Evidence map›Paper›PMID 26909741›Full record

ArticleJournal of cellular physiology2016

Lipid-Targeting Peptide Probes for Extracellular Vesicles.

Aaron D Flynn, Hang Yin

Open access · greenAbstract read
In one paragraph

Article in Journal of cellular physiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

4 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
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 2 institutions in 1 country.

Aaron D FlynnDepartment of Molecular, Cellular, and Developmental Biology, University of Colorado, Boulder, Colorado.
Hang YinBioFrontiers Institute, University of Colorado, Boulder, Colorado.
University of Colorado Boulder · USUniversity of Colorado System · US

Funding

TRAINING IN SIGNAL TRANSDUCTION &CELL CYCLE REGULATIONT32GM008759 · NIGMS · UNIVERSITY OF COLORADO AT BOULDER · PI AHN, NATALIE G. · 2000 to 2020
$5.9M
Predoctoral Training Program in Signaling and Cellular Regulation INCLUDE Down Syndrome SupplementT32GM142607 · NIGMS · UNIVERSITY OF COLORADO · PI Sabrina Leigh Spencer, Tin Tin Su · 2021 to 2026
$3.6M
Dissecting Cell Signaling Mediated by Protein-Protein Interactions in MembranesR01GM103843 · NIGMS · UNIVERSITY OF COLORADO · PI YIN, HANG HUBERT · 2013 to 2016
$1.3M
NIGMS NIH HHS R01 GM103843NIGMS NIH HHS T32 GM008759NIGMS NIH HHS T32 GM142607
6 · The paper itself

Abstract

Extracellular vesicles released from cells are under intense investigation for their roles in cell-cell communication and cancer progression. However, individual vesicles have been difficult to probe as their small size renders them invisible by conventional light microscopy. However, as a consequence of their small size these vesicles possess highly curved lipid membranes that offer an unconventional target for curvature-sensing probes. In this article, we present a strategy for using peptide-based biosensors to detect highly curved membranes and the negatively charged membrane lipid phosphatidylserine, we delineate several assays used to validate curvature- and lipid-targeting mechanisms, and we explore potential applications in probing extracellular vesicles released from sources such as apoptotic cells, cancer cells, or activated platelets. J. Cell. Physiol. 231: 2327-2332, 2016. © 2016 Wiley Periodicals, Inc.

Indexed as

Cell MembraneExtracellular VesiclesLipidsModels, BiologicalMolecular ProbesPeptidesPhosphatidylserinesLipidsMolecular ProbesPeptidesPhosphatidylserines

Identifiers

PMID26909741
PMCPMC5243140
OpenAlexW2279871119

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.