Transient expression of the <i>β-glucuronidase</i> gene in <i>Cannabis sativa</i> varieties
Bibliographic record
Abstract
In plant biology, transient expression analysis plays a vital role to provide a fast method to study the gene of interest. In this study, we report a rapid and efficient method for transient expression in Cannabis sativa seedlings using Agrobacterium tumefaciens-mediated transformation. A. tumefaciens strain EHA105 carrying the pCAMBIA1301 construct with uidA gene was used to transform cannabis seedlings and the GUS assay (a measurement of β-glucuronidase activity) was used to detect the uidA expression. In the current study, we have also established a rapid germination protocol for cannabis seeds. The all three steps seed sterilization, germination and seedlings development were carried out in a 1% H2O2 solution. Transient transformation revealed that both cotyledons and young true leaves are amenable to transformation. Compared with tobacco (Nicotiana benthamiana), cannabis seedlings were less susceptible to transformation with A. tumefaciens. Susceptibility to Agrobacterium transformation also varied with the different cannabis varieties. The method established in this study has the potential to be an important tool for gene function studies and genetic improvement in cannabis.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".