Evidence map›Paper›PMID 26160546›Full record

ArticleThe Analyst2015

Optical detection enhancement in porous volumetric microfluidic capture elements using refractive index matching fluids.

M S Wiederoder, L Peterken, A X Lu, O D Rahmanian, S R Raghavan, D L DeVoe

Abstract read
In one paragraph

Article in The Analyst, 2015. 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. Biosensors Based on Inorganic Composite Fluorescent Hydrogels.Nanomaterials (Basel, Switzerland) · 2023
    Review
  2. Article
  3. 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

6 authors.

M S WiederoderDepartment of Bioengineering, University of Maryland, College Park, Maryland, USA.
L Peterken
A X Lu
O D Rahmanian
S R Raghavan
D L DeVoe

Funding

Integrated polymer microfluidic device for multiplex diagnosis of viral infectionR01AI096215 · NIAID · GENEVA FOUNDATION · PI ULRICH, ROBERT G. · 2011 to 2015
$4.4M
NIAID NIH HHS R01 AI096215NIAID NIH HHS R01AI096215
6 · The paper itself

Abstract

Porous volumetric capture elements in microfluidic sensors are advantageous compared to planar capture surfaces due to higher reaction site density and decreased diffusion lengths that can reduce detection limits and total assay time. However a mismatch in refractive indices between the capture matrix and fluid within the porous interstices results in scattering of incident, reflected, or emitted light, significantly reducing the signal for optical detection. Here we demonstrate that perfusion of an index-matching fluid within a porous matrix minimizes scattering, thus enhancing optical signal by enabling the entire capture element volume to be probed. Signal enhancement is demonstrated for both fluorescence and absorbance detection, using porous polymer monoliths in a silica capillary and packed beds of glass beads within thermoplastic microchannels, respectively. Fluorescence signal was improved by a factor of 3.5× when measuring emission from a fluorescent compound attached directly to the polymer monolith, and up to 2.6× for a rapid 10 min direct immunoassay. When combining index matching with a silver enhancement step, a detection limit of 0.1 ng mL(-1) human IgG and a 5 log dynamic range was achieved. The demonstrated technique provides a simple method for enhancing optical sensitivity for a wide range of assays, enabling the full benefits of porous detection elements in miniaturized analytical systems to be realized.

Indexed as

RefractometryHumansImmunoglobulin GLimit of DetectionMicrofluidicsPorosityImmunoglobulin G

Identifiers

PMID26160546
PMCPMC4516631

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.