Enhanced In Vitro Plant Morphogenesis of Tobacco: Unveiling Indoleamine-Modulated Adaptogenic Properties of Tulsi (Ocimum sanctum L.)
Bibliographic record
Abstract
L.) is acknowledged for its invigorating and healing properties that enhance resilience to stress in various human and animal models by modulating antioxidant compounds. While extensive research has documented these effects in humans, the adaptogenic potential of tulsi in stressful in vitro plant systems has not been explored. This study aimed to elucidate the adaptogenic properties of tulsi leaf extract on the in vitro regeneration of tobacco leaf explants through an investigation of the indoleamines at different developmental stages. Shoot regeneration from leaf explants on the medium supplemented with tulsi extract (20%) was compared to the control, and the differences in indoleamine compounds were analyzed using ultra-performance liquid chromatography. Treatment of the explants with the extract resulted in an almost two-fold increase in the number of regenerants after four weeks of culture, and 9% of the regenerants resembled somatic embryo-like structures. The occurrence of browning in the extract-treated explants stopped on day 10, shoots began to develop, and a significant concentration of tryptamine and N-acetyl-serotonin accumulated. A comparative analysis of indoleamine compounds in intact and cut tobacco leaves also revealed the pivotal role of melatonin and 2-hydroxymelatonin functioning as antioxidants during stress adaptation. This study demonstrates that tulsi is a potent adaptogen that is capable of modulating plant morphogenesis in vitro, paving the way for further investigations into the role of adaptogens in plant stress biology.
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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) | 0.000 | 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 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".