Sulfite oxidation by iron-grown cells of<i>Thiobacillus ferrooxidans</i>at pH 3 possibly involves free radicals, iron, and cytochrome oxidase
Bibliographic record
Abstract
Thiobacillus ferrooxidans cells grown on ferrous iron oxidized sulfite to sulfate at pH 3, possibly by a free radical mechanism involving iron and cytochrome oxidase. A purely chemical system with low concentrations of Fe3+ simulated the T. ferrooxidans system. Metal chelators, ethylenediamine tetraacetic acid (EDTA), 4,5-dihydroxy-1-3-benzene disulfonic acid (Tiron), o-phenanthroline, and 2,2'-dipyridyl, inhibited both sulfite oxidation systems, but the T. ferrooxidans system was inhibited only after the initial brief oxygen consumption. EDTA and Tiron, strong chelators of Fe3+, inhibited the oxidation at lower concentrations than o-phenanthroline and 2,2'-dipyridyl, strong chelators of Fe2+. Inhibition of Fe3+-catalyzed sulfite oxidation by EDTA and Tiron was instant, but the inhibition by o-phenanthroline and dipyridyl was briefly delayed, presumably for the reduction of Fe3+ to Fe2+. Mannitol, a free radical scavenger, inhibited both systems to the same extent. Cyanide and azide inhibited only the T. ferrooxidans system, suggesting a role of cytochrome oxidase. It is proposed that sulfite is oxidized by a free radical mechanism initiated by Fe3+ on the cell surface of T. ferrooxidans. Cytochrome oxidase is possibly involved in the regeneration of Fe3+ from Fe2+ by the normal Fe2+-oxidizing system of T. ferrooxidans.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".