Stable indoleamines attenuate stress<b>—</b>A novel paradigm in tryptophan metabolism in plants
Bibliographic record
Abstract
Abstract Stability of metabolites in harsh environments such as drought, temperature, and light suggest their untapped potential in processes the plants utilize in mitigation of abiotic and biotic stresses. Such metabolites could be nonspecific to microorganisms, plants, or animals. Many of the indoleamines are ubiquitous throughout species and have been shown to mitigate a wide range of stresses. We tested the role of indoleamine metabolites via exogenous application of the precursor tryptophan (TRP) on strawberry due to the short reproductive life cycle and its temperate traits. Seasonal responses appeared to be perturbed with exogenous application of TRP as a combination of foliar (3 mg/L) and ground drench (100 mg/L) or ground drench only (100 mg/L). The treatment yielded growth stimulatory responses besides mitigating stress, that is, short photoperiod and cold temperature. Plants preparing into dormancy reverted to produce green foliage and flowers that set fruit in unfavorable climate in the month of November where the untreated plants senesced. Analyses of the endogenous indoleamines in flowers and fruits of the treated plants indicated that the titers and ratios of the metabolites NAS, 2‐hydroxymelatonin, and N(1)‐acetyl‐N(2)‐formyl‐5‐methoxykynuramine assisted in the stress mitigation. The ASMT and M2H gene regulations emphasized the stability of intermediate metabolites of TRP. The TDC and T5H regulation explained the detection of a rare to find compound, 5‐hydroxytryptophan, in strawberry. This is the first report on detection of eight indoleamines in strawberry alongside the regulatory genes in the indoleamine pathway. Inclining climate crisis demands climate‐resilient plants in quick time and the indoleamine toolkit may offer the opportunity to develop simple and effective practices to manage stress tolerance in plants.
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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 | 0.000 |
| 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".