Evidence map›Paper›PMID 30680295›Full record

ArticleBio-protocol2019

Detection of Ligand-binding to Membrane Proteins by Capacitance Measurements.

Verena Burtscher, Matej Hotka, Walter Sandtner

Open access · bronzeAbstract read
In one paragraph

Article in Bio-protocol, 2019. 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
0.3field-weighted citation impact, top 40% 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, 5 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 1 institution in 1 country.

Verena Burtscher *Institute of Pharmacology and the Gaston H. Glock Research Laboratories for Exploratory Drug Development, Center of Physiology and Pharmacology, Medical University of Vienna, Vienna, Waehringerstrasse 13a, A-1090 Vienna, Austria.
Matej Hotka *Institute of Pharmacology and the Gaston H. Glock Research Laboratories for Exploratory Drug Development, Center of Physiology and Pharmacology, Medical University of Vienna, Vienna, Waehringerstrasse 13a, A-1090 Vienna, Austria.
Walter SandtnerInstitute of Pharmacology and the Gaston H. Glock Research Laboratories for Exploratory Drug Development, Center of Physiology and Pharmacology, Medical University of Vienna, Vienna, Waehringerstrasse 13a, A-1090 Vienna, Austria.
Medical University of Vienna · AT

Funding

Austrian Science Fund FWF P 28090
6 · The paper itself

Abstract

In multi-cellular organisms, cells communicate with each other utilizing chemical messengers. For many of these messenger molecules, the membrane is an insurmountable barrier. Yet, they act by binding to surface proteins often triggering a cascade of reactions inside the cell. Accordingly, studying ligand-receptor interactions at the cellular surface is key to understanding important aspects of membrane biology. However, despite a multitude of approaches to study membrane features, there is a need for developing techniques that can measure ligand binding with high temporal resolution and on a single cellular level. We recently developed a label-free approach to study ligand binding in real time. This methodology capitalizes on changes of the membrane's surface potential induced by the adsorption of a charged ligand. The resulting apparent alteration of membrane capacitance is measurable by capacitance recordings. Herein, we describe the implementation of the same using recordings obtained from HEK293 cells stably expressing the human serotonin transporter (SERT), which were challenged with the inhibitor cocaine.

Indexed as

Ligand bindingMembrane capacitanceSerotonin transporterSurface chargeWhole-cell patch-clamp technique

Identifiers

PMID30680295
PMCPMC6342252
OpenAlexW2977770604

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.