Uptake and depuration of cadmium, nickel, and lead in laboratory-exposed <i>Tubifex tubifex</i> and corresponding changes in the concentration of a metallothionein-like protein
Bibliographic record
Abstract
Based on weight loss in water, 24 h is recommended for Tubifex tubifex gut clearance. Biota-to-sediment accumulation factors (BSAFs) in gut-cleared T. tubifex following six weeks of exposure to Cd-, Ni-, and Pb-spiked sediment were 12.4, 3.0, and 19.0, respectively. Tissue Ni concentrations peaked after 12 h, whereas Cd and Pb were accumulated for the duration of the exposure. Tubifex tubifex were transferred to either water (24 h) or sediment (10 weeks) to monitor changes in internal metal concentrations. After 24 h in water, only Ni concentration had declined significantly (p < 0.05), suggesting that the majority of Ni was associated with the gut content, while Cd and Pb were accumulated in the tissues. Metal depuration in sediment was described with two-compartment, first-order kinetic models (r2 = 0.7-0.8; p < 0.001), indicating that T. tubifex has both a quickly depurated and a more tightly bound pool of accumulated metal. Tubifex tubifex were also exposed to sediment spiked with just Cd (3.66 micromol/g). Cadmium uptake and induction of metallothionein-like protein (MTLP) were rapid; both parameters were significantly elevated within 24 h of exposure. Metallothionein-like protein (8.7 +/- 1.8 nmol/g) and Cd (60.8 +/- 11.0 micromol/g) reached maximum concentrations after 96 h and four weeks, respectively.
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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) | 0.001 | 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".