In Vivo <sup>31</sup> P Nuclear Magnetic Resonance Investigation of Tellurite Toxicity in <i>Escherichia coli</i>
Bibliographic record
Abstract
Here we compare the physiological state of Escherichia coli exposed to tellurite or selenite by using the noninvasive technique of phosphorus-31 nuclear magnetic resonance (NMR) spectroscopy. We studied glucose-fed Escherichia coli HB101 cells containing either a normal pUC8 plasmid with no tellurite resistance determinants present or the pTWT100 plasmid which contains the resistance determinants tehAB. No differences could be observed in intracellular ATP levels, the presence or absence of a transmembrane pH gradient, or the levels of phosphorylated glycolytic intermediates when resistant cells were studied by 31P NMR in the presence or absence of tellurite. In the sensitive strain, we observed that the transmembrane pH gradient was dissipated and intracellular ATP levels were rapidly depleted upon exposure to tellurite. Only the level of phosphorylated glycolytic intermediates remained the same as observed with resistant cells. Upon exposure to selenite, no differences could be observed by 31P NMR between resistant and sensitive strains, suggesting that the routes for selenite and tellurite reduction within the cells differ significantly, since only tellurite is able to collapse the transmembrane pH gradient and lower ATP levels in sensitive cells. The presence of the resistance determinant tehAB, by an as yet unidentified detoxification event, protects the cells from uncoupling by tellurite.
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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".