A 10‐kDa acyl‐CoA‐binding protein (ACBP) from <i>Brassica napus</i> enhances acyl exchange between acyl‐CoA and phosphatidylcholine
Bibliographic record
Abstract
The gene encoding a 10-kDa acyl-CoA-binding protein (ACBP) from Brassica napus was over-expressed in developing seeds of Arabidopsis thaliana. Biochemical analysis of T(2) and T(3) A. thaliana seeds revealed a significant increase in polyunsaturated fatty acids (FAs) (18:2(cisDelta9,12) and 18:3(cisDelta9,12,15)) at the expense of very long monounsaturated FA (20:1(cisDelta11)) and saturated FAs. In vitro assays demonstrated that recombinant B. napus ACBP (rBnACBP) strongly increases the formation of phosphatidylcholine (PC) in the absence of added lysophosphatidylcholine in microsomes from DeltaYOR175c yeast expressing A. thaliana lysophosphatidylcholine acyltransferase (AthLPCAT) cDNA or in microsomes from microspore-derived cell suspension cultures of B. napus L. cv. Jet Neuf. rBnACBP or bovine serum albumin (BSA) were also shown to be crucial for AthLPCAT to catalyse the transfer of acyl group from PC into acyl-CoA in vitro. These data suggest that the cytosolic 10-kDa ACBP has an effect on the equilibrium between metabolically active acyl pools (acyl-CoA and phospholipid pools) involved in FA modifications and triacylglycerol bioassembly in plants. Over-expression of ACBP during seed development may represent a useful biotechnological approach for altering the FA composition of seed oil.
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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) | 0.001 | 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 | 0.001 |
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".