Strategies and tools for studying the metabolism and function of γ-aminobutyrate in plants. I. Pathway structure
Bibliographic record
Abstract
γ-Aminobutyrate (GABA) is a ubiquitous four-C, nonprotein, amino acid that has been linked to stress, signaling, and storage in plants. In this paper, we discuss analytical, enzyme-linked, and colorimetric methods for analyzing GABA and related metabolites, and review tracer evidence for the derivation of GABA from glutamate and its subsequent catabolism to succinic semialdehyde and either succinate or γ-hydroxybutyrate. Also, we describe biochemical, complementation, bioinformatic, recombinant, and modelling strategies for identifying genes and investigating properties of the encoded proteins responsible for transport and metabolism of GABA. For Arabidopsis, evidence supports the involvement of a plasma membrane GABA transporter, a mitochondrial GABA permease, a cytosolic Ca 2+ /calmodulin- and pH-regulated cytosolic glutamate decarboxylase, a pyruvate- and glyoxylate-regulated mitochondrial GABA transaminase, a redox-regulated mitochondrial succinic semialdehyde dehydrogenase, and redox-regulated glyoxylate/succinic semialdehyde reductases located in both cytosol and plastid, respectively. This simple biochemical model does not account for species and tissue differences in the isoform complement of GABA pathway enzymes or transcriptional control of the pathway. In a companion review, we provide a more integrated view of GABA metabolism and function.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".