Evidence map›Paper›PMID 30834502›Full record

ReviewBiophysical reviews2019

Advances in domain and subunit localization technology for electron microscopy.

Zuben P Brown, Junichi Takagi

Abstract readReview
In one paragraph

Review in Biophysical reviews, 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
–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

2 citing papers in PubMed.

  1. The Structure and Mechanism of Drug Transporters.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
  2. 2019-A year in Biophysical Reviews.Biophysical reviews · 2019
    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

2 authors.

Zuben P BrownDepartment of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, USA. zb2218@cumc.columbia.edu.ORCID http://orcid.org/0000-0002-9846-2822
Junichi TakagiLaboratory of Protein Synthesis and Expression, Institute for Protein Research, Osaka University, Osaka, Japan.

Funding

STRUCTURE ANALYSIS OF MACROMOLECULAR ASSEMBLIESR01GM029169 · NIGMS · WADSWORTH CENTER · PI FRANK, JOACHIM · 1985 to 2019
$6.1M
National Institutes of Health Joachim FrankNIGMS NIH HHS R01 GM029169
6 · The paper itself

Abstract

The award of the 2017 Nobel Prize in chemistry, 'for developing cryo-electron microscopy for the high-resolution structure determination of biomolecules in solution', was recognition that this method, and electron microscopy more generally, represent powerful techniques in the scientific armamentarium for atomic level structural assessment. Technical advances in equipment, software, and sample preparation, have allowed for high-resolution structural determination of a range of complex biological machinery such that the position of individual atoms within these mega-structures can be determined. However, not all targets are amenable to attaining such high-resolution structures and some may only be resolved at so-called intermediate resolutions. In these cases, other tools are needed to correctly characterize the domain or subunit orientation and architecture. In this review, we will outline various methods that can provide additional information to help understand the macro-level organization of proteins/biomolecular complexes when high-resolution structural description is not available. In particular, we will discuss the recent development and use of a novel protein purification approach, known as the the PA tag/NZ-1 antibody system, which provides numberous beneficial properties, when used in electron microscopy experimentation.

Indexed as

Domain mappingElectron microscopyNZ-1PA tag

Identifiers

PMID30834502
PMCPMC6441409

What OpenQuestion holds

Textmetadata
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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.