Model plants for studying the interaction between <i>Methylobacterium mesophilicum</i> and <i>Xylella fastidiosa</i>
Bibliographic record
Abstract
Over the last few years, endophytic bacterial communities associated with citrus have been studied as key components interacting with Xylella fastidiosa. In this study, we investigated the possible interaction between the citrus endophyte Methylobacterium mesophilicum SR1.6/6 and X. fastidiosa in model plants such as Catharanthus roseus (Madagaskar periwinkle) and Nicotiana clevelandii (Clevelands tobacco). The aim of this study was to establish the fate of M. mesophilicum SR1.6/6 after inoculation of C. roseus and N. clevelandii plants, using PCR-DGGE (polymerase chain reaction--denaturing gradient gel electrophoresis) and plating techniques. Shifts in the indigenous endophytic bacterial communities were observed in plants inoculated with strain SR1.6/6, using specific primers targeting alpha- and beta-Proteobacteria. Cells of strain SR1.6/6 were observed in a biofilm structure on the root and hypocotyl surfaces of in vitro seedlings inoculated with M. mesophilicum SR1.6/6. This emphasizes the importance of these tissues as main points of entrance for this organism. The results showed that C. roseus and N. clevelandii could be used as model plants to study the interaction between M. mesophilicum and X. fastidiosa.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".