Evidence map›Paper›PMID 36005010›Full record

ArticleBiosensors2022

Data Processing of SPR Curve Data to Maximize the Extraction of Changes in Electrochemical SPR Measurements.

Suzuyo Inoue, Kenta Fukada, Katsuyoshi Hayashi, Michiko Seyama

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2022. 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
0.7field-weighted citation impact, top 37% 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, 10 citations in OpenAlex.

  1. Review
  2. 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

4 authors at 1 institution in 1 country.

Suzuyo InoueNTT Device Technology Laboratory, NTT Corporation, Atsugi 243-0198, Kanagawa, Japan.ORCID 0000-0002-6409-1373
Kenta FukadaNTT Device Technology Laboratory, NTT Corporation, Atsugi 243-0198, Kanagawa, Japan.
Katsuyoshi HayashiNTT Device Technology Laboratory, NTT Corporation, Atsugi 243-0198, Kanagawa, Japan.
Michiko SeyamaNTT Device Technology Laboratory, NTT Corporation, Atsugi 243-0198, Kanagawa, Japan.
NTT (Japan) · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We developed a novel measuring and data-processing method for performing electrochemical surface plasmon resonance (EC-SPR) on sensor surfaces for which detecting a specific SPR angle is difficult, such as a polymer having a non-uniform thickness with coloration. SPR measurements are used in medicine and basic research as an analytical method capable of molecular detection without labeling. However, SPR is not good for detecting small molecules with small refractive index changes. The proposed EC-SPR, which combines SPR measurements with an electrochemical reaction, makes it possible to measure small molecules without increasing the number of measurement steps. A drawback of EC-SPR is that it is difficult to detect a specific SPR angle on electron mediators, and it was found that it may not be possible to capture all the features produced. The novel method we describe here is different from the conventional one in which a specific SPR angle is obtained from an SPR curve; rather, it processes the SPR curve itself and can efficiently aggregate the feature displacements in the SPR curves that are dispersed through multiple angles. As an application, we used our method to detect small concentrations of H

Indexed as

Hydrogen PeroxideSurface Plasmon ResonanceRefractometryHydrogen Peroxideelectrochemical SPR (EC-SPR)glutamatesignal processingsurface plasmon resonance (SPR)

Identifiers

PMID36005010
PMCPMC9406148
OpenAlexW4290704618

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.