Detection of polystyrene nanoplastics in biological tissues with a fluorescent molecular rotor probe
Bibliographic record
Abstract
The release of nanoplastics (NPs) from the weathering and degradation of plastics is an important environmental concern. Given their small sizes and their invasiveness in cells, methods for the detection of NPs in biological tissues are urgently needed. A simple fluorescence-based methodology for the detection of polystyrene NPs in biological tissues is proposed. The commercially available molecular rotor probe 9- (dicyanovinyl)-julolidine (DCVJ) has the properties to detect changes in hydrophobicity and microviscosity and was used to detect NPs. Increasing concentrations of 50 and 100 nm NPs in water and in tissue extracts were mixed with the DCVJ probe and the emission spectra determined between 480-800 nm at 450 nm excitation. The data revealed that NPs induces a second emission peak at 620 nm that differed from the normal spectra of the biological extract at 500 nm. A significant linear relationship was obtained for NPs of both sizes (r=0.98; P<0.001) with a theoretical limit of detection of 65 ng/mL. A simple and rapid microplate spectrofluorometric method for the semi-quantitative detection of polystyrene NPs in biological tissues is thus presented.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".