Evidence map›Paper›PMID 32484329›Full record

ArticleAnalytical chemistry2020

Super-resolution Surface-Enhanced Raman Scattering Imaging of Single Particles in Cells.

Carlos Diego L de Albuquerque, Zachary D Schultz

Open access · greenAbstract read
In one paragraph

Article in Analytical chemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

19 citing papers in PubMed, 49 citations in OpenAlex.

  1. Review
  2. Article
  3. Recent Advancements in the SERS-Based Detection ofSensors (Basel, Switzerland) · 2026
    Review
  4. Article
  5. Article
  6. Review
  7. Review
  8. Review
  9. Review
  10. Raman Spectroscopy as a Tool to Study the Pathophysiology of Brain Diseases.International journal of molecular sciences · 2023
    Review
  11. Article
  12. Super-Resolution SERS Spectral Bioimaging.Proceedings of SPIE--the International Society for Optical Engineering · 2022
    Article
  13. Article
  14. Surface-enhanced Raman scattering: An emerging tool for sensing cellular function.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology · 2022
    Review
  15. Article
  16. Review
  17. Review
  18. Article
  19. 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

2 authors at 1 institution in 1 country.

Carlos Diego L de AlbuquerqueDepartment of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States.
Zachary D SchultzDepartment of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States.ORCID 0000-0003-1741-8801
The Ohio State University · US

Funding

Targeted TERS Investigations of Ligand-Receptor BindingR01GM109988 · NIGMS · UNIVERSITY OF NOTRE DAME · PI SCHULTZ, ZACHARY · 2015 to 2024
$3.2M
NIGMS NIH HHS R01 GM109988
6 · The paper itself

Abstract

The ability to locate and identify molecular interactions in cells has significant importance for understanding protein function and molecular biology. Functionalized metallic nanoparticles have been used as probes for protein tracking and drug delivery because of their ability to carry therapeutic agents and readily functionalized surfaces. In this work, we present a super-resolution surface-enhanced Raman scattering (SERS) approach for imaging and tracking membrane receptors interacting with peptide-functionalized gold nanostars (AuNS). The α

Indexed as

Amino Acid SequenceCell Line, TumorColonic NeoplasmsGoldHumansIntegrin alphaVbeta3Metal NanoparticlesPeptidesSpectrum Analysis, RamanGoldIntegrin alphaVbeta3Peptides

Identifiers

PMID32484329
PMCPMC7364441
OpenAlexW3030223725

What OpenQuestion holds

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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.