Gene expression associated with N‐induced shifts in resource allocation in poplar
Bibliographic record
Abstract
ABSTRACT Surprisingly little is known about molecular mechanisms by which nitrogen (N) availability acts to modulate the growth of forest trees. To address this issue, differential display was used in conjunction with filter‐based arrays to identify 52 partial cDNA clones that were significantly regulated within days in response to limiting or luxuriant levels of NH4NO3 fertilization in Populus trichocarpa Torr. & Gray × deltoides Bartr. ex Marsh. A subset of these cDNAs also demonstrated shifts in expression patterns in stem‐girdled trees, a manipulative physiology technique that disrupts phloem transport. Stem girdling also induced changes in glutamine and asparagine pools which were correlated with the observed changes in expression profiles for these genes. The identity of these genes provides insight into biochemical processes that are altered by N availability in poplar. Carbon–nitrogen interactions appear to figure prominently in the N‐response. The gene expression data suggest that N availability modulates the partitioning of C and N resources into metabolic fates that have the potential to alter both wood quality and quantity, including synthesis of vegetative storage proteins, cell wall components, and terpenoids.
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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".