Evidence map›Paper›PMID 23049161›Full record

ArticleMRS bulletin2012

Development of Electron Energy Loss Spectroscopy in the Biological Sciences.

M A Aronova, R D Leapman

Open access · greenAbstract read
In one paragraph

Article in MRS bulletin, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

29 citing papers in PubMed, 107 citations in OpenAlex.

  1. Article
  2. Quantification ofMedicinal research reviews · 2026
    Review
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  9. Review
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  11. Review
  12. Charting the molecular landscape of the cell.Structure (London, England : 1993) · 2023
    Review
  13. A spatially resolved elemental nanodomain organization within acidocalcisomes inProceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
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  20. 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 at 1 institution in 1 country.

M A AronovaNational Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD 20892, USA.
R D Leapman
National Institutes of Health · US

Funding

Energy-Filtered Electron TomographyZIAEB000037 · NIBIB · NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING · PI LEAPMAN, RICHARD · 2009 to 2022
$4.2M
Localization of Secretion-Related Proteins in Pancreatic Islets of LangerhansZ01EB000044 · NIBIB · NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING · PI LEAPMAN, RICHARD · 2007 to 2008
$40k
Intramural NIH HHS Z01 EB000044Intramural NIH HHS ZIA EB000037
6 · The paper itself

Abstract

The high sensitivity of electron energy loss spectroscopy (EELS) for detecting light elements at the nanoscale makes it a valuable technique for application to biological systems. In particular, EELS provides quantitative information about elemental distributions within subcellular compartments, specific atoms bound to individual macromolecular assemblies, and the composition of bionanoparticles. The EELS data can be acquired either in the fixed beam energy-filtered transmission electron microscope (EFTEM) or in the scanning transmission electron microscope (STEM), and recent progress in the development of both approaches has greatly expanded the range of applications for EELS analysis. Near single atom sensitivity is now achievable for certain elements bound to isolated macromolecules, and it becomes possible to obtain three-dimensional compositional distributions from sectioned cells through EFTEM tomography.

Identifiers

PMID23049161
PMCPMC3465455
OpenAlexW2092390379

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.