Melatonin enhances the recovery of cryopreserved shoot tips of <scp>A</scp>merican elm (<i><scp>U</scp>lmus americana </i><scp>L</scp>.)
Bibliographic record
Abstract
Climate change and global migrations of people and goods have exposed trees to new diseases and abiotic challenges that threaten the survival of species. In vitro germplasm storage via cryopreservation is an effective tool to ensure conservation of tree species, but plant cells and tissues are exposed to multiple stresses during the cryopreservation process. The current study was designed to evaluate the potential of melatonin to improve survival through the process of cryopreservation. Shoot tips of in vitro-grown plantlets and dormant winter buds of American elm were successfully cryopreserved in liquid nitrogen (LN) at -196°C under controlled environmental conditions following melatonin treatment and cold acclimation with either vitrification or encapsulation–vitrification protocols. Explants had optimal regrowth following cryopreservation when treated with the plant vitrification solution#2 (PVS2) for 10 min. Supplementation of both preculture and regrowth media with melatonin significantly enhanced regrowth of frozen shoots compared with the untreated control (P < 0.05). Approximately 80–100% of shoot explants grew under optimized conditions using melatonin-enriched media. Shoot tips of dormant winter buds consistently produced nearly 100% regrowth with both techniques. The main steps of the optimized protocol are14-day cold-acclimated cultures exposed to preculture medium with 0.1–0.5 lM melatonin for 24 hr, application of PVS2 for 10 min, rapid cooling in LN, rapid rewarming, removal of cryoprotectants, and recovery on a medium supplemented with 0.1–0.5 lM melatonin. Our results demonstrate the usefulness of the antioxidant melatonin for long-term storage of naturally resistant elm germplasm.
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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".