Formation of Tellurium Nanocrystals during Anaerobic Growth of Bacteria That Use Te Oxyanions as Respiratory Electron Acceptors
Bibliographic record
Abstract
Certain toxic elements support the metabolism of diverse prokaryotes by serving as respiratory electron acceptors for growth. Here, we demonstrate that two anaerobes previously shown to be capable of respiring oxyanions of selenium also achieve growth by reduction of either tellurate [Te(VI)] or tellurite [Te(IV)] to elemental tellurium [Te(0)]. This reduction achieves a sizeable stable-Te-isotopic fractionation (isotopic enrichment factor [epsilon] = -0.4 to -1.0 per ml per atomic mass unit) and results in the formation of unique crystalline Te(0) nanoarchitectures as end products. The Te(0) crystals occur internally within but mainly externally from the cells, and each microorganism forms a distinctly different structure. Those formed by Bacillus selenitireducens initially are nanorods ( approximately 10-nm diameter by 200-nm length), which cluster together, forming larger ( approximately 1,000-nm) rosettes composed of numerous individual shards ( approximately 100-nm width by 1,000-nm length). In contrast, Sulfurospirillum barnesii forms extremely small, irregularly shaped nanospheres (diameter < 50 nm) that coalesce into larger composite aggregates. Energy-dispersive X-ray spectroscopy and selected area electron diffraction indicate that both biominerals are composed entirely of Te and are crystalline, while Raman spectroscopy confirms that they are in the elemental state. These Te biominerals have specific spectral signatures (UV-visible light, Raman) that also provide clues to their internal structures. The use of microorganisms to generate Te nanomaterials may be an alternative for bench-scale syntheses. Additionally, they may also generate products with unique properties unattainable by conventional physical/chemical methods.
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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) | 0.000 | 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 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".