Development of a rapid screen to identify formulations that enhance plant resistance to viral infection
Why this work is in the frame
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Bibliographic record
Abstract
A screening method was developed to identify formulations that enhance plant resistance to viral infection. A modified Tobacco rattle virus (TRV) genome with green fluorescent protein (TRV-GFP) was delivered into Nicotiana benthamiana cells using Agrobacterium tumefaciens . Subjective scales based on TRV-GFP fluorescence in inoculated and systemic leaves were created and validated by examining TRV coat protein expression using RT-PCR. This rapid 7-day Agrobacterium -TRV-GFP/ N. benthamiana screen was used to test many formulations containing sodium magnesium chlorophyllin (Mg-chl) with various surfactants. Treatment with Mg-chl formulation 1 and 2 resulted in significant reductions in TRV-GFP levels in N. benthamiana inoculated and systemic leaves compared to mock-treated plants, without causing phytotoxic effects. Given that Mg-chl is activated by light to produce reactive oxygen species (ROS), H 2 O 2 levels were examined and shown to increase in Mg-chl-treated leaves. Elevated H 2 O 2 levels may have initiated Salicylic acid (SA)- and Jasmonic acid (JA)-mediated resistance pathways as supported by expression of N.benthamiana Pathogenesis-Related1 ( NbPR1 ) and N.benthamiana Myelocytomatosis transcription factor ( NbMYC2) in formulation-treated leaves. Treatment with formulations 1 and 2 also provided resistance in Nicotiana tabacum leaves to Tobacco mosaic virus (TMV). Given that the JA pathway gene NbMYC2 was expressed in response to Mg-chl treatment, resistance to necrotrophic pathogens or insects may also be enhanced. Treatment with Mg-chl formulation 1 and 2 conferred resistance to TRV-GFP in N. benthamiana and TMV in N. tabacum without causing phytotoxic effects, indicating these formulations are ideal candidates for commercialization as plant immunity stimulators.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it