Evidence map›Paper›PMID 35742996›Full record

ReviewInternational journal of molecular sciences2022

Silicon Nitride as a Biomedical Material: An Overview.

Xiaoyu Du, Seunghun S Lee, Gurdial Blugan, Stephen J Ferguson

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

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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

4 authors.

Xiaoyu DuInstitute for Biomechanics, ETH Zurich, 8093 Zurich, Switzerland.ORCID 0000-0003-2532-731X
Seunghun S LeeInstitute for Biomechanics, ETH Zurich, 8093 Zurich, Switzerland.ORCID 0000-0002-9654-8577
Gurdial BluganLaboratory for High Performance Ceramics, Empa, Swiss Federal Laboratories for Materials Science and Technology, 8600 Dübendorf, Switzerland.
Stephen J FergusonInstitute for Biomechanics, ETH Zurich, 8093 Zurich, Switzerland.

Funding

European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant 812765
6 · The paper itself

Abstract

Silicon nitride possesses a variety of excellent properties that can be specifically designed and manufactured for different medical applications. On the one hand, silicon nitride is known to have good mechanical properties, such as high strength and fracture toughness. On the other hand, the uniqueness of the osteogenic/antibacterial dualism of silicon nitride makes it a favorable bioceramic for implants. The surface of silicon nitride can simultaneously inhibit the proliferation of bacteria while supporting the physiological activities of eukaryotic cells and promoting the healing of bone tissue. There are hardly any biomaterials that possess all these properties concurrently. Although silicon nitride has been intensively studied as a biomedical material for years, there is a paucity of comprehensive data on its properties and medical applications. To provide a comprehensive understanding of this potential cornerstone material of the medical field, this review presents scientific and technical data on silicon nitride, including its mechanical properties, osteogenic behavior, and antibacterial capabilities. In addition, this paper highlights the current and potential medical use of silicon nitride and explains the bottlenecks that need to be addressed, as well as possible solutions.

Indexed as

CeramicsSilicon CompoundsAnti-Bacterial AgentsBiocompatible MaterialsAnti-Bacterial AgentsBiocompatible MaterialsSilicon Compoundssilicon nitrideantibacterialimplantsmechanical propertiesosteogenesissilicon nitride

Identifiers

PMID35742996
PMCPMC9224221

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.