A Role for Diacylglycerol Acyltransferase during Leaf Senescence
Bibliographic record
Abstract
Lipid analysis of rosette leaves from Arabidopsis has revealed an accumulation of triacylglycerol (TAG) with advancing leaf senescence coincident with an increase in the abundance and size of plastoglobuli. The terminal step in the biosynthesis of TAG in Arabidopsis is catalyzed by diacylglycerol acyltransferase 1 (DGAT1; EC 2.3.1.20). When gel blots of RNA isolated from rosette leaves at various stages of development were probed with the Arabidopsis expressed sequence tag clone, E6B2T7, which has been annotated as DGAT1, a steep increase in DGAT1 transcript levels was evident in the senescing leaves coincident with the accumulation of TAG. The increase in DGAT1 transcript correlated temporally with enhanced levels of DGAT1 protein detected immunologically. Two lines of evidence indicated that the TAG of senescing leaves is synthesized in chloroplasts and sequesters fatty acids released from the catabolism of thylakoid galactolipids. First, TAG isolated from senescing leaves proved to be enriched in hexadecatrienoic acid (16:3) and linolenic acid (18:3), which are normally present in thylakoid galactolipids. Second, DGAT1 protein in senescing leaves was found to be associated with chloroplast membranes. These findings collectively indicate that diacylglycerol acyltransferase plays a role in senescence by sequestering fatty acids de-esterified from galactolipids into TAG. This would appear to be an intermediate step in the conversion of thylakoid fatty acids to phloem-mobile sucrose during leaf senescence.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".