Evidence map›Paper›PMID 31705179›Full record

ArticleEuropean biophysics journal : EBJ2020

Distance measurements in the F

Markus Burger, Stephan Rein, Stefan Weber, Peter Gräber, Sylwia Kacprzak

Abstract read
PubMed Publisher
In one paragraph

Article in European biophysics journal : EBJ, 2020. 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
1.1field-weighted citation impact, top 15% 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, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Frontiers in bioengineering and biotechnology · 2021
    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

5 authors at 1 institution in 1 country.

Markus BurgerInstitut für Physikalische Chemie, Albert-Ludwigs-Universität Freiburg, Albertstraße 21, 79104, Freiburg, Germany.
Stephan ReinInstitut für Physikalische Chemie, Albert-Ludwigs-Universität Freiburg, Albertstraße 21, 79104, Freiburg, Germany.
Stefan WeberInstitut für Physikalische Chemie, Albert-Ludwigs-Universität Freiburg, Albertstraße 21, 79104, Freiburg, Germany.
Peter GräberInstitut für Physikalische Chemie, Albert-Ludwigs-Universität Freiburg, Albertstraße 21, 79104, Freiburg, Germany. peter.graeber@pc.uni-freiburg.de.ORCID http://orcid.org/0000-0003-1506-7497
Sylwia KacprzakInstitut für Physikalische Chemie, Albert-Ludwigs-Universität Freiburg, Albertstraße 21, 79104, Freiburg, Germany.
University of Freiburg · DE

Funding

Deutsche Forschungsgemeinschaft INST 39/928-1 FUGG
6 · The paper itself

Abstract

Fluorescence resonance energy transfer in single enzyme molecules (smFRET, single-molecule measurement) allows the measurement of multicomponent distance distributions in complex biomolecules similar to pulsed electron-electron double resonance (PELDOR, ensemble measurement). Both methods use reporter groups: FRET exploits the distance dependence of the electric interaction between electronic transition dipole moments of the attached fluorophores, whereas PELDOR spectroscopy uses the distance dependence of the interaction between the magnetic dipole moments of attached spin labels. Such labels can be incorporated easily to cysteine residues in the protein. Comparison of distance distributions obtained with both methods was carried out with the H

Indexed as

Amino Acid SubstitutionCysteineElectron Spin Resonance SpectroscopyEscherichia coli ProteinsFluorescence Resonance Energy TransferMolecular Dynamics SimulationProton-Translocating ATPasesCysteineEscherichia coli ProteinsProton-Translocating ATPasesDEERDistance measurementsEF0F1PELDORSingle-molecule spectroscopysmFRET

Identifiers

PMID31705179
OpenAlexW2987803745

What OpenQuestion holds

Textmetadata
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.