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Record W4224271180 · doi:10.1021/acs.estlett.2c00186

Maternal Exposure to Polystyrene Micro- and Nanoplastics Causes Fetal Growth Restriction in Mice

2022· article· en· W4224271180 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnvironmental Science & Technology Letters · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsMount Sinai HospitalHospital for Sick ChildrenUniversity of TorontoMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaBanting Research Foundation
KeywordsMicroplasticsFetusFetal growthGestationPregnancyPolystyreneAndrologyPhysiologyChemistryMedicineToxicologyBiologyEnvironmental chemistryPolymer

Abstract

fetched live from OpenAlex

Plastics are ubiquitous and, when released into the environment, break down into smaller particles termed microplastics (MPs) and nanoplastics (NPs). These MPs and NPs can be ingested by organisms and potentially accumulate in tissues and organs. Recently, MPs were found in the placentas of healthy women, raising the concern that exposure to plastics may have an impact on pregnancy and fetal development. In this study, we investigated the effect of maternal exposure to plastics on fetal and placental growth using experimental mice. The dams exposed to plastics received either 5 μm or 50 nm polystyrene plastics in filtered drinking water at one of three concentrations (102, 104, or 106 ng/L). In late gestation, MP- and NP-exposed fetuses were significantly growth restricted, with a 12% decrease in fetal weight at the highest exposure concentration. This study represents a crucial first step toward evaluating the risks to human pregnancies posed by exposure to plastics.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.003
GPT teacher head0.168
Teacher spread0.165 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it