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 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 | 0.000 |
| 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".