The Effect of Tellurite on Highly Resistant Freshwater Aerobic Anoxygenic Phototrophs and Their Strategies for Reduction
Bibliographic record
Abstract
Six fresh water aerobic anoxygenic phototrophs (Erythromicrobium ezovicum, strain E1; Erythromicrobium hydrolyticum, E4(1); Erythromicrobium ramosum, E5; Erythromonas ursincola, KR99; Sandaracinobacter sibiricus, RB 16-17; and Roseococcus thiosulfatophilus, RB3) possessing high level resistance to TeO₃(2-) and the ability to reduce it to elemental Te were studied to understand their interaction with this highly toxic oxyanion. Tested organic carbon sources, pH, and level of aeration all had an impact on reduction. Physiological and metabolic responses of cells to tellurite varied among strains. In its presence, versus absence, cellular biomass either increased (KR99, 66.6% and E5, 21.2%) or decreased (RB3, 66.1%, E1, 57.8%, RB 16-17, 41.5%, and E4(1), 21.3%). The increase suggests a possible benefit from tellurite. Cellular ATP production was similarly affected, resulting in an increase (KR99, 15.2% and E5, 38.9%) or decrease (E4(1), 31.9%; RB 16-17, 48.8%; RB3, 55.9%; E1, 35.9%). Two distinct strategies to tellurite reduction were identified. The first, found in E4(1), requires de novo protein preparations as well as an undisturbed whole cell. The second strategy, in which reduction depended on a membrane associated constitutive reductase, was used by the remaining strains.
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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) | 0.000 | 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) | 0.001 | 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".