Molecular Mechanisms of Nematode-Nematophagous Microbe Interactions: Basis for Biological Control of Plant-Parasitic Nematodes
Bibliographic record
Abstract
Plant-parasitic nematodes cause significant damage to a broad range of vegetables and agricultural crops throughout the world. As the natural enemies of nematodes, nematophagous microorganisms offer a promising approach to control the nematode pests. Some of these microorganisms produce traps to capture and kill the worms from the outside. Others act as internal parasites to produce toxins and virulence factors to kill the nematodes from within. Understanding the molecular basis of microbe-nematode interactions provides crucial insights for developing effective biological control agents against plant-parasitic nematodes. Here, we review recent advances in our understanding of the interactions between nematodes and nematophagous microorganisms, with a focus on the molecular mechanisms by which nematophagous microorganisms infect nematodes and on the nematode defense against pathogenic attacks. We conclude by discussing several key areas for future research and development, including potential approaches to apply our recent understandings to develop effective biocontrol strategies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".