CO<sub>2</sub> laser enhances the chilling tolerance of wheat seedlings by stimulating NO synthesis
Bibliographic record
Abstract
To investigate the mechanism by which laser irradiation enhances the chilling tolerance of wheat seedlings, seeds were exposed to different treatments, and biochemical parameters were measured. Compared with the control group, chilling stress (CS) led to an increase in the concentrations of malondialdehyde (MDA) and H2O2, and decreases in the activities of superoxide dismutase (SOD), ascorbate peroxidase (APX), glutathione reductase (GR), catalase (CAT), peroxidase (POD), and nitric oxide synthase (NOS), and the concentrations of nitric oxide (NO) and protein. Treatment with 2-(4-carboxyphenyl)-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide (PTIO), sodium tungstate (ST), and NG-nitro-L-arginine methyl ester (L-NAME) followed by CS resulted in further increases in the concentrations of MDA and H2O2 and further decreases in the other parameters. However, treatment with PTIO, ST, and L-NAME followed by laser irradiation had the opposite effects on these parameters. When the seeds were treated with PTIO, ST, and L-NAME followed by laser and CS, the concentrations of MDA and H2O2 were significantly lower and the other parameters were higher than in the PTIO, ST, and L-NAME plus CS groups. These results suggest that CO2 laser irradiation enhances the chilling tolerance of wheat seedlings by stimulating endogenous NO synthesis.
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.
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".