Measurement of 24 phthalate metabolites in 1st trimester urine samples: The MIREC study
Bibliographic record
Abstract
Phthalates are non-persistent chemicals measured as metabolites in urine. Over time, new metabolites have been identified. In the original Maternal-Infant Research on Environmental Chemicals (MIREC) study (2008-2011), we measured 11 phthalate metabolites in first trimester urine samples. The goal of the present study was to develop a method to measure new metabolites, to increase the sensitivity for some previously measured metabolites, and to measure these new metabolites in biobanked urine samples from MIREC participants. Using Ultra Performance Liquid Chromatography with a tandem mass spectrometer, we developed a method to measure 24 metabolites from 10 different parent phthalates. Chromatographic interpretation of some of the di-iso-decyl phthalate metabolites (mono-(2-propyl-6oxoheptyl) phthalate (MOiDP), mono-(2,7-methyl-7-carboxyheptyl) phthalate (MCiNP), mono-(2-propyl-6-hydroxy-heptyl) phthalate (MHiDP)) and di-iso-nonyl phthalate metabolites (mono(oxo-isononyl) phthalate (MOiNP), mono(carboxy-isooctyl) phthalate (MCiOP), mono(hydroxy-isononyl) phthalate (MHiNP) and mono-isononyl phthalate (MiNP)) was challenging as these are complex isomeric mixtures. To validate and confirm our quantitation peaks, an assay using a high-resolution detection technique was developed on a Quadrupole Time-of-Flight (QToF) system. This system has a mass resolution of at least 0.005 amu, compared to 0.5 amu for the MS/MS detector. Using the QToF system, the distinction between an isomer and possible interference was achieved with the use of the exact mass. In about 1800 MIREC samples, mono-cyclo-hexyl phthalate (MCHP), mono-(7-carboxy-n-heptyl) phthalate (MCHpP), mono-iso-decyl phthalate (MiDP), and mono-n-octyl phthalate (MnOP) were rarely detected, while detection of MMP was improved. MCiOP, MiNP and MCiNP had to be reported semi-quantitatively. Given the complexity of isomeric mixtures of some phthalates, researchers must be careful in their determination of the analytes and the approach used in their quantification when generating biomonitoring data. This study produced biomonitoring data for a large population of pregnant people that can be used in risk assessment of phthalates. Future work will examine associations with birth and child outcomes.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".