Analysis of sulfur and selenium assimilation in <i>Astragalus</i> plants with varying capacities to accumulate selenium
Why this work is in the frame
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Bibliographic record
Abstract
Several Astragalus species have the ability to hyperaccumulate selenium (Se) when growing in their native habitat. Given that the biochemical properties of Se parallel those of sulfur (S), we examined the activity of key S assimilatory enzymes ATP sulfurylase (ATPS), APS reductase (APR), and serine acetyltransferase (SAT), as well as selenocysteine methyltransferase (SMT), in eight Astragalus species with varying abilities to accumulate Se. Se hyperaccumulation was found to positively correlate with shoot accumulation of S-methylcysteine (MeCys) and Se-methylselenocysteine (MeSeCys), in addition to the level of SMT enzymatic activity. However, no correlation was observed between Se hyperaccumulation and ATPS, APR, and SAT activities in shoot tissue. Transgenic Arabidopsis thaliana overexpressing both ATPS and APR had a significant enhancement of selenate reduction as a proportion of total Se, whereas SAT overexpression resulted in only a slight increase in selenate reduction to organic forms. In general, total Se accumulation in shoots was lower in the transgenic plants overexpressing ATPS, PaAPR, and SAT. Root growth was adversely affected by selenate treatment in both ATPS and SAT overexpressors and less so in the PaAPR transgenic plants. Such observations support our conclusions that ATPS and APR are major contributors of selenate reduction in planta. However, Se hyperaccumulation in Astragalus is not driven by an overall increase in the capacity of these enzymes, but rather by either an increased Se flux through the S assimilatory pathway, generated by the biosynthesis of the sink metabolites MeCys or MeSeCys, or through an as yet unidentified Se assimilation pathway.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it