Gastrointestinal Elimination of Perfluorinated Compounds Using Cholestyramine and <i>Chlorella pyrenoidosa</i>
Bibliographic record
Abstract
Background. While perfluorinated compounds (PFCs) are a family of commonly used synthetic compounds with many applications, some PFCs remain persistent within the human body due, in part, to enterohepatic recirculation and renal tubular reabsorption. With increasing recognition of potential harm to human health associated with PFC bioaccumulation, interventions to facilitate elimination of these toxicants are welcome in order to potentially preclude or overcome illness. Minimal research has been undertaken thus far on methods to accelerate human clearance of PFCs. Methods. To test for possible oral treatments to hasten PFC elimination, a group of individuals with elevated PFC levels was treated with cholestyramine (CSM) and, after a break, was subsequently treated with Chlorella pyrenoidosa (CP). Stool samples were collected from all participants (i) prior to any treatment, (ii) during treatment with CSM, and (iii) during treatment with CP. Results. With CSM treatment, significant levels of three distinct PFCs were found in all stools, while levels were mostly undetectable prior to treatment. Following treatment with oral CP, undetectable or very low levels of all PFCs were noted in each sample tested. Conclusion. CSM appears to facilitate elimination of some common PFCs and may have some role in the clinical management of patients with accrued PFCs.
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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 | 0.000 |
| 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".