In vitro metabolism of sunscreen compounds by liquid chromatography/high‐resolution tandem mass spectrometry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
RATIONALE: Exposure to UV light can induce adverse effects on human health, such as photo-aging, immunosuppression, and cancer. Sunscreens are used to prevent the absorption of UV rays, but certain UV-filtering compounds have been shown to disrupt endocrine systems or act as carcinogens. To assess the effects of the exposure to such compounds, it is important to study the pathways by which they are biotransformed in the body. METHODS: Liquid chromatography coupled to high-resolution tandem mass spectrometry (LC/HRMS/MS) was employed to evaluate the oxidative metabolism and, specifically, the formation of reactive metabolites of six active ingredients commonly used in sunscreen formulations: oxybenzone, avobenzone, homosalate, octisalate, octocrylene, and octinoxate. In vitro incubations were performed with human and rat liver microsomes in the presence of β-nicotinamide adenine dinucleotide phosphate and glutathione. An LC/HRMS/MS method was developed to identify metabolites employing a biphenyl reversed-phase column for separating parent molecules, metabolites, and glutathione (GSH) adducts. RESULTS: Each tested compound resulted in the formation of several metabolites, including at least one GSH adduct. Compounds containing ester groups were hydrolyzed, and some metabolites of the free acid forms were also detected. High-resolution MS/MS data was crucial for the structural elucidation of metabolites and GSH adducts. Fragmentation pathways were proposed for all parent compounds, as well as each described metabolite and adduct. CONCLUSIONS: The results of this study will help better understand the metabolism and detoxification pathways of these xenobiotics.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it