Mercury Analysis of Acid- and Alkaline-Reduced Biological Samples: Identification of <i>meta</i> -Cinnabar as the Major Biotransformed Compound in Algae
Bibliographic record
Abstract
The biotransformation of Hg(II) in pH-controlled and aerated algal cultures was investigated. Previous researchers have observed losses in Hg detection in vitro with the addition of cysteine under acid reduction conditions in the presence of SnCl2. They proposed that this was the effect of Hg-thiol complexing. The present study found that cysteine-Hg, protein and nonprotein thiol chelates, and nucleoside chelates of Hg were all fully detectable under acid reduction conditions without previous digestion. Furthermore, organic (R-Hg) mercury compounds could not be detected under either the acid or alkaline reduction conditions, and only beta-HgS was detected under alkaline and not under acid SnCl2 reduction conditions. The blue-green alga Limnothrix planctonica biotransformed the bulk of Hg(II) applied as HgCl2 into a form with the analytical properties of beta-HgS. Similar results were obtained for the eukaryotic alga Selenastrum minutum. No evidence for the synthesis of organomercurials such as CH3Hg+ was obtained from analysis of either airstream or biomass samples under the aerobic conditions of the study. An analytical procedure that involved both acid and alkaline reduction was developed. It provides the first selective method for the determination of beta-HgS in biological samples. Under aerobic conditions, Hg(II) is biotransformed mainly into beta-HgS (meta-cinnabar), and this occurs in both prokaryotic and eukaryotic algae. This has important implications with respect to identification of mercury species and cycling in aquatic habitats.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".