Characterization of Bacteria Associated with Pinewood Nematode Bursaphelenchus xylophilus
Bibliographic record
Abstract
Pine Wilt Disease (PWD) is a complex disease integrating three major agents: the pathogenic agent, the pinewood nematode Bursaphelenchus xylophilus; the insect-vector Monochamus spp.; and the host pine tree, Pinus sp. Since the early 80's, the notion that another pathogenic agent, namely bacteria, may play a role in PWD has been gaining traction, however the role of bacteria in PWD is still unknown. The present work supports the possibility that some B. xylophilus-associated bacteria may play a significant role in the development of this disease. This is inferred as a consequence of: (i) the phenotypic characterization of a collection of 35 isolates of B. xylophilus-associated bacteria, in different tests broadly used to test plant pathogenic and plant growth promoting bacteria, and (ii) greenhouse experiments that infer the pathogenicity of these bacteria in maritime pine, Pinus pinaster. The results illustrate the presence of a heterogeneous microbial community associated with B. xylophilus and the traits exhibited by at least, some of these bacteria, appear to be related to PWD symptoms. The inoculation of four specific B. xylophilus-associated bacteria isolates in P. pinaster seedlings resulted in the development of some PWD symptoms suggesting that these bacteria likely play an active role with B. xylophilus in PWD.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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 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".