Evidence map›Paper›PMID 39175406›Full record

ReviewACS applied bio materials2024

Shedding Light on Cellular Secrets: A Review of Advanced Optical Biosensing Techniques for Detecting Extracellular Vesicles with a Special Focus on Cancer Diagnosis.

Beyza Nur Küçük, Eylul Gulsen Yilmaz, Yusuf Aslan, Özgecan Erdem, Fatih Inci

Abstract readReview
In one paragraph

Review in ACS applied bio materials, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. 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

5 authors.

Beyza Nur KüçükUNAM─National Nanotechnology Research Center, Bilkent University, 06800 Ankara, Turkey.
Eylul Gulsen YilmazUNAM─National Nanotechnology Research Center, Bilkent University, 06800 Ankara, Turkey.
Yusuf AslanUNAM─National Nanotechnology Research Center, Bilkent University, 06800 Ankara, Turkey.
Özgecan ErdemUNAM─National Nanotechnology Research Center, Bilkent University, 06800 Ankara, Turkey.
Fatih InciUNAM─National Nanotechnology Research Center, Bilkent University, 06800 Ankara, Turkey.ORCID 0000-0002-9918-5038

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the relentless pursuit of innovative diagnostic tools for cancer, this review illuminates the cutting-edge realm of extracellular vesicles (EVs) and their biomolecular cargo detection through advanced optical biosensing techniques with a primary emphasis on their significance in cancer diagnosis. From the sophisticated domain of nanomaterials to the precision of surface plasmon resonance, we herein examine the diverse universe of optical biosensors, emphasizing their specified applications in cancer diagnosis. Exploring and understanding the details of EVs, we present innovative applications of enhancing and blending signals, going beyond the limits to sharpen our ability to sense and distinguish with greater sensitivity and specificity. Our special focus on cancer diagnosis underscores the transformative potential of optical biosensors in early detection and personalized medicine. This review aims to help guide researchers, clinicians, and enthusiasts into the captivating domain where light meets cellular secrets, creating innovative opportunities in cancer diagnostics.

Indexed as

Biosensing TechniquesExtracellular VesiclesNeoplasmsBiocompatible MaterialsHumansMaterials TestingOptical ImagingParticle SizeSurface Plasmon ResonanceBiocompatible Materialscancer diagnosisEV biomarkersEV isolation methodsextracellular vesicle (EV)optical biosensors

Identifiers

PMID39175406
PMCPMC11409220

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.