The influence of polystyrene nanoparticles on the fractal kinetics of lactate dehydrogenase
Bibliographic record
Abstract
Plastics are ubiquitous in the aquatic environment and their degradation of fragments down to the nanoscale level have raised concerns given their ability to pervade cells. The accumulation of nanoparticles could lead to molecular crowding which can alter the normal functioning of enzymes. The purpose of this study was to examine the influence of polystyrene nanoparticles (NPs) on the fractal kinetics of the lactate dehydrogenase reaction: pyruvate + NADH ↔ lactate + NAD+. The influence of NPs on LDH activity was examined first in vitro to highlight specific effects and secondly in mussels exposed to NPs in vivo for 24h at 15 °C. The reaction rates of LDH were determined with increasing concentrations of pyruvate to reach saturation at circa 1 mM pyruvate. The addition of F-actin, a known binding template for LDH, revealed a characteristic change in reaction rates associated with fractal organization. The addition of 50 and 100 nm transparent NPs also produced these changes. The fractal dimension was determined and revealed that both F-actin and NPs reduced the fractal dimension of the LDH reaction. The addition of viscosity sensor probe in the reaction media revealed viscosity waves during the reaction at low substrate concentrations thought to be associated to synchronized switching between the relaxed and tensed states of LDH. The amplitude and the frequency of viscosity waves were increased by both NPs and F-actin which were associated with increased reaction rates. In mussels exposed to NPs, the isolation of digestive gland subcellular fraction revealed that LDH activity was significantly influenced by the fractal dimension of the LDH reaction where a loss of affinity (high fractal KM) was detected in mussels exposed to the high concentrations of NPs. It is concluded that polystyrene NPs could change the biophysical properties of the cytoplasm such as the fractal organization of the intracellular environment during the LDH reaction.
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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 | 0.001 |
| 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".