Applying high throughput techniques in the study of adenosine kinase in plant metabolism and development
Bibliographic record
Abstract
Adenosine kinase (ADK, EC 2.7.1.20) is a purine salvage enzyme, which phosphorylates adenosine (Ado) to AMP. It may also contribute to the interconversion of cytokinin ribosides and nucleotides. Recent microarray analyses have provided new insights into the impact of ADK activity towards plant metabolism and development. The majority of these findings reflect ADK's role in the metabolism of Ado produced from transmethylation reactions in addition to providing necessary nucleotides for the synthesis of nucleic acids and nucleotide cofactors. As such, ADK was found to increase during events associated with high transmethylation activity, such as cell wall synthesis and seed filling. Differences between plant organs were also detected, with ADK transcript levels found highest in siliques and roots and lowest in callus, leaves and buds. Transcript profiling of Arabidopsis expression using microarrays, reveals a predominance of ADK1 expression relative to that of ADK2. In the majority of the studies, the isoforms appeared to behave in a similar pattern of expression, with the exception being microgametogenesis where ADK1 was up-regulated when ADK2 was not. What specialized function the ADK1 could be providing to these cells during development and whether or not this is occurring in other biochemical processes has yet to be determined.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.007 |
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".