The Metabolism of 6:2 FTOH and its Role in Covalent Protein Modifications
Bibliographic record
Abstract
Fluorotelomer alcohols (FTOHs) belong to a group of chemicals called per-and polyfluoroalkyl substances (PFAS).PFAS have been shown to cause toxicity in humans through exposure to household products, ingestion of dust, water, or inhalation of indoor air.Some studies have postulated the mechanism of action for FTOH metabolism, which is that certain metabolites can cause toxicity, such as hormonal discrepancies, immunotoxicity, and possible tumor aggregation.Two understudied groups of bioactive metabolites of FTOHs are the fluorotelomer saturated and unsaturated aldehydes (FTAL and FTUAL).As shown in Figure 1, these are reactive metabolites, due to their highly electrophilic α,β-unsaturated or saturated aldehyde moieties that will react with biological nucleophiles to potentially cause protein modification or inactivation.Yet, the proteins they covalently bind to are unknown.Determining specific proteins will demonstrate how biological mechanisms are affected in the presence of these metabolites.Some issues could include disruption of cellular events or cell signalling leading to toxicity.Therefore, this project focused on the specific proteins modified upon FTOH biotransformation.Our hypothesis was that 6:2 FTAL and/or 6:2 FTUAL would react immediately with the enzyme(s) that produce it, given their high reactivity.Enzymes of interest were cytochrome P450 (CYP) 2A6 and 2E1, which were determined as possible targets from previous studies as they were shown to be active for the metabolism of FTOHs.We also used CYP 3A4 as a negative control.
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 | 0.000 |
| 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) | 0.003 | 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".