Evidence map›Paper›PMID 30420636›Full record

ArticleScientific reports2018

An Algorithm for Enhancing the Image Contrast of Electron Tomography.

Hao Wu, Xiaobo Zhai, Dongsheng Lei, Jianfang Liu, Yadong Yu, Rongfang Bie, Gang Ren

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Ab-initio contrast estimation and denoising of cryo-EM images.Computer methods and programs in biomedicine · 2022
    Article
  8. Article
  9. Review
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  11. 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.

Hao WuCollege of Information Science and Technology, Beijing Normal University, Beijing, China. 11132015314@bnu.edu.cn.
Xiaobo ZhaiThe Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
Dongsheng LeiThe Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
Jianfang LiuThe Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
Yadong YuThe Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
Rongfang BieCollege of Information Science and Technology, Beijing Normal University, Beijing, China. rfbie@bnu.edu.cn.
Gang RenThe Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA. gren@lbl.gov.

Funding

Structure-Function Relationship Studies of the Plasma Lipid Transfer Proteins CETP and PLTPR01HL115153 · NHLBI · UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB · PI REN, GANG · 2012 to 2021
$3.9M
Lipoprotein Structure and Function by Individual Particle Electron TomographyR01GM104427 · NIGMS · UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB · PI REN, GANG · 2013 to 2016
$1.3M
DOE | SC | Basic Energy Sciences (BES) AC02-05CH11231NHLBI NIH HHS R01 HL115153NIGMS NIH HHS R01 GM104427U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI) R01HL115153U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) R01GM104427
6 · The paper itself

Abstract

Three-dimensional (3D) reconstruction of a single protein molecule is essential for understanding the relationship between the structural dynamics and functions of the protein. Electron tomography (ET) provides a tool for imaging an individual particle of protein from a series of tilted angles. Individual-particle electron tomography (IPET) provides an approach for reconstructing a 3D density map from a single targeted protein particle (without averaging from different particles of this type of protein), in which the target particle was imaged from a series of tilting angles. However, owing to radiation damage limitations, low-dose images (high noise, and low image contrast) are often challenging to be aligned for 3D reconstruction at intermediate resolution (1-3 nm). Here, we propose a computational method to enhance the image contrast, without increasing any experimental dose, for IPET 3D reconstruction. Using an edge-preserving smoothing-based multi-scale image decomposition algorithm, this method can detect the object against a high-noise background and enhance the object image contrast without increasing the noise level or significantly decreasing the image resolution. The method was validated by using both negative staining (NS) ET and cryo-ET images. The successful 3D reconstruction of a small molecule (<100 kDa) indicated that this method can be used as a supporting tool to current ET 3D reconstruction methods for studying protein dynamics via structure determination from each individual particle of the same type of protein.

Indexed as

AlgorithmsCryoelectron MicroscopyElectron Microscope TomographyImage Processing, Computer-AssistedImaging, Three-Dimensional

Identifiers

PMID30420636
PMCPMC6232092

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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.