Crowding Effects of Polystyrene Nanoparticles on Lactate Dehydrogenase Activity in Hydra Attenuata
Bibliographic record
Abstract
Plastics pervade our environment and potentially release important quantities of plastic nanoparticles (NPs) from degradation in the environment. The purpose of this study was to examine the crowding effects of polystyrene NPs on lactate dehydrogenase (LDH) in vitro and following exposure to Hydra attenuata. First, LDH activity was measured in vitro in the presence of filamentous (F-)actin and NPs (50 and 100 nm diameter) to determine changes in viscosity and the fractal kinetics of LDH. The fractal dimension (fD) was also determined using the rescaled range analysis procedure. Secondly, these changes were examined in hydra exposed to NPs for 96h to concentrations of NPs. The data revealed that the addition of F-actin increased the rate of LDH at low substrate (pyruvate) concentrations compared to LDH alone with a gradual decrease in the rate with the addition of pyruvate, which is characteristic of the fractal behavior of enzymes in crowded environments. The addition of 50 and 100 nm NPs also produced these changes, which suggest that NPs could change the space properties of the LDH reaction. The fD was reduced to 0.85 and 0.91 with 50 and 100 nm NPs compared to 1.093 with LDH alone. Decrease in the fD was related with increased amplitudes and frequency in viscosity waves in the reaction media. Exposure of hydra to NPs confirmed the increase in LDH activity and the fD was significantly correlated with LDH activity (r = −0.5). Correction of LDH activity (residuals) still revealed an increase in LDH activity in hydra suggesting increased anaerobic metabolism by NPs. In conclusion, the presence of NPs in the intracellular space decreased the fD, which could influence LDH activity in organisms exposed to NPs.
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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".