Evidence map›Paper›PMID 32842724›Full record

ArticleACS sensors2021

Charge-Sensitive Optical Detection of Small Molecule Binding Kinetics in Normal Ionic Strength Buffer.

Runli Liang, Guangzhong Ma, Wenwen Jing, Yan Wang, Yunze Yang, Nongjian Tao, Shaopeng Wang

Open access · greenAbstract read
In one paragraph

Article in ACS sensors, 2021. 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
0.2field-weighted citation impact, top 47% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  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

7 authors at 1 institution in 1 country.

Runli Liang
Yunze Yang
Nongjian Tao
BioElectronics (United States) · US

Funding

Charge sensitive optical detection for high-throughput study of small moleculesR33CA202834 · NCI · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI TAO, NONGJIAN · 2016 to 2018
$1.1M
NCI NIH HHS R33 CA202834
6 · The paper itself

Abstract

Most label-free detection technologies detect the masses of molecules, and their sensitivities thus decrease with molecular weight, making it challenging to detect small molecules. To address this need, we have developed a charge-sensitive optical detection (CSOD) technique, which detects the charge rather than the mass of a molecule with an optical fiber. However, the effective charge of a molecule decreases with the buffer ionic strength. For this reason, the previous CSOD works with diluted buffers, which could affect the measured molecular binding kinetics. Here, we show a technique capable of detecting molecular binding kinetics in normal ionic strength buffers. An H-shaped sample well was developed to increase the current density at the sensing area to compensate the signal loss due to ionic screening at normal ionic strength buffer, while keeping the current density low at the electrodes to minimize the electrode reaction. In addition, agarose gels were used to cover the electrodes to prevent electrode reaction generated bubbles from entering the sensing area. With this new design, we have measured the binding kinetics between G-protein-coupled receptors (GPCRs) and their small molecule ligands in normal buffer. We found that the affinities measured in normal buffer are stronger than those measured in diluted buffer, likely due to the stronger electrostatic repulsion force between the same charged ligands and receptors in the diluted buffer.

Indexed as

KineticsIonsLigandsOsmolar ConcentrationStatic ElectricityIonsLigandsbinding kineticscharge sensitive optical detectionG-protein-coupled receptorslabel-freenormal ionic strength buffersmall moleculevirion display

Identifiers

PMID32842724
PMCPMC7914145
OpenAlexW3081183520

What OpenQuestion holds

Textmetadata
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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.