Evidence map›Paper›PMID 33160114›Full record

ArticleActa biomaterialia2021

Effect of the silica nanoparticle size on the osteoinduction of biomineralized silk-silica nanocomposites.

Zaira Martín-Moldes, Diego López Barreiro, Markus J Buehler, David L Kaplan

Open access · greenAbstract read
In one paragraph

Article in Acta biomaterialia, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

11 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
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  5. Materials today. Bio · 2024
    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

4 authors at 2 institutions in 1 country.

Zaira Martín-MoldesDepartment of Biomedical Engineering, Tufts University, 4 Colby Street, Medford, MA 02155, USA; Laboratory for Atomistic and Molecular Mechanics (LAMM), Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, 1-290, Cambridge, MA 02139, USA.
Diego López BarreiroLaboratory for Atomistic and Molecular Mechanics (LAMM), Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, 1-290, Cambridge, MA 02139, USA.
Markus J BuehlerLaboratory for Atomistic and Molecular Mechanics (LAMM), Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, 1-290, Cambridge, MA 02139, USA.
David L KaplanDepartment of Biomedical Engineering, Tufts University, 4 Colby Street, Medford, MA 02155, USA. Electronic address: david.kaplan@tufts.edu.
Massachusetts Institute of Technology · USTufts University · US

Funding

Models to Predict Protein Biomaterial PerformanceU01EB014976 · NIBIB · TUFTS UNIVERSITY MEDFORD · PI BUEHLER, MARKUS J., KAPLAN, DAVID L. · 2012 to 2020
$5.2M
Degradable orthopedic hardwareR01AR068048 · NIAMS · TUFTS UNIVERSITY MEDFORD · PI KAPLAN, DAVID L., LIN, SAMUEL J · 2015 to 2020
$2.0M
NIAMS NIH HHS R01 AR068048NIBIB NIH HHS U01 EB014976
6 · The paper itself

Abstract

Understanding the properties and behavior of biomineralized protein-based materials at the organic-inorganic interface is critical to optimize the performance of such materials for biomedical applications. To that end, this work investigates biomineralized protein-based films with applications for bone regeneration. These films were generated using a chimeric protein fusing the consensus repeat derived from the spider Nephila clavipes major ampullate dragline silk with the silica-promoting peptide R5 derived from the Cylindrotheca fusiformis silaffin gene. The effect of pH on the size of silica nanoparticles during their biomineralization on silk films was investigated, as well as the potential impact of nanoparticle size on the differentiation of human mesenchymal stem cells (hMSCs) into osteoblasts. To that end, induction of the integrin αV subunit and the osteogenic markers Runx2 transcription factor and Bone Sialoprotein (BSP) was followed. The results indicated that pH values of 7-8 during biomineralization maximized the coverage of the film surface by silica nanoparticles yielding nanoparticles ranging 200-500 nm and showing enhanced osteoinduction in gene expression analysis. Lower (3-5) or high (10) pH values led to lower biomineralization and poor coverage of the protein surfaces, showing reduced osteoinduction. Molecular dynamics simulations confirmed the activation of the integrin αVβ3 in contact with silica nanoparticles, correlating with the experimental data on the induction of osteogenic markers. This work sheds light on the optimal conditions for the development of fit-for-purpose biomaterial designs for bone regeneration, while the agreement between experimental and computational results shows the potential of computational methods to predict the expression of osteogenic markers for biomaterials. STATEMENT OF SIGNIFICANCE: The ability of biomineralized materials to induce hMSCs differentiation for bone tissue regeneration applications was analyzed. Biomaterials were created using a recombinant protein formed by the consensus repeat derived from the spider Nephila clavipes major ampullate dragline silk and the silica-promoting peptide R5 derived from the Cylindrotheca fusiformis silaffin gene. A combination of computational and experimental techniques revealed the optimal conditions for the synthesis of biomineralized silk-silica films with enhanced expression of markers related to bone regeneration.

Indexed as

NanocompositesNanoparticlesSpidersAnimalsHumansSilicon DioxideSilkSilicon DioxideSilkBiomaterialBiosilicificationMultiscale modelingSilica nanoparticle sizesSpider silk fusion

Identifiers

PMID33160114
PMCPMC7796966
OpenAlexW3095740664

What OpenQuestion holds

Textmetadata
LicenceTDM
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.