Evidence map›Paper›PMID 25222033›Full record

ReviewSensors (Basel, Switzerland)2014

Various on-chip sensors with microfluidics for biological applications.

Hun Lee, Linfeng Xu, Domin Koh, Nikhila Nyayapathi, Kwang W Oh

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
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  11. Toward improvedAPL bioengineering · 2021
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  17. Acoustic Actuation ofJournal of micromechanics and microengineering : structures, devices, and systems · 2018
    Article
  18. Article
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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.

Hun LeeDepartment of Electrical Engineering, University at Buffalo, State University of New York (SUNY at Buffalo), Buffalo, NY 14260, USA. hlee24@buffalo.edu.
Linfeng XuDepartment of Electrical Engineering, University at Buffalo, State University of New York (SUNY at Buffalo), Buffalo, NY 14260, USA. linfengx@buffalo.edu.
Domin KohDepartment of Electrical Engineering, University at Buffalo, State University of New York (SUNY at Buffalo), Buffalo, NY 14260, USA. dominkoh@buffalo.edu.
Nikhila NyayapathiDepartment of Electrical Engineering, University at Buffalo, State University of New York (SUNY at Buffalo), Buffalo, NY 14260, USA. nikhilan@buffalo.edu.
Kwang W OhDepartment of Electrical Engineering, University at Buffalo, State University of New York (SUNY at Buffalo), Buffalo, NY 14260, USA. kwangoh@buffalo.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we review recent advances in on-chip sensors integrated with microfluidics for biological applications. Since the 1990s, much research has concentrated on developing a sensing system using optical phenomena such as surface plasmon resonance (SPR) and surface-enhanced Raman scattering (SERS) to improve the sensitivity of the device. The sensing performance can be significantly enhanced with the use of microfluidic chips to provide effective liquid manipulation and greater flexibility. We describe an optical image sensor with a simpler platform for better performance over a larger field of view (FOV) and greater depth of field (DOF). As a new trend, we review consumer electronics such as smart phones, tablets, Google glasses, etc. which are being incorporated in point-of-care (POC) testing systems. In addition, we discuss in detail the current optical sensing system integrated with a microfluidic chip.

Indexed as

Computers, HandheldPoint-of-Care SystemsBiosensing TechniquesEquipment DesignMicrofluidic Analytical TechniquesSpectrum Analysis, RamanSurface Plasmon ResonanceTransducers

Identifiers

PMID25222033
PMCPMC4208211

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.