Biotransformation of Hg(II) by Cyanobacteria
Bibliographic record
Abstract
The biotransformation of Hg(II) by cyanobacteria was investigated under aerobic and pH-controlled culture conditions. Mercury was supplied as HgCl(2) in amounts emulating those found under heavily impacted environmental conditions where bioremediation would be appropriate. The analytical procedures used to measure mercury within the culture solution, including that in the cyanobacterial cells, used reduction under both acid and alkaline conditions in the presence of SnCl(2). Acid reduction detected free Hg(II) ions and its complexes, whereas alkaline reduction revealed that meta-cinnabar (beta-HgS) constituted the major biotransformed and cellularly associated mercury pool. This was true for all investigated species of cyanobacteria: Limnothrix planctonica (Lemm.), Synechococcus leopoldiensis (Racib.) Komarek, and Phormidium limnetica (Lemm.). From the outset of mercury exposure, there was rapid synthesis of beta-HgS and Hg(0); however, the production rate for the latter decreased quickly. Inhibitory studies using dimethylfumarate and iodoacetamide to modify intra- and extracellular thiols, respectively, revealed that the former thiol pool was required for the conversion of Hg(II) into beta-HgS. In addition, increasing the temperature enhanced the amount of beta-HgS produced, with a concomitant decrease in Hg(0) volatilization. These findings suggest that in the environment, cyanobacteria at the air-water interface could act to convert substantial amounts of Hg(II) into beta-HgS. Furthermore, the efficiency of conversion into beta-HgS by cyanobacteria may lead to the development of applications in the bioremediation of mercury.
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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".