Evidence map›Paper›PMID 35936408›Full record

ArticleACS omega2022

Unbiased Data Analysis for the Parameterization of Fast Translocation Events through Nanopores.

Florian L R Lucas, Kherim Willems, Matthijs J Tadema, Katarzyna M Tych, Giovanni Maglia, Carsten Wloka

Abstract read
In one paragraph

Article in ACS omega, 2022. 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. Article
  2. Article
  3. 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

6 authors.

Florian L R LucasGroningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, 9712 CP Groningen, The Netherlands.ORCID https://orcid.org/0000-0002-9561-5408
Kherim WillemsIMEC, Kapeldreef 75, B-3001 Leuven, Belgium.ORCID https://orcid.org/0000-0003-1341-1581
Matthijs J TademaGroningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, 9712 CP Groningen, The Netherlands.
Katarzyna M TychGroningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, 9712 CP Groningen, The Netherlands.
Giovanni MagliaGroningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, 9712 CP Groningen, The Netherlands.ORCID https://orcid.org/0000-0003-2784-0811
Carsten WlokaGroningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, 9712 CP Groningen, The Netherlands.ORCID https://orcid.org/0000-0003-0487-3311

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-molecule nanopore electrophysiology is an emerging technique for the detection of analytes in aqueous solutions with high sensitivity. These detectors have proven applicable for the enzyme-assisted sequencing of oligonucleotides. There has recently been an increased interest in the use of nanopores for the fingerprinting of peptides and proteins, referred to as single-molecule nanopore spectrometry. However, the analysis of the resulting electrophysiology traces remains complicated due to the fast unassisted translocation of such analytes, usually in the order of micro- to milliseconds, and the small ion current signal produced (in the picoampere range). Here, we present the application of a generalized normal distribution function (gNDF) for the characterization of short-lived ion current signals (blockades). We show that the gNDF can be used to determine if the observed blockades have adequate time to reach their maximum current plateau while also providing a description of each blockade based on the open pore current (

Identifiers

PMID35936408
PMCPMC9352258

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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.