Evidence map›Paper›PMID 35514435›Full record

ReviewMaterials today. Bio2022

Plasmonic nanosensors for point-of-care biomarker detection.

Congran Jin, Ziqian Wu, John H Molinski, Junhu Zhou, Yundong Ren, John X J Zhang

Abstract readReview
In one paragraph

Review in Materials today. Bio, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Review
  15. Review
  16. Article
  17. Review
  18. Review
  19. Article
  20. 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

6 authors.

Congran JinThayer School of Engineering, Dartmouth College, NH, USA.
Ziqian WuThayer School of Engineering, Dartmouth College, NH, USA.
John H MolinskiThayer School of Engineering, Dartmouth College, NH, USA.
Junhu ZhouThayer School of Engineering, Dartmouth College, NH, USA.
Yundong RenThayer School of Engineering, Dartmouth College, NH, USA.
John X J ZhangThayer School of Engineering, Dartmouth College, NH, USA.

Funding

Implantable Cardiac Power Generation Using Flexible 3D Porous Thin FilmsR01HL137157 · NHLBI · DARTMOUTH COLLEGE · PI ZHANG, XIAOJING · 2016 to 2020
$2.2M
NHLBI NIH HHS R01 HL137157
6 · The paper itself

Abstract

Advancement of materials along with their fascinating properties play increasingly important role in facilitating the rapid progress in medicine. An excellent example is the recent development of biosensors based on nanomaterials that induce surface plasmon effect for screening biomarkers of various diseases ranging from cancer to Covid-19. The recent global pandemic re-confirmed the trend of real-time diagnosis in public health to be in point-of-care (POC) settings that can screen interested biomarkers at home, or literally anywhere else, at any time. Plasmonic biosensors, thanks to its versatile designs and extraordinary sensitivities, can be scaled into small and portable devices for POC diagnostic tools. In the meantime, efforts are being made to speed up, simplify and lower the cost of the signal readout process including converting the conventional heavy laboratory instruments into lightweight handheld devices. This article reviews the recent progress on the design of plasmonic nanomaterial-based biosensors for biomarker detection with a perspective of POC applications. After briefly introducing the plasmonic detection working mechanisms and devices, the selected highlights in the field focusing on the technology's design including nanomaterials development, structure assembly, and target applications are presented and analyzed. In parallel, discussions on the sensor's current or potential applicability in POC diagnosis are provided. Finally, challenges and opportunities in plasmonic biosensor for biomarker detection, such as the current Covid-19 pandemic and its testing using plasmonic biosensor and incorporation of machine learning algorithms are discussed.

Indexed as

BiomarkerBiosensorCovid-19PlasmonicPoint-of-care

Identifiers

PMID35514435
PMCPMC9062760

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.