Identification of differentially regulated proteins in response to a compatible interaction between the pathogen <b><i>Fusarium graminearum</i></b> and its host, <b><i>Triticum aestivum</i></b>
Bibliographic record
Abstract
Using proteomic analyses, a study was carried out aimed at understanding the molecular mechanism of interaction between Fusarium graminearum and Triticum aestivum. Wheat spikelets were inoculated with H2O and conidia spores of F. graminearum. Proteins were extracted from spikelets harvested at three time points: 1, 2 and 3 days post inoculation. About 1380 protein spots were displayed on 2-D gels stained with Sypro Ruby. In total, 41 proteins were detected to be differentially regulated due to F. graminearum infection, and were analyzed with LC-MS/MS for their identification. The proteins involved in the antioxidant and jasmonic acid signaling pathways, pathogenesis-related response, amino acid synthesis and nitrogen metabolism were up-regulated, while those related to photosynthesis were less abundant following F. graminearum infection. The DNA-damage inducible protein was found to be induced and glycosylated in F. graminearum-infected spikelets. Using TargetP program, seven of the identified wheat proteins were predicted to be located in the chloroplast, implying that the chloroplast is the organelle mostly affected by F. graminearum infection. Eight identified fungal proteins possess possible functions such as antioxidant and acquiring carbon from wheat through glycolysis in a compatible interaction between F. graminearum and wheat.
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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 | 0.001 |
| 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) | 0.001 | 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".