Biomonitoring and Elimination of Perfluorinated Compounds and Polychlorinated Biphenyls through Perspiration: Blood, Urine, and Sweat Study
Bibliographic record
Abstract
Perfluorinated compounds (PFCs) are man-made organofluorine chemicals manufactured and marketed for their stain-resistant properties. Polychlorinated biphenyls (PCBs) are anthropogenic organochlorine compounds previously used in various industrial and chemical applications prior to being banned in the Western world in the 1970s. Both PFCs and PCBs are persistent contaminants within the human organism and both have been linked to adverse health sequelae. Data is lacking on effective means to facilitate clearance of PFCs and PCBs from the body. Methods. Blood, urine, and sweat were collected from 20 individuals (10 healthy participants and 10 participants with assorted health problems) and analyzed for PFCs and PCBs using high performance liquid chromatography tandem mass spectrometry. Results. Some individual PCB congeners, but not all, were released into sweat at varying concentrations. None of the PFCs found in serum testing appeared to be excreted efficiently into perspiration. Conclusions. Induced perspiration may have some role in facilitating elimination of selected PCBs. Sweat analysis may be helpful in establishing the existence of some accrued PCBs in the human body. Sweating does not appear to facilitate clearance of accrued PFHxS (perfluorohexane sulfonate), PFOS (perfluorooctane sulfonate), or PFOA (perfluorooctanoic acid), the most common PFCs found in the human body.
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 | 0.000 | 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) | 0.001 | 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".