Evidence map›Paper›PMID 22250703›Full record

ArticleAnalytical chemistry2012

Modeling analyte transport and capture in porous bead sensors.

Jie Chou, Alexis Lennart, Jorge Wong, Mehnaaz F Ali, Pierre N Floriano, Nicolaos Christodoulides, James Camp, John T McDevitt

Open access · greenAbstract read
In one paragraph

Article in Analytical chemistry, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.1field-weighted citation impact, top 25% 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

7 citing papers in PubMed, 15 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Jie ChouDepartment of Bioengineering, Rice University, Houston, Texas 77005, USA.
Alexis Lennart
Jorge Wong
Mehnaaz F Ali
Pierre N Floriano
Nicolaos Christodoulides
James Camp
John T McDevitt
The University of Texas at Austin · USRice University · US

Funding

Effects of Oral Inflammation on the Levels of Salivary Biomarkers of AMIU01DE017793 · NIDCR · UNIVERSITY OF TEXAS AT AUSTIN · PI MCDEVITT, JOHN T · 2006 to 2012
$13.0M
NIDCR NIH HHS 3 U01 DE017793-02S1NIDCR NIH HHS 5 U01 DE017793-2NIDCR NIH HHS U01 DE017793
6 · The paper itself

Abstract

Porous agarose microbeads, with high surface to volume ratios and high binding densities, are attracting attention as highly sensitive, affordable sensor elements for a variety of high performance bioassays. While such polymer microspheres have been extensively studied and reported on previously and are now moving into real-world clinical practice, very little work has been completed to date to model the convection, diffusion, and binding kinetics of soluble reagents captured within such fibrous networks. Here, we report the development of a three-dimensional computational model and provide the initial evidence for its agreement with experimental outcomes derived from the capture and detection of representative protein and genetic biomolecules in 290 μm porous beads. We compare this model to antibody-mediated capture of C-reactive protein and bovine serum albumin, along with hybridization of oligonucleotide sequences to DNA probes. These results suggest that, due to the porous interior of the agarose bead, internal analyte transport is both diffusion and convection based, and regardless of the nature of analyte, the bead interiors reveal an interesting trickle of convection-driven internal flow. On the basis of this model, the internal to external flow rate ratio is found to be in the range of 1:170 to 1:3100 for beads with agarose concentration ranging from 0.5% to 8% for the sensor ensembles here studied. Further, both model and experimental evidence suggest that binding kinetics strongly affect analyte distribution of captured reagents within the beads. These findings reveal that high association constants create a steep moving boundary in which unbound analytes are held back at the periphery of the bead sensor. Low association constants create a more shallow moving boundary in which unbound analytes diffuse further into the bead before binding. These models agree with experimental evidence and thus serve as a new tool set for the study of bioagent transport processes within a new class of medical microdevices.

Indexed as

MicrospheresModels, TheoreticalAnimalsCattleC-Reactive ProteinDiffusionKineticsPorosityProtein BindingSepharoseSerum Albumin, BovineC-Reactive ProteinSepharoseSerum Albumin, Bovine

Identifiers

PMID22250703
PMCPMC3993991
OpenAlexW1978042550

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.