The development of biological markers for the identification of intrauterine alcohol exposure
Bibliographic record
Abstract
Confirmation of gestational ethanol exposure is required for the diagnosis of Fetal Alcohol Spectrum Disorder. The development of a novel neonatal screening test for fatty acid ethyl esters (FAEE) in meconium was investigated in this thesis. The potential application of meconium FAEE screening in the absence of maternal drinking history was investigated in a high-risk population. A substantial proportion of neonates (14%) suspected of intrauterine substance exposure were likely exposed to heavy maternal drinking, as identified by meconium screening. Baseline FAEE measurements in the meconium of neonates (n = 183) born to non-drinking mothers from Jerusalem and Toronto were investigated. Certain FAEE (ethyl laurate and myristate) were detected mostly at trace levels among non-exposed neonates. The presence of elevated levels of multiple FAEE (5--25 fold) and the presence of longer chain FAEE (ethyl palmitate, stearate, oleate, linoleate) were characteristic of neonates born to drinking mothers (n = 6). The use of cumulative FAEE measurements ge;2 nmol/g (excluding ethyl laurate and myristate) as a positive cut-off distinguished neonates with and without heavy prenatal alcohol exposure with the highest sensitivity (100%) and specificity (98%). The transfer and metabolic handling of FAEE by the human placenta was investigated to elucidate the origin of meconium FAEE. In vitro placental perfusion of 4 FAEE (ethyl palmitate, stearate, oleate, linoleate) at low and high concentrations (2--20 muM) in the absence and presence of a physiologic carrier, albumin, did not result in maternal-fetal transfer. Subsequent kinetic studies using subcellular preparations revealed that the majority of maternally derived FAEE were taken up and metabolized by enzymatic activities localized in the microsomal fraction of the human placenta (Mean Km 35--95 muM; Vmax 0.6--1.8 nmol/min/mg). Hence, FAEE detected in meconium were likely produced by the fetus from the ethanol that has been transferred to and metabolized by the fetus. These findings strongly support further validation of meconium FAEE as biomarkers of prenatal alcohol exposure. Future use of meconium FAEE screening as an objective and non-invasive method for the confirmation of intrauterine ethanol exposure can potentially facilitate earlier diagnosis and interventions in the affected children, leading to more favourable 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".