The <i>Arabidopsis</i> paraquat resistant1 mutant accumulates leucine upon dark treatment
Bibliographic record
Abstract
The Arabidopsis paraquat resistant1 (PAR1) was classified as L-type amino acid transporter 4 (LAT4) based on a phylogenetic analysis of selected genes from Saccharomyces cerevisiae, Arabidopsis thaliana (L.) Heynh, and Homo sapiens that clustered LAT4 with four other members as a LAT family in Arabidopsis. In silico analysis of the Arabidopsis LATs identified an amino acid permease domain and motifs that are common in amino acid transporters. However, their role in amino acid transport remained to be studied. A knockout mutant for PAR1/LAT4 gene, reported here as par1-5, showed significantly altered growth compared with wild type on leucine-containing growth medium. Mutant par1-5 seedlings showed reduced biomass compared with wild type on nitrate-containing Murashige and Skoog growth medium, which was further reduced when grown on medium containing nitrate and leucine. Radio-labelled leucine uptake studies using leaf protoplasts and seedlings showed increased accumulation of leucine in par1-5 mutants compared with wild type. Increased accumulation of leucine in par1-5 was detected when seedlings or protoplasts were treated in the dark prior to isotopic feeding. These studies suggest that the PAR1/LAT4 protein, in addition to its ability to mediate paraquat and polyamine transport, possess leucine transport activity that is regulated by physiological conditions such as dark induction.
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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) | 0.002 | 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".