Vitro toxicity assessments of nano-ZnS on bovine serum albumin by multispectroscopic methods
Bibliographic record
Abstract
Measuring protein damaged by nanomaterials may give insight into the mechanisms of toxicity of nanomaterials. The toxic effects of nano-ZnS, nano-Al2O3, nano-ZnCO3, and nano-SiO2 on bovine serum albumin (BSA) were thoroughly studied by multispectroscopic methods, including resonance light scattering, UV-vis absorption spectroscopy, fluorescence spectroscopy, circular dichroism, etc., and the most obvious changes were observed when nano-ZnS interacted with BSA among the four nanoparticles. The experimental results showed that nano-ZnS can bind with BSA to form a complex when the conjugating ratio is 1:1. nano-ZnS can alter the structure of BSA, leading to a loosening of the protein skeleton, and therefore, the internal hydrophobic amino acids are exposed in the loose structure, which indicated that nano-ZnS has an obvious toxic effect on BSA. This work provides a new perspective and method for determining the toxic effects of nanomaterials on biological macromolecules.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".