JoVE Video Dataset
Bibliographic record
Abstract
Testing the function of therapeutic compounds in plants is an important component of agricultural research. Foliar and soil-drench methods are routine but have drawbacks, including variable uptake and the environmental breakdown of tested molecules. Trunk injection of trees is well-established, but most methods for this require expensive, proprietary equipment. To screen various treatments for Huanglongbing, a simple, low-cost method to deliver these compounds to the vascular tissue of small greenhouse-grown citrus trees infected with the phloem-limited bacterium Candidatus Liberibacter asiaticus (CLas) or infested with the phloem-feeding CLas insect vector Diaphorina citri Kuwayama (D. citri) is needed. To meet these screening requirements, a direct plant infusion (DPI) device was designed that connects to the plant's trunk. The device is made using a nylon-based 3D-printing system and easily obtainable auxiliary components. The compound uptake efficacy of this device was tested in citrus plants using the fluorescent marker 5,6-carboxyfluorescein-diacetate. Uniform compound distribution of the marker throughout the plants was routinely observed. Furthermore, this device was used to deliver antimicrobial and insecticidal molecules to determine their effects on CLas and D. citri respectively. The aminoglycoside antibiotic streptomycin was delivered into CLas-infected citrus plants using the device, which resulted in a reduction in the CLas titer from 2 weeks to 4 weeks post treatment. Delivering the neonicotinoid insecticide imidacloprid into D. citri-infested citrus plants resulted in a significant increase in psyllid mortality after 7 days. These results suggest that this DPI device represents a useful system for delivering molecules into plants for testing and facilitate research and screening purposes.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.708 | 0.493 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".