Autoantibodies and Levels of Polychlorinated Biphenyls in Persons Living near a Hazardous Waste Treatment Facility
Bibliographic record
Abstract
Background Increased autoantibody prevalence has been described in instances of high-dose exposure to polychlorinated biphenyls (PCBs). In 1996, an equipment malfunction at the Swan Hills Treatment Centre in Alberta, Canada, caused the release of gases containing PCBs into the ambient air. In view of the immune effects of PCBs and their potential as endocrine disruptors, we assessed autoantibody prevalence and looked for correlations with PCB levels. Methods Fifty-seven persons living within a 100 km radius of the waste treatment facility were assessed. Autoantibodies were measured by indirect immunofluorescence, double immunodiffusion, and immunoblotting. The levels of 26 congeners of PCBs were measured by gas chromatography and mass spectrometry. Provincial health records for physician visits and hospitalizations were reviewed for diagnoses of autoimmune disease. Results The prevalence of autoantibodies was 11% in the study participants and 0% in healthy controls. There was no correlation of PCB levels with autoantibody results. There was no associated increase in autoimmune disease noted on physician visits or hospitalizations. PCB levels were comparable to background levels reported for other populations. Conclusion A correlation of titers of autoantibodies in the sera of individuals at risk and the blood levels of PCBs was not found, and the prevalence of autoantibodies in the at-risk group was not statistically different ( p > .05) from that of an unexposed control group. The study group had higher titers of autoantibodies and some strong reactivity with intracellular antigens, but the significance of this observation may be understood only after long-term clinical assessments and follow-up.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".