Evidence map›Paper›PMID 31141513›Full record

ArticlePLoS computational biology2019

Modeling enamel matrix secretion in mammalian teeth.

Teemu J Häkkinen, S Susanna Sova, Ian J Corfe, Leo Tjäderhane, Antti Hannukainen, Jukka Jernvall

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.8field-weighted citation impact, top 29% of its field
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

6 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
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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 at 2 institutions in 1 country.

Teemu J HäkkinenDevelopmental Biology Program, Institute of Biotechnology, University of Helsinki, Helsinki, Finland.
S Susanna SovaDevelopmental Biology Program, Institute of Biotechnology, University of Helsinki, Helsinki, Finland.
Ian J CorfeDevelopmental Biology Program, Institute of Biotechnology, University of Helsinki, Helsinki, Finland.
Leo TjäderhaneDepartment of Oral and Maxillofacial Diseases, Helsinki University Hospital, University of Helsinki, Helsinki, Finland.ORCID 0000-0002-5018-478X
Antti HannukainenDepartment of Mathematics and Systems Analysis, Aalto University, Espoo, Finland.
Jukka JernvallDevelopmental Biology Program, Institute of Biotechnology, University of Helsinki, Helsinki, Finland.ORCID 0000-0001-6575-8486
University of Helsinki · FIAalto University · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The most mineralized tissue of the mammalian body is tooth enamel. Especially in species with thick enamel, three-dimensional (3D) tomography data has shown that the distribution of enamel varies across the occlusal surface of the tooth crown. Differences in enamel thickness among species and within the tooth crown have been used to examine taxonomic affiliations, life history, and functional properties of teeth. Before becoming fully mineralized, enamel matrix is secreted on the top of a dentine template, and it remains to be explored how matrix thickness is spatially regulated. To provide a predictive framework to examine enamel distribution, we introduce a computational model of enamel matrix secretion that maps the dentine topography to the enamel surface topography. Starting from empirical enamel-dentine junctions, enamel matrix deposition is modeled as a diffusion-limited free boundary problem. Using laboratory microCT and synchrotron tomographic data of pig molars that have markedly different dentine and enamel surface topographies, we show how diffusion-limited matrix deposition accounts for both the process of matrix secretion and the final enamel distribution. Simulations reveal how concave and convex dentine features have distinct effects on enamel surface, thereby explaining why the enamel surface is not a straightforward extrapolation of the dentine template. Human and orangutan molar simulations show that even subtle variation in dentine topography can be mapped to the enamel surface features. Mechanistic models of extracellular matrix deposition can be used to predict occlusal morphologies of teeth.

Indexed as

Models, DentalAlgorithmsAnimalsComputational BiologyComputer SimulationDental EnamelFinite Element AnalysisHumansImaging, Three-DimensionalMammalsMolarSwineToothX-Ray Microtomography

Identifiers

PMID31141513
PMCPMC6541238
OpenAlexW2949127419

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.