Evidence map›Paper›PMID 38882113›Full record

ReviewACS omega2024

Advancements and Perspectives in Optical Biosensors.

Shahriar Mostufa, Bahareh Rezaei, Stefano Ciannella, Parsa Yari, Jenifer Gómez-Pastora, Rui He, Kai Wu

Abstract readReview
In one paragraph

Review in ACS omega, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

35 citing papers in PubMed.

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  19. Materials and System Design for Self-Decision Bioelectronic Systems.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
  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

7 authors.

Shahriar MostufaDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, Texas 79409, United States.ORCID https://orcid.org/0000-0002-3326-4817
Bahareh RezaeiDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, Texas 79409, United States.
Stefano CiannellaDepartment of Chemical Engineering, Texas Tech University, Lubbock, Texas 79409, United States.
Parsa YariDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, Texas 79409, United States.
Jenifer Gómez-PastoraDepartment of Chemical Engineering, Texas Tech University, Lubbock, Texas 79409, United States.
Rui HeDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, Texas 79409, United States.ORCID https://orcid.org/0000-0002-2368-7269
Kai WuDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, Texas 79409, United States.ORCID https://orcid.org/0000-0002-9444-6112

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optical biosensors exhibit immense potential, offering extraordinary possibilities for biosensing due to their high sensitivity, reusability, and ultrafast sensing capabilities. This review provides a concise overview of optical biosensors, encompassing various platforms, operational mechanisms, and underlying physics, and it summarizes recent advancements in the field. Special attention is given to plasmonic biosensors and metasurface-based biosensors, emphasizing their significant performance in bioassays and, thus, their increasing attraction in biosensing research, positioning them as excellent candidates for lab-on-chip and point-of-care devices. For plasmonic biosensors, we emphasize surface plasmon resonance (SPR) and its subcategories, along with localized surface plasmon resonance (LSPR) devices and surface enhance Raman spectroscopy (SERS), highlighting their ability to perform diverse bioassays. Additionally, we discuss recently emerged metasurface-based biosensors. Toward the conclusion of this review, we address current challenges, opportunities, and prospects in optical biosensing. Considering the advancements and advantages presented by optical biosensors, it is foreseeable that they will become a robust and widespread platform for early disease diagnostics.

Identifiers

PMID38882113
PMCPMC11170745

What Socratic 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 Socratic graph.