Evidence map›Paper›PMID 42239147›Full record

ArticlebioRxiv : the preprint server for biology2026

MRI-based dental maturity in newborns reflects prenatal exposures and predicts timing of primary tooth eruption.

Ying Meng, Thomas G O'Connor, Felicitas B Bidlack, Scotty A Simmons, Jin Xiao, Jerod M Rasmussen

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ying MengSchool of Nursing, University of Rochester, Rochester, NY.
Thomas G O'ConnorDepartments of Psychiatry, Neuroscience, Obstetrics and Gynecology, University of Rochester, Rochester, NY.
Felicitas B BidlackCraniofacial Biology and Bioengineering, ADA Forsyth Institute, Inc., Somerville, MA.
Scotty A SimmonsDepartment of Neurobiology and Behavior, University of California, Irvine, CA.
Jin XiaoEastman Institute for Oral Health, University of Rochester Medical Center, Rochester, NY.
Jerod M RasmussenDepartment of Pediatrics and Biomedical Engineering, University of California, Irvine, CA.ORCID 0000-0002-9400-7750

Funding

Pre- and Postnatal Exposure Periods for Child Health: Common Risks and Shared MechanismsUH3OD023349 · OD · UNIVERSITY OF ROCHESTER · PI Emily S Barrett, Richard Kermit Miller · 2018 to 2026
$15.9M
Pre- and Postnatal Exposure Periods for Child Health: Common Risks and Shared MechanismsUG3OD023349 · OD · UNIVERSITY OF ROCHESTER · PI BARRETT, EMILY S, MILLER, RICHARD KERMIT · 2016 to 2024
$7.0M
Developmental Programming of the Human Hypothalamus and its Role in Motivated BehaviorsR01MH138481 · NIMH · UNIVERSITY OF CALIFORNIA-IRVINE · PI Jerod Michael Rasmussen · 2025 to 2026
$785k
Fetal Programming of Human Newborn Energy Homeostasis Brain NetworksR00HD100593 · NICHD · UNIVERSITY OF CALIFORNIA-IRVINE · PI RASMUSSEN, JEROD MICHAEL · 2023 to 2025
$744k
NICHD NIH HHS R00 HD100593NIH HHS UG3 OD023349NIH HHS UH3 OD023349NIMH NIH HHS R01 MH138481
6 · The paper itself

Abstract

Primary tooth development is shaped by prenatal experience and has consequences for childhood caries and lifelong oral health. However, evidence linking prenatal conditions to dental development has relied largely on postnatal proxies, such as parent-recalled eruption timing, that conflate prenatal programming with postnatal exposures. Here, we directly phenotype developing dentition in vivo using routinely acquired neonatal brain MRI. Using T2-weighted imaging from the HEALthy Brain and Child Development Study, we trained a 3D U-Neton 100 semi-automatic labels and applied the model to 1,433 quality-controlled neonatal scans. Automated post-processing extracted quantitative features of tooth volume, mineralization, and arch geometry. These features were used to predict postmenstrual age at MRI and to derive a bias-corrected tooth age gap (TAG), indexing relative dental maturity at birth. The segmentation model achieved mean cross-validated Dice = 0.94. Dental features predicted postmenstrual age with R

Indexed as

dental maturitydevelopmental programmingHBCDneonatal MRIprenatal exposurestooth eruption

Identifiers

PMID42239147
PMCPMC13228430

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.