Assessing toxicity of titanium dioxide (TiO2) nanoparticles on Pseudomonas species biofilms
Bibliographic record
Abstract
Biofilms are essential to the aquatic environment. Recent advances in technology resulted in increased use of nanomaterials (such as titanium dioxide nanoparticles) and their release into aquatic environments with unknown long-term effects. Potential toxicity of titanium dioxide, known for its photocatalytic properties, on Pseudomonas aeruginosa (PAO1-gfp) and Pseudomonas sp. (CT07-gfp) biofilm formation and proliferation was assessed using flowcells, confocal laser scanning microscopy (CLSM), and total and viable cell release into effluent under different titanium dioxide concentrations (100 ppm, 10 ppm and 1 ppm). COMSTAT software analysis was used to obtain quantitative morphological biofilm data. Results showed that titanium dioxide had a concentration and media-dependent effect on biofilm formation, growth, proliferation and viability. Viable effluent cell counts remained within the same order of magnitude. Biofilm recovery was evident within 24-48 hours after exposure. At environmentally relevant concentration (1 ppm), there was no effect on formation, proliferation or growth of the biofilm.
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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".