Evidence map›Paper›PMID 30513867›Full record

ArticleSensors (Basel, Switzerland)2018

Real-Time Monitoring of a Botulinum Neurotoxin Using All-Carbon Nanotube-Based Field-Effect Transistor Devices.

Nam Hee Lee, Seung-Hoon Nahm, Insung S Choi

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
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.

Nam Hee LeeDepartment of Chemistry, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea. n30237@kaist.ac.kr.
Seung-Hoon NahmEnergy Materials Metrology, Korea Research Institute of Standards and Science, 267 Gajeong-ro, Yuseong-gu, Daejeon 34113, Korea. shnahm@kriss.re.kr.
Insung S ChoiDepartment of Chemistry, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea. ischoi@kaist.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The possibility of exposure to botulinum neurotoxin (BoNT), a powerful and potential bioterrorism agent, is considered to be ever increasing. The current gold-standard assay, live-mouse lethality, exhibits high sensitivity but has limitations including long assay times, whereas other assays evince rapidity but lack factors such as real-time monitoring or portability. In this study, we aimed to devise a novel detection system that could detect BoNT at below-nanomolar concentrations in the form of a stretchable biosensor. We used a field-effect transistor with a p-type channel and electrodes, along with a channel comprising aligned carbon nanotube layers to detect the type E light chain of BoNT (BoNT/E-Lc). The detection of BoNT/E-Lc entailed observing the cleavage of a unique peptide and the specific bonding between BoNT/E-Lc and antibody BoNT/E-Lc (Anti-BoNT/E-Lc). The unique peptide was cleaved by 60 pM BoNT/E-Lc; notably, 52 fM BoNT/E-Lc was detected within 1 min in the device with the antibody in the bent state. These results demonstrated that an all-carbon nanotube-based device (all-CNT-based device) could be produced without a complicated fabrication process and could be used as a biosensor with high sensitivity, suggesting its potential development as a wearable BoNT biosensor.

Indexed as

Biosensing TechniquesAnimalsAntibodies, MonoclonalBioterrorismBotulinum ToxinsHumansMiceNanotubes, CarbonPeptidesAntibodies, MonoclonalBotulinum Toxinsbotulinum toxin type ENanotubes, CarbonPeptidesbotulinum neurotoxin (BoNT)carbon nanotube (CNT)field-effect transistor (FET)lateral flow immunoassaymicrofluidic devicestretchable sensor

Identifiers

PMID30513867
PMCPMC6308983

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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.