Dissolved Organic Matter Kinetically Controls Mercury Bioavailability to Bacteria
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Predicting the bioavailability of inorganic mercury (Hg) to bacteria that produce the potent bioaccumulative neurotoxin monomethylmercury remains one of the greatest challenges in predicting the environmental fate and transport of Hg. Dissolved organic matter (DOM) affects mercury methylation due to its influence on cell physiology (as a potential nutrient) and its influence on Hg(II) speciation in solution (as a complexing agent), therefore controlling Hg bioavailability. We assessed the role of DOM on Hg(II) bioavailability to a gram-negative bacterium bioreporter under oxic pseudo- and nonequilibrium conditions, using defined media and field samples spanning a wide range of DOM levels. Our results showed that Hg(II) was considerably more bioavailable under nonequilibrium conditions than when DOM was absent or when Hg(II) and DOM had reached pseudoequilibrium (24 h) prior to cell exposure. Under these enhanced uptake conditions, Hg(II) bioavailability followed a bell shaped curve as DOM concentrations increased, both for defined media and natural water samples, consistent with bioaccumulation results in a companion paper (this issue) observed for amphipods. Experiments also suggest that DOM may not only provide shuttle molecules facilitating Hg uptake, but also alter cell wall properties to facilitate the first steps toward Hg(II) internalization. We propose the existence of a short-lived yet critical time window (<24 h) during which DOM facilitates the entry of newly deposited Hg(II) into aquatic food webs, suggesting that the bulk of mercury incorporation in aquatic food webs would occur within hours following its deposition from the atmosphere.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.027 | 0.020 |
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 it