Evidence map›Paper›PMID 35615304›Full record

ArticleJournal of materials research2022

Engineered 2D materials for optical bioimaging and path toward therapy and tissue engineering.

Jeewan C Ranasinghe, Arpit Jain, Wenjing Wu, Kunyan Zhang, Ziyang Wang, Shengxi Huang

Abstract read
In one paragraph

Article in Journal of materials research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Lateral heterostructures of WSScientific reports · 2024
    Article
  5. Review
  6. Review
  7. Article
  8. 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

6 authors.

Jeewan C RanasingheDepartment of Electrical Engineering, The Pennsylvania State University, University Park, PA 16802 USA.
Arpit JainDepartment of Materials Science and Engineering, The Pennsylvania State University, University Park, PA 16802 USA.
Wenjing WuDepartment of Electrical Engineering, The Pennsylvania State University, University Park, PA 16802 USA.
Kunyan ZhangDepartment of Electrical Engineering, The Pennsylvania State University, University Park, PA 16802 USA.
Ziyang WangDepartment of Electrical Engineering, The Pennsylvania State University, University Park, PA 16802 USA.
Shengxi HuangDepartment of Electrical Engineering, The Pennsylvania State University, University Park, PA 16802 USA.ORCID 0000-0002-3618-9074

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Two-dimensional (2D) layered materials as a new class of nanomaterial are characterized by a list of exotic properties. These layered materials are investigated widely in several biomedical applications. A comprehensive understanding of the state-of-the-art developments of 2D materials designed for multiple nanoplatforms will aid researchers in various fields to broaden the scope of biomedical applications. Here, we review the advances in 2D material-based biomedical applications. First, we introduce the classification and properties of 2D materials. Next, we summarize surface and structural engineering methods of 2D materials where we discuss surface functionalization, defect, and strain engineering, and creating heterostructures based on layered materials for biomedical applications. After that, we discuss different biomedical applications. Then, we briefly introduced the emerging role of machine learning (ML) as a technological advancement to boost biomedical platforms. Finally, the current challenges, opportunities, and prospects on 2D materials in biomedical applications are discussed. Graphical abstract:

Indexed as

2D materialsBiomedical applicationsMachine learningSurface engineering

Identifiers

PMID35615304
PMCPMC9122553

What OpenQuestion holds

Textmetadata
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.