New insight into the roles of lipid transfer protein and seed storage albumin gene families involved in oil and protein accumulation in rapeseed (<i>Brassica napus</i> L.)
Bibliographic record
Abstract
In rapeseed ( Brassica napus L.), lipid transfer protein (LTP) and seed storage albumin (SSA) gene families are involved in lipid and protein metabolism. Understanding the mechanism of oil biosynthesis has great value to increase oil production. The LTPs and SSA gene families were identified of Brassicaceae. The LTPs were divided into six groups according to their sequences, and LTPs of all five species in Brassicaceae also had the same pattern. The genes at a higher expression level were evenly distributed across five groups except group ii. The gene groups in these two gene families showed different expression patterns, with most of the LTP genes expressed at a higher level at 25 days after flowering (DAF), but SSA genes were highly expressed at 40 DAF stage. Gene Ontology (GO) enrichment analysis of the regulatory genes for LTPs also was performed, including response to biotic stimulus (GO:0009607), generation of precursor metabolites and energy (GO:0006091), electron transport chain (GO:0022900), oxidative phosphorylation (GO:0006119), adenosine triphosphate metabolic process (GO:0046034), and phosphorylation (GO:0016310). These results may facilitate further research to understand the expression patterns and regulatory mechanism of LTPs and SSAs.
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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".