Branched Perfluorooctane Sulfonate Isomer Quantification and Characterization in Blood Serum Samples by HPLC/ESI-MS(/MS)
Bibliographic record
Abstract
Perfluorooctane sulfonate (PFOS) is a global contaminant and is currently among the most prominent contaminants in human blood and wildlife samples. Although "total PFOS" (SigmaPFOS) analytical methods continue to be the most commonly used for quantification, recent analytical method developments have made it possible to resolve the various isomers of PFOS by HPLC-MS/MS. Characterized technical PFOS standards (i.e., containing a mixture of PFOS isomers) are now available that enable isomer specific quantification of PFOS, however the advantages of such an analysis have notyet been examined systematically. Herein, PFOS isomers have been individually quantified for the first time in real samples and the results are compared to a traditional SigmaPFOS method; the influence of analytical standards and isomer specific electrospray and MS/ MS behavior were also investigated. The two human serum standard reference materials chosen for analysis contained dramaticallydifferent PFOS isomer profiles (approximately 30-50% total branched isomers) emphasizing that isomer patterns should not be ignored and may provide useful information on exposure sources (i.e., direct exposure to PFOS vs indirect exposure from PFOS-precursors). Depending on the sample and the particular MS/MS transition chosen for SigmaPFOS analysis (i.e., 499-->80 or 499-->99), SigmaPFOS concentrations may be over- or underestimated compared to the isomer specific analysis. Differences in the extent of in-source fragmentation and MS/MS dissociation contributed to the systematic analytical bias. It was also shown that SigmaPFOS data are prone to interlaboratory variation due to various choices of PFOS standards and instrumental conditions used. In the future, for either SigmaPFOS or isomer specific PFOS analyses, we suggest that accuracy can be maximized and interlaboratory discrepancies minimized by using a common chemically pure technical PFOS standard characterized by 19F NMR.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".