Evidence map›Paper›PMID 25538800›Full record

ArticleBiomicrofluidics2014

Quantifying spatio-temporal dynamics of biomarker pre-concentration and depletion in microfluidic systems by intensity threshold analysis.

Ali Rohani, Walter Varhue, Yi-Hsuan Su, Nathan S Swami

Open access · bronzeAbstract read
In one paragraph

Article in Biomicrofluidics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.5field-weighted citation impact, top 12% 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

12 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. RapidACS infectious diseases · 2020
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  4. Single-cell electro-phenotyping for rapid assessment ofSensors and actuators. B, Chemical · 2018
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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

4 authors at 1 institution in 1 country.

Ali RohaniElectrical and Computer Engineering, University of Virginia , Charlottesville, Virginia 22904, USA.
Walter VarhueElectrical and Computer Engineering, University of Virginia , Charlottesville, Virginia 22904, USA.
Yi-Hsuan SuElectrical and Computer Engineering, University of Virginia , Charlottesville, Virginia 22904, USA.
Nathan S SwamiElectrical and Computer Engineering, University of Virginia , Charlottesville, Virginia 22904, USA.
University of Virginia · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microfluidic systems are commonly applied towards pre-concentration of biomarkers for enhancing detection sensitivity. Quantitative information on the spatial and temporal dynamics of pre-concentration, such as its position, extent, and time evolution are essential towards sensor design for coupling pre-concentration to detection. Current quantification methodologies are based on the time evolution of fluorescence signals from biomarkers within a statically defined region of interest, which does not offer information on the spatial dynamics of pre-concentration and leads to significant errors when the pre-concentration zone is delocalized or exhibits wide variations in size, shape, and position over time under the force field. We present a dynamic methodology for quantifying the region of interest by using a statistical description of particle distribution across the device geometry to determine the intensity thresholds for particle pre-concentration. This method is applied to study the delocalized pre-concentration dynamics under an electrokinetic force balance driven by negative dielectrophoresis, for aligning the pre-concentration and detection regions of neuropeptide Y, and for quantifying the polarizability dispersion of silica nano-colloids with frequency of the force field. We envision the application of this automated methodology on data from 2D images and 3D Z-stacks for quantifying pre-concentration dynamics over delocalized regions as a function of the force field.

Identifiers

PMID25538800
PMCPMC4222295
OpenAlexW2002357422

What OpenQuestion holds

Textmetadata
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Registered trials

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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.