Particulate contamination of human placenta: Plastic and non-plastic
Bibliographic record
Abstract
Recent evidence indicates that the human womb is contaminated with a variety of particulate contaminants. Microplastics (MPs, tiny plastic particles, 0.1 – 5000 µm) generated by the breakdown of larger plastic products in the environment) accumulation in human placenta has recently been described. In addition, recent evidence has correlated the number of air pollution particulates in term placentas to the loading of these particles in dust from the gestational parent home. The current study sought to characterize the accumulation of plastic and non-plastic particles (NPP) within the term human placenta. Placenta tissues were collected from healthy, singleton pregnancies following vaginal (n=5) and caesarean section (n=5) deliveries at a tertiary care centre located in an urban Canadian city (Ottawa, ON), with particles detected and characterized by Raman micro-spectroscopy. Both plastic and non-plastic particles were identified in all placentas examined, with an average of 1 ± 1.2 MPs /g and 4 ± 2.9 NPP /g of tissue. Similar tissue concentrations of MPs and NNP were identified in all regions of the placenta (basal plate, chorionic villous, chorionic plate), and did not differ according to mode of delivery. MPs ranged in size (2 – 60 μm), with the most abundant MPs being polyethylene (PE), polypropylene (PP), polystyrene (PS) and polyvinyl chloride (PVC). The most abundantly identified NPP were carbon, graphite, and lead oxide. Collectively, these results demonstrate the accumulation of foreign particles, including MPs, throughout the human placenta. Given the vital functions of the placenta in supporting fetal growth and development, and a potential for MPs to induce toxicity, further investigations into the potential harmful effects of these environmental toxicants on maternal and fetal health is warranted.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".