Isomer–Specific Distribution of Perfluoroalkyl Substances in Blood
Bibliographic record
Abstract
Perfluoroalkyl substances (PFASs) such as perfluorohexanesulfonate (PFHxS), perfluorooctanoate (PFOA), perfluorooctanesulfonate (PFOS) and PFOS-precursors are routinely measured in human plasma and serum, but their relative abundance in the blood cell fraction has not been carefully examined, particularly at the isomer-specific level. Human plasma and whole blood were collected and partitioning behaviors of PFASs and their isomers between plasma and blood cells were investigated. In human samples, mass fraction in plasma (Fp) for PFASs increased among perfluoroalkyl carboxylates as the carbon chain length increased from C6 (mean 0.24) to C11 (0.87), indicating preference for the plasma fraction with increasing chain length. However, among perfluoroalkyl sulfonates, PFHxS (mean 0.87) had a slightly higher Fp than PFOS (0.85). In vitro assays with spiked Sprague-Dawley rat blood were also conducted, and the results showed that PFOS-precursors had lower Fp values than perfluoroalkyl acids, with perfluoroctanesulfonamide having the lowest Fp (mean 0.24). Consistently, linear isomers of PFOS and PFOS-precursors had lower mean Fp than their corresponding total branched isomers. Multiplying by a factor of 2 is not a reasonable method to convert from whole blood to plasma PFAS concentrations, and current ratios could be used as more accurate conversion factors.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".