Evidence map›Paper›PMID 20302841›Full record

ReviewBiochimica et biophysica acta2010

GUV preparation and imaging: minimizing artifacts.

Nelson F Morales-Penningston, Jing Wu, Elaine R Farkas, Shih Lin Goh, Tatyana M Konyakhina, Judy Y Zheng, Watt W Webb, Gerald W Feigenson

Abstract readReview
In one paragraph

Review in Biochimica et biophysica acta, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed
6.2field-weighted citation impact, top 3% 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

82 citing papers in PubMed, 195 citations in OpenAlex.

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22 more citing papers are in PubMed but not listed here.

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

8 authors at 1 institution in 1 country.

Nelson F Morales-PenningstonDepartment of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853, USA.
Jing Wu
Elaine R Farkas
Shih Lin Goh
Tatyana M Konyakhina
Judy Y Zheng
Watt W Webb
Gerald W Feigenson
Cornell University · US

Funding

TRAINING IN MOLECULAR PHYSICS OF BIOLOGICAL SYSTEMST32GM008267 · NIGMS · CORNELL UNIVERSITY ITHACA · PI WANG, MICHELLE D. · 1988 to 2021
$9.6M
Biotechnology Resource Digital Electro-Optical ImagingP41EB001976 · NIBIB · CORNELL UNIVERSITY ITHACA · PI ZIPFEL, WARREN R · 2003 to 2010
$6.9M
Membrane Control of Protein-Protein Contact. Simulation Based on Phase DiagramsR01GM077198 · NIGMS · CORNELL UNIVERSITY · PI FEIGENSON, GERALD WILLIAM · 2007 to 2010
$1.6M
NIBIB NIH HHS P41 EB001976NIGMS NIH HHS 1-T32 GM 08267NIGMS NIH HHS R01 GM077198NIGMS NIH HHS T32 GM008267NIGMS NIH HHS T32 GM 08267
6 · The paper itself

Abstract

The components of biological membranes are present in a physical mixture. The nonrandom ways that the molecules of lipids and proteins mix together can strongly influence the association of proteins with each other, and the chemical reactions that occur in the membrane, or that are mediated by the membrane. A particular type of nonrandom mixing is the separation of compositionally distinct phases. Any such phase separation would result in preferential partition of some proteins and lipids between the coexisting phases, and thus would influence which proteins could be in contact, and whether a protein could find its target. Phase separation in a plasma membrane would also influence the binding of molecules from outside the cell to the membrane, including recognition proteins on viruses, bacteria, and other cells. The concept of these and other events associated with membrane phase separation are sometimes grouped together as the "raft model" of biological membranes. Several types of experiments are aimed at detecting and characterizing membrane phase separation. Visualizing phase separation has special value, both because the immiscibility is so decisively determined, and also because the type of phase can often be identified. The fluorescence microscope has proven uniquely useful for yielding images of separated phases, both in certain cell preparations, and especially in models of cell membranes. Here we discuss ways to prepare useful model membranes for image studies, and how to avoid some of the artifacts that can plague these studies.

Indexed as

Image Processing, Computer-AssistedModels, ChemicalBacteriaCell MembraneMembrane LipidsMicroscopy, FluorescenceUnilamellar LiposomesVirusesMembrane LipidsUnilamellar Liposomes

Identifiers

PMID20302841
PMCPMC2885611
OpenAlexW2059957397

What OpenQuestion holds

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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.