Microplastic Impacts on Microalgae Growth: Effects of Size and Humic Acid
Bibliographic record
Abstract
Research has already demonstrated the toxic effects of microplastics (MPs) on different biota. However, the underlying toxic mechanism of MPs remains to be elucidated, especially the effect of particle size and the presence of dissolved organic matter in water. This study investigated the impact on Scenedesmus obliquus exposed in five types of polystyrene particle suspensions with different sizes and surface charges, in the presence and absence of humic acid (HA). Results indicated that the 50% growth inhibition rate of S. obliquus showed no significant difference between the five types of MPs, but the toxic mechanism varied with particle size. Larger size MPs caused adverse effects by blocking the light transport and affecting photosynthesis, while smaller ones destroyed the cell wall by adsorbing onto the algae surface. Also, the addition of HA significantly alleviated the toxicity of smaller size MPs, but not of the larger ones. Scanning electron microscopy images and the reactive oxygen species assay demonstrated that the HA could form a corona on the surface of MPs, reduce the affinity to microalgae, and minimize the adverse effect. Together, these findings identified important factors in determining the toxicity of MPs, providing valuable data for risk assessment of MPs.
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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) | 0.000 | 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 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".