Localizing the Chemical Forms of Sulfur in Vivo Using X-ray Fluorescence Spectroscopic Imaging: Application to Onion (<i>Allium cepa</i>) Tissues
Bibliographic record
Abstract
Sulfur has a particularly rich biochemistry and fills a number of important roles in biology. In situ information on sulfur biochemistry is generally difficult to obtain because of a lack of biophysical techniques that have sufficient sensitivity to molecular form. We have recently reported that sulfur K-edge X-ray absorption spectroscopy can be used as a direct probe of the sulfur biochemistry of living mammalian cells [Gnida, M., et al. (2007) Biochemistry 46, 14735-14741]. Here we report an extension of this work and develop sulfur K-edge X-ray fluorescence spectroscopic imaging as an in vivo probe of sulfur metabolism in living cells. For this work, we have chosen onion (Allium cepa) as a tractable model system with well-developed sulfur biochemistry and present evidence of the localization of a number of different chemical forms. X-ray absorption spectroscopy of onion sections showed increased levels of lachrymatory factor (LF) and thiosulfinate and decreased levels of sulfoxide (LF precursor) following cell breakage. In intact cells, X-ray fluorescence spectroscopic imaging showed elevated levels of sulfoxides in the cytosol and elevated levels of reduced sulfur in the central transport vessels and bundle sheath cells.
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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 | 0.001 | 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".