susceptible A. trifida. CONCLUSION: The GR RR mechanism of resistance is not associated with vacuole sequestration of glyphosate, and the observed reduced translocation is likely a consequence of rapid tissue death. Rapid cell death was inhibited by exogenous application of aromatic amino acids phenylalanine and tyrosine. The mechanism by which these amino acids inhibit rapid cell death in the GR RR phenotype remains unknown, and it could involve glyphosate phytotoxicity or other agents generating reactive oxygen species. Implications of these findings are discussed. The GR RR mechanism is distinct from the currently described glyphosate TSR or NTSR mechanisms in other species. © 2017 Society of Chemical Industry.
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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) | 0.001 | 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) | 0.001 | 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".