Proteomic analyses of <b><i>Fusarium graminearum</i></b> grown under mycotoxin‐inducing conditions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Non-gel-based quantitative proteomics technology was used to profile protein expression differences when Fusarium graminearum was induced to produce trichothecenes in vitro. As F. graminearum synthesizes and secretes trichothecenes early in the cereal host invasion process, we hypothesized that proteins contributing to infection would also be induced under conditions favouring mycotoxin synthesis. Protein samples were extracted from three biological replicates of a time course study and subjected to iTRAQ (isobaric tags for relative and absolute quantification) analysis. Statistical analysis of a filtered dataset of 435 proteins revealed 130 F. graminearum proteins that exhibited significant changes in expression, of which 72 were upregulated relative to their level at the initial phase of the time course. There was good agreement between upregulated proteins identified by 2-D PAGE/MS/MS and iTRAQ. RT-PCR and northern hybridization confirmed that genes encoding proteins which were upregulated based on iTRAQ were also transcriptionally active under mycotoxin producing conditions. Numerous candidate pathogenicity proteins were identified using this technique. These will provide leads in the search for mechanisms and markers of host invasion and novel antifungal targets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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 it