The Impact of Tellurite on Highly Resistant Marine Bacteria and Strategies for Its Reduction
Bibliographic record
Abstract
Five marine bacteria (＂Pseudoalteromonas spiralis＂, Te-2-2; ＂Pseudoalteromonas telluritireducens＂, Se-1-2-red; ＂Erythrobacter litoralis＂, T4; ＂Citromicrobium bathyomarinum＂, JF1; and a ＂Shewanella frigidimarina relative＂, strain ER-Te-48), possessing both very high level aerobic resistance and the ability to reduce TeO_3^(2-) to elemental Te were investigated to better understand their interaction with this metalloid oxide. It was found that reduction can be greatly influenced by several factors including carbon source, pH and aeration. The physiological and metabolic response of cells to tellurite differs between strains. In its presence, versus absence, cellular biomass varied, yielding relatively similar or decreased amounts of protein. ATP production was affected in the same manner, with similar and decreased levels in cells harvested from media containing TeO_3^(2-). Three different strategies for tellurite reduction, which required de novo synthesis of a reductase, were observed. Strain ER-Te-48 employed a periplasmic reductase, while Te-2-2, T4 and JF1 required an intact cytoplasmic membrane for reduction. Lastly, Se-1-2-red was only able to reduce as an undisturbed whole cell culture.
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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".