The detection and quantification of ethyl glucuronide in placental tissue and placental perfusate by headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry.
Bibliographic record
Abstract
BACKGROUND: Ethyl glucuronide (EtG) is arising as a promising biomarker of heavy prenatal alcohol exposure, however its transfer across the human placenta is still unclear and is currently being investigated using the ex vivo placental perfusion model. This model allows for sampling from placental tissue and placental perfusate, which is a surrogate to plasma. OBJECTIVE: To develop a method for detecting and quantifying EtG in placental perfusate and tissue using headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). METHODS: A method was optimized by manipulation of the following components to attain the highest peak counts for the quantifying ions of EtG and its deuterated internal standard on the mass spectrum: cartridges used for solid phase extraction, injection method, derivatizing agent, pre-injection parameters, SPME fiber, GC ramp speed, and GC column flow. RESULTS: The final method utilized involved solid phase extraction of standards via UCT CleanScreen Cartridges, derivatization with heptafluorobutyric acid, and introduction into the GC via HS-SPME with adsorption to a polydimethylsiloxane fiber. The method has improved sensitivity over other methods that quantify EtG in blood using GC-MS, with detection limits of 1.6 ng/mL and 13.7 ng/g for placental perfusate and tissue, respectively. The method was applied to samples collected from the fetal reservoir during the ex vivo placental perfusion model and EtG was detected in the fetal circulation after 20 minutes of perfusion, indicating transfer of EtG. CONCLUSIONS: The present method is sensitive and can be used to quantify EtG transfer during ex vivo placental perfusion experiments.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.000 | 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 teacher head, 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".