A Comparative Study on Heavy Metal Removal from CCA-Treated Wood Waste by Yarrowia lipolytica: Effects of Metal Stress
Bibliographic record
Abstract
Bioremediation is an effective way to remove heavy metals from pollutants. This study investigated the effects of Yarrowia lipolytica (Y. lipolytica) on the bioremediation of chromated copper arsenate (CCA)-treated wood wastes. Copper ions stressed the yeast strains to improve their bioremediation efficiency. A comparison of changes in morphology, chemical composition, and metal content of CCA wood before and after bioremediation was conducted. The amount of arsenic (As), chromium (Cr), and copper (Cu) was quantified by microwave plasma atomic emission spectrometer. The results showed that yeast strains remained on the surface of CCA-treated wood after bioremediation. The morphologies of the strains changed from net to spherical because of the Cu2+ stress. Fourier-transform infrared spectroscopy showed that carboxylic acid groups of wood were released after removing heavy metals. A large amount of oxalic acid was observed when the optical density (OD600nm) was 0.05 on the 21st day. Meanwhile, the highest removal rate of Cu, As, and Cr was 82.8%, 68.3%, and 43.1%, respectively. Furthermore, the Cu removal from CCA-treated wood increased by about 20% after Cu2+ stress. This study showed that it is feasible to remove heavy metals from CCA-treated wood by Y. lipolytica without destroying the wood structure, especially by copper-induced Y. lipolytica.
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".