Evidence map›Paper›PMID 36404956›Full record

ReviewThe Japanese dental science review2022

The structural motifs of mineralized hard tissues from nano- to mesoscale: A future perspective for material science.

Jingxiao Zhong, Yo Shibata

Open access · goldAbstract readReview
In one paragraph

Review in The Japanese dental science review, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 34% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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  5. Review
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

2 authors at 2 institutions in 2 countries.

Jingxiao ZhongSchool of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, Sydney, Australia.
Yo ShibataDepartment of Conservative Dentistry, Division of Biomaterials and Engineering, Showa University School of Dentistry, Tokyo, Japan.
Showa University · JPThe University of Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biological tissues have developed structures that fulfil their various specific requirements. Mineralized tissues, such as tooth and bone, are often of mechanical competence for load bearing. Tooth enamel is the hardest and toughest mineralized tissue. Despite a few millimeters thick and with minimal regenerative capacity, human tooth enamel maintains its functions throughout a lifetime. Bone provides skeletal support and essential metabolism to our body. Degenerative diseases and ageing induce the loss of mechanical integrity of the bone, increasing the susceptibility to fractures. Tooth and bone share certain commonalities in chemical components and material characteristics, both consisting of nanocrystalline apatite and matrix proteins as their basic foundational structural units. Although the mechanical properties of such mineralized hard tissues remain unclear, it is plausible that they have an inherent toughening mechanism. Nanoindentation is able to characterize the mechanical properties of tooth enamel and bone at multiscale levels, and the results suggest that such toughening mechanisms of enamel and bone may be mainly associated with the smallest-scale structure-function relationships. These findings will benefit the development of advanced biomaterials in the field of material science and will further our understanding of degenerative bone disease in the clinical community.

Indexed as

BoneMechanical propertyMineralized tissueNanoindentationTooth

Identifiers

PMID36404956
PMCPMC9672955
OpenAlexW4308945912

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.