The Pyruvate–Glyoxalate Pathway as a Toxicity Assessment Tool of Xenobiotics: Lessons from Prebiotic Chemistry
Bibliographic record
Abstract
There is an urgent need to evaluate the toxicity of xenobiotics and environmental mixtures for preventing loss in water quality for the sustainability of aquatic ecosystems. A simple prebiotic chemical pathway based on malate formation from pyruvate (pyr) and glyoxalate (glyox) is proposed as a quick and cheap screening tool for toxicity assessment. The assay is based on the pyr and glyox (aldol) condensation reactions, leading to biologically relevant precursors such as oxaloacetate and malate. Incubation of pyr and glyox at 40–70 °C in the presence of reduced iron Fe(II) led to malate formation following the first 3 h of incubation. The addition of various xenobiotics/contaminants (silver, copper, zinc, cerium IV, samarium III, dibutylphthalate, 1,3-diphenylguanidine, carbon-walled nanotube, nanoFe2O3 and polystyrene nanoparticles) led to inhibitions in malate synthesis at various degrees. Based on the concentration inhibiting malate concentrations by 20% (IC20), the following potencies were observed: silver < copper ~ 1.3-diphenylguanidine ~ carbon-walled nanotube < zinc ~ samarium < dibutylphthalate ~ samarium < Ce(IV) < nFeO3 < polystyrene nanoplastics. The IC20 values were also significantly correlated with the reported trout acute lethality data, suggesting its potential as an alternative toxicity test. The pyr-glyox pathway was also tested on surface water extracts (C18), identifying the most contaminated sites from large cities and municipal wastewater effluents dispersion plume. The inhibition potencies of the selected test compounds revealed that not only pro-oxidants but also chemicals hindering enolate formation, nucleophilic attack of carbonyls and dehydration involved in aldol-condensation reactions were associated with toxicity. The pyr-glyox pathway is based on prebiotic chemical reactions during the emergence of life and represents a unique tool for identifying toxic compounds individually and in complex mixtures.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".