Determining the molecular interactions of perfluorinated carboxylic acids with human sera and isolated human serum albumin using nuclear magnetic resonance spectroscopy
Bibliographic record
Abstract
Perfluorooctanoate (PFOA) is ubiquitous in North American human sera and has a serum half-life of 3.5 years in humans. The molecular interactions that lead to the bioaccumulation of these hydrophobic and lipophobic molecules in human blood are not well understood. Perfluorohexanoic acid (PFHxA) and PFOA were used as model perfluorinated carboxylic acids (PFCAs) to characterize the major site of PFCA interaction in human sera. Using novel heteronuclear saturation transfer difference nuclear magnetic resonance spectroscopy experiments, human serum albumin (HSA) was identified as the major site of interaction for both PFHxA and PFOA in human sera. Heteronuclear single quantum coherence nuclear magnetic resonance experiments were then performed to interrogate site-specific interactions of PFHxA and PFOA with isolated HSA. Perfluorohexanoic acid was found to bind specifically to Sudlow's drug-binding site II, whereas PFOA interacted preferentially with Sudlow's drug-binding site I at the lower concentration, with additional interactions developing at the higher concentration. These experiments highlight the utility of nuclear magnetic resonance spectrometry as a tool to observe the in situ interactions of chemical contaminants with biological systems. Both PFCAs displaced the endogenous HSA ligand oleic acid at concentrations lower than observed for the drugs ibuprofen and phenylbutazone, which are established HSA ligands. Interactions between PFCAs and HSA may affect the pharmacokinetics and distribution of fatty acids and certain drugs in the human body and warrant further investigation.
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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".