Evidence map›Paper›PMID 39473793›Full record

ArticleRSC advances2024

Titania nanotubes modified with copper enhance osteogenic differentiation of adipose derived stem cells.

Aniruddha Vijay Savargaonkar, Liszt Coutinho Madruga, Amit H Munshi, Ketul C Popat

Abstract read
In one paragraph

Article in RSC advances, 2024. 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. Review
  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

4 authors.

Aniruddha Vijay SavargaonkarDepartment of Mechanical Engineering, Colorado State University Fort Collins CO 80523 USA ketul.popat@colostate.edu.ORCID https://orcid.org/0009-0005-2680-2233
Liszt Coutinho MadrugaDepartment of Bioengineering, George Mason University Fairfax VA 22030 USA kpopat@gmu.edu.
Amit H MunshiDepartment of Mechanical Engineering, Colorado State University Fort Collins CO 80523 USA ketul.popat@colostate.edu.ORCID https://orcid.org/0000-0002-9949-9600
Ketul C PopatDepartment of Mechanical Engineering, Colorado State University Fort Collins CO 80523 USA ketul.popat@colostate.edu.ORCID https://orcid.org/0000-0002-2417-7789

Funding

Nanostructured Surfaces With Improved HemocompatibilityR21EB033511 · NIBIB · GEORGE MASON UNIVERSITY · PI POPAT, KETUL CHANDRAKANT · 2022 to 2023
$410k
NIBIB NIH HHS R21 EB033511
6 · The paper itself

Abstract

To achieve long term success of orthopedic implants, it is critical to have a successful integration of bone and implant material. To accomplish this, various surface modifications have been investigated in research. Even though titania nanotubes and copper have individually demonstrated successful stem cell adhesion, proliferation and differentiation, these modifications have not yet been investigated together. In this study, we fabricated copper-modified titania nanotubes and evaluated the adhesion, proliferation and osteogenic differentiation of adipose derived stem cells on these surfaces. Implant surfaces also have to interact with blood after insertion in the body. Several studies have shown the importance of blood clots on material surfaces and their influence in differentiation of cells. Hence, blood clotting properties of modified surfaces were also investigated through whole blood clotting, and platelet adhesion and activation. The copper-modified titania nanotube surfaces demonstrated increased differentiation of adipose derived stem cells towards osteogenic lineage as well as enhanced blood clotting properties, thus they can be used as a potential surface for orthopedic implants.

Identifiers

PMID39473793
PMCPMC11520316

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.