Number of Carbons Is a Critical Parameter for Accumulation of Per- and Polyfluoroalkyl Substances in the Human Brain
Bibliographic record
Abstract
Per- and polyfluoroalkyl substances (PFAS), a large group of manmade chemicals, have been detected extensively in the blood of people living in developed countries. Although it has been suggested that PFAS exposure might be associated with harmful effects on the brain, few studies have assessed the presence of PFAS in brain tissues. This study aimed to evaluate the concentrations of a broad range of PFAS in paired postmortem human brain and serum samples and investigate brain-to-serum concentration ratios. A partitioning experiment using PFAS-fortified animal brain samples additionally investigated differences in distribution between lipid-rich brain and water for different PFAS. Out of the 43 PFAS analyzed, 5 were detected in all paired human brain and serum samples, 11 were found in all serum, and 7 were found in all brain samples. Two PFAS compounds were observed at notably higher detection frequencies in brain samples compared to serum. The brain-to-serum ratios of PFAS concentrations ranged from approximately 0.04 for perfluorohexanesulfonate (PFHxS) to 1.3 for N -methyl perfluorooctanesulfonamido acetic acid ( N -MeFOSAA) with a clear increase in PFAS brain-to-serum ratios with the total number of carbons. There were no differences between the two cortical brain regions analyzed. Results underscore the necessity of a better understanding of individual PFAS, as the difference in their properties can influence their behavior within the human brain.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".