Biological Markers of IntrauterineExposure to Cocaine and CigaretteSmoking
Bibliographic record
Abstract
We describe hair tests for assessment of fetal exposure to cocaine and cigarette smoking. Cocaine and its major metabolites are incorporated into hair during the growth of the shaft and stay there for the whole life of the hair. Cocaine crosses the placenta and its metabolite benzoylecgonine, has been found in neonatal urine, meconium and hair. In order to utilize hair measurements of cocaine as a biological marker of systemic exposure, we conducted both animal and human investigations on the dose response characteristics of this phenomenon. Our data suggest that both maternal and fetal accumulation of cocaine and its metabolite follow a linear pattern within the regularly used doses. Similarly, a good correlation was observed in animals between maternal dose and fetal hair accumulation. To date, no biological markers have been identified that can predict the extent of fetal exposure to the adverse effects of toxic constituents of cigarette smoke. We measured maternal and fetal hair concentrations of nicotine and cotinine in mother-infant pairs. Smoking mothers had a mean of 21.3 ± 18 ng/mg hair nicotine and 6 ± 9.2 ng/mg of cotinine, significantly more than nonsmokers (0.9 ± 0.8 ng/mg nicotine and 0.3 ± 0.5 ng/mg cotinine, p < 0.0001). Babies of smokers had a mean nicotine concentration of 6 ± 9.2 ng/mg (range 0-27.3) and cotinine of 2.1 ± 3.7 ng/mg (range 0-12.2), significantly more than babies of nonsmokers (nicotine 0.6 ± 0.7 ng/mg and cotinine 0.2 ± 0.5 ng/mg; p < 0.01). There was no correlation between the number of cigarettes consumed daily and either maternal or infant’s hair concentrations of nicotine or cotinine. Conversely, there was a significant correlation between maternal and neonatal hair concentrations of nicotine (r=0.78,p = 0.01)or cotinine (r = 0.64, p < 0.05). Among nonsmokers, a subgroup of‘passive smokers’ had significantly more cotinine in their and their babies’ hair than those exposed to no smoke at all.
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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 | 0.000 | 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) | 0.000 | 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".