Role of<i>Leptothrix discophora</i>in Mediating Metal Uptake in the Filter-Feeding Bivalve<i>Mytilus trossulus (edulis)</i>
Bibliographic record
Abstract
The potential for filter-feeding bivalves to accumulate metals from a wide range of food sources is an important consideration when examining trophic transfer of metals up the food chain. The objective of this study was to determine the role of Leptothrix discophora in mediating metal uptake in the filter-feeding bivalve Mytilus trossulus. The bacterium L. discophora SP-6 was cultured in the absence or presence of Mn, allowing for a naturally formed Mn oxide sheath to develop. Secondary metals (Cd and Pb) were then added to the cultures, allowing for potential Cd and Pb adsorption to the Mn oxide sheath. Resulting bacterial aggregates of known diameter were then fed to the bivalve M. trossulus using a flow-through system. Initial concentrations of both Pb and Cd on the bacterium did not differ significantly in the presence or absence of the Mn oxide; conversely both Pb (F = 7.39, p < 0.0001) and Cd (F= 33.65, p < 0.0001) were found at lower concentrations in the mussel tissue when the Mn oxide was present. To determine whether these differences in metal uptake could be attributed to sorting by the mussel based on food quality, nutritional analysis was performed. Bacterial food matrixes containing Mn oxides were found to have significantly lower levels of carbon (F = 256, p < 0.0001). Particle clearance rates for the various food matrixes were positively correlated with organic content (R2 = 0.852, p > 0.008). The results of our study suggest that metal uptake in M. trossulus was significantly decreased for Cd with a similar trend for Pb when the SP-6 sheath contained Mn oxides. The mechanism mediating this differential uptake is best explained by food quality, in that a higher quality food source enhanced metal uptake due to an increased clearance rate of organic-rich particles by M. trossulus.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".