Identification of novel α-gliadin genes
Bibliographic record
Abstract
Ten novel α-gliadin genes (Gli-ta, Gli-turg1, Gli-turg2, Gli-turg3, Gli-turg4, Gli-turg5, Gli-turg6, Gli-cs1, Gli-cs2, and Gli-cs3) with unique characteristics were isolated from wheat (Triticum aestivumL.), among which Gli-cs1, Gli-cs2, Gli-cs3, and Gli-turg6 were pseudogenes. Gli-cs3 and nine other sequences were much larger and smaller, respectively, than the typical α-gliadins. This variation was caused by insertion or deletion of the unique domain I and a polyglutamine region, possibly the result of illegitimate recombination. Consequently, Gli-cs3 contained 10 cysteine residues, whereas there were 2 cysteine residues only in the other nine sequences. Gli-ta/Gli-ta-like α-gliadin genes are normally expressed during the development of seeds. SDS-PAGE analysis showed that in-vitro-expressed Gli-ta could form intermolecular disulphide bonds and could be chain extenders. A protein band similar in size to Gli-ta has been observed in seed extracts, and mass spectrometry results confirm that the band contains small molecular mass α-gliadins, which is a characteristic of the novel α-gliadins. Mass spectrometry results also indicated that the two cysteine residues of Gli-ta/Gli-ta-like proteins participated in the formation of intermolecular disulphide bonds in vivo.
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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 | 0.000 |
| 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".