Partitioning of Polychlorinated Biphenyls into Human Cells and Adipose Tissues: Evaluation of Octanol, Triolein, and Liposomes as Surrogates
Bibliographic record
Abstract
Whereas octanol, triacylglycerides, and liposomes have all been proposed as surrogates for measuring the affinity of hydrophobic organic contaminants to human lipids, no comparative evaluation of their suitability exists. Here we conducted batch sorption experiments with polyoxymethylene passive samplers to determine the partition coefficients at 37 °C of 18 polychlorinated biphenyls (PCBs) from water into (i) triolein (Ktriolein/water), (ii) eight types of liposomes (Kliposome/water), (iii) human abdominal fat tissues (KAFT/water) from seven individuals, and (iv) human MCF-7 cells cultured in vitro (Kcell/water). Differences between KAFT/water among individuals and between Kliposome/water among liposome types were very small and not correlated to structural attributes of the PCBs. Similarly, the length and degree of saturation of the phospholipid carbon chains, the headgroup, and the composition of the liposome did not affect the partitioning of PCBs into the studied liposomes. Whereas Kliposome/water values were similar to literature values of Koctanol/water adjusted to 37 °C, they both were lower than KAFT/water and Kcell/water by a factor of 3 on average. Partitioning of PCBs into triolein on the other hand closely mimicked that into human lipids, for which triolein is thus a better surrogate than either octanol or liposomes. Previously published polyparameter linear free energy relationships for partitioning from water into storage lipids and liposomes predicted the measured partition coefficients with a root-mean-square error of less than 0.15 log units, if the chosen equations and solute descriptors do not allow chlorine substitution in the ortho-position to influence the prediction. By guiding the selection of (i) a surrogate for the experimental determination and (ii) a method for the prediction of partitioning into human lipids, this study contributes to a better assessment of hydrophobic organic contaminant bioaccumulation in humans.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".