Evidence map›Paper›PMID 21993141›Full record

ArticleBiosensors & bioelectronics2011

Rapidly optimizing an aptamer based BoNT sensor by feedback system control (FSC) scheme.

Fang Wei, Bin Bai, Chih-Ming Ho

Abstract read
In one paragraph

Article in Biosensors & bioelectronics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

2 citing papers in PubMed, 30 citations in OpenAlex.

  1. Article
  2. 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

3 authors at 2 institutions in 2 countries.

Fang WeiSchool of Dentistry, Dental Research Institute, University of California, Los Angeles, CA, USA.
Bin Bai
Chih-Ming Ho
University of California, Los Angeles · USPeking University · CN

Funding

The Center for Systemic Control of Cyto-NetworksPN2EY018228 · NEI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI HO, CHIH-MING · 2006 to 2010
$8.2M
NEI NIH HHS PN2 EY018228
6 · The paper itself

Abstract

The sensitivity and detection time of an aptamer based biosensor for detecting botulinum neurotoxin (BoNT) depend upon the formation of proper tertiary architecture of aptamer, which closely correlates with the combinatorial effects of multiple types of ions and their concentrations presented in the buffer. Finding the optimal conditions for four different ions at 12 different concentrations, 20,736 possible combinations, by brute force is an extremely laborious and time-consuming task. Here, we introduce a feedback system control (FSC) scheme that can rapidly identify the best combination of components to form the optimal aptamer structure binding to a target molecule. In this study, rapid identification of optimized ionic combinations for electrochemical aptasensor of BoNT type A (BoNT/A) detection has been achieved. Only about 10 iterations with about 50 tests in each iteration are needed to identify the optimal ionic concentration out of the 20,736 possibilities. The most exciting finding was that a very short detection time and high sensitivity could be achieved with the optimized combinational ion buffer. Only a 5-min detection time, compared with hours or even days, was needed for aptamer-based BoNT/A detection with a limit of detection of 40 pg/ml. The methodologies described here can be applied to other multi-parameter chemical systems, which should significantly improve the rate of parameter optimization.

Indexed as

AlgorithmsAptamers, NucleotideBiosensing TechniquesBotulinum Toxins, Type AEquipment DesignEquipment Failure AnalysisFeedbackReproducibility of ResultsSensitivity and SpecificityAptamers, NucleotideBotulinum Toxins, Type A

Identifiers

PMID21993141
PMCPMC3210382
OpenAlexW2039904359

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.