ArticleFrontiers in plant science2020
Summary of Discussions From the 2019 OECD Conference on RNAi Based Pesticides.
Article in Frontiers in plant science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
10 citing papers in PubMed, 39 citations in OpenAlex.
- Nanoparticle-enhanced multi-target RNAi in Myzus persicae: Molecular mechanisms, cross-kingdom sRNA transfer, and efficacy for sustainable pest management.Pest management science · 2026Article
- RNAi: the next wave of green agriculture, challenges, and bridging the translational gap.Plant cell reports · 2026Review
- Exploring the potential of RNA interference (RNAi) in mosquito control: from mechanisms to molecular insights.In vitro cellular & developmental biology. Animal · 2026Review
- Challenges and Opportunities Arising from Host-International journal of molecular sciences · 2024Review
- A Combinatorial Nanobased Spray-Induced Gene Silencing Technique for Crop Protection and Improvement.ACS omega · 2023Review
- Characterization of Ionotropic Receptor GenePlants (Basel, Switzerland) · 2023Article
- A novel sustainable platform for scaled manufacturing of double-stranded RNA biopesticides.Bioresources and bioprocessing · 2022Article
- Comparison of Antifungal Activity ofPlants (Basel, Switzerland) · 2022Article
- CRISPR/Cas- and Topical RNAi-Based Technologies for Crop Management and Improvement: Reviewing the Risk Assessment and Challenges Towards a More Sustainable Agriculture.Frontiers in bioengineering and biotechnology · 2022Review
- Advances in the Development of Microbial Double-Stranded RNA Production Systems for Application of RNA Interference in Agricultural Pest Control.Frontiers in bioengineering and biotechnology · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 9 institutions in 7 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
RNA interference (RNAi) is a biological process in which double-stranded ribonucleic acid (dsRNA) molecules inhibit protein expression. In recent years, the application of dsRNA has been used in the development of agricultural products for pest control. The 2019 Organisation for Economic Cooperation and Development (OECD) Conference on RNAi Based Pesticides ("the Conference") brought together academic, industry, and government experts in various aspects of RNAi to discuss the current state of knowledge and topics to help in developing considerations for risk assessment. The Conference focused on environment, with some discussion of human health. Along with presentations on the use of dsRNA-based products in agriculture, government regulation, risk assessment, and a background on the Draft OECD Working Paper on "Considerations for the Environmental Risk Assessment of the Application of Sprayed or Externally Applied dsRNA-Based Pesticides" ("OECD Working Paper"), the Conference included panel discussions from presenters at the end of each session and a larger discussion session with Conference participants on the environmental fate of dsRNA, non-target organism (NTO) risk assessment, and human health risk assessment. This paper summarizes input from presenters and Conference participants during these discussions. Key considerations from these discussions have already been incorporated into the OECD Working Paper, that once finalized and published, will facilitate regulators in evaluating externally applied dsRNA-based products for potential environmental risks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.