Evidence map›Paper›PMID 39871866›Full record

ArticleIn vitro models2022

Surface-modified WE43 magnesium alloys for reduced degradation and superior biocompatibility.

Vignesh K Manivasagam, Magesh Sankar, Caterina Bartomeu Garcia, Jithin Vishnu, Kaushik Chatterjee, Satyam Suwas, Geetha Manivasagam, Thomas J Webster

Abstract read
In one paragraph

Article in In vitro models, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

8 authors.

Vignesh K ManivasagamDepartment of Chemical Engineering, Northeastern University, Boston, MA USA.
Magesh SankarCentre for Biomaterials Cellular and Molecular Theranostics, CBCMT, Vellore Institute of Technology, Vellore, India.
Caterina Bartomeu GarciaDepartment of Chemical Engineering, Northeastern University, Boston, MA USA.
Jithin VishnuCentre for Biomaterials Cellular and Molecular Theranostics, CBCMT, Vellore Institute of Technology, Vellore, India.
Kaushik ChatterjeeDepartment of Materials Engineering, Indian Institute of Science, Bangalore, 560012 India.
Satyam SuwasDepartment of Materials Engineering, Indian Institute of Science, Bangalore, 560012 India.
Geetha ManivasagamCentre for Biomaterials Cellular and Molecular Theranostics, CBCMT, Vellore Institute of Technology, Vellore, India.ORCID 0000-0003-3326-3176
Thomas J WebsterDepartment of Chemical Engineering, Northeastern University, Boston, MA USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

WE43 magnesium alloy was modified using surface mechanical attrition treatment (SMAT) and characterized to evaluate the influence of sub-micron surface modification on degradation rate and in vitro behavior. Modified surface was characterized for wettability, hardness, roughness, degradation rate, in vitro biocompatibility, and antibacterial activity as per the ASTM standards. The treated substrates proved to have a significant decrease in the degradation profile by creating micro pockets of oxidation channels and reducing the total delamination in comparison to the conventional heterogeneous oxide layer formed on the untreated substrate surface. Biocompatibility studies showed that this modification did not induce any toxicity to human fetal osteoblast (hFOB) cells as demonstrated by cell proliferation and enhanced calcium deposition. In fact, results showed that between the 7

Indexed as

AntibacterialCalcium depositionIn vitro studiesMagnesiumSurface mechanical attrition treatmentSurface modificationWE43

Identifiers

PMID39871866
PMCPMC11756484

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.