Evidence map›Paper›PMID 24655505›Full record

ArticleBiophysical journal2014

Depolarization Laplace transform analysis of exchangeable hyperpolarized ¹²⁹Xe for detecting ordering phases and cholesterol content of biomembrane models.

Matthias Schnurr, Christopher Witte, Leif Schröder

Abstract read
In one paragraph

Article in Biophysical journal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Molecular Sensing with Host Systems for HyperpolarizedMolecules (Basel, Switzerland) · 2020
    Review
  2. Nanoparticle-Based Contrast Agents forContrast media & molecular imaging · 2019
    Review
  3. NMR Hyperpolarization Techniques of Gases.Chemistry (Weinheim an der Bergstrasse, Germany) · 2017
    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

3 authors.

Matthias SchnurrEuropean Research Council Project BiosensorImaging, Leibniz-Institut für Molekulare Pharmakologie (FMP), Berlin, Germany.
Christopher WitteEuropean Research Council Project BiosensorImaging, Leibniz-Institut für Molekulare Pharmakologie (FMP), Berlin, Germany.
Leif SchröderEuropean Research Council Project BiosensorImaging, Leibniz-Institut für Molekulare Pharmakologie (FMP), Berlin, Germany. Electronic address: lschroeder@fmp-berlin.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a highly sensitive nuclear-magnetic resonance technique to study membrane dynamics that combines the temporary encapsulation of spin-hyperpolarized xenon ((129)Xe) atoms in cryptophane-A-monoacid (CrAma) and their indirect detection through chemical exchange saturation transfer. Radiofrequency-labeled Xe@CrAma complexes exhibit characteristic differences in chemical exchange saturation transfer-driven depolarization when interacting with binary membrane models composed of different molecular ratios of DPPC (1,2-dipalmitoyl-sn-glycero-3-phosphocholine) and POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine). The method is also applied to mixtures of cholesterol and POPC. The existence of domains that fluctuate in cluster size in DPPC/POPC models at a high (75-98%) DPPC content induces up to a fivefold increase in spin depolarization time τ at 297 K. In POPC/cholesterol model membranes, the parameter τ depends linearly on the cholesterol content at 310 K and allows us to determine the cholesterol content with an accuracy of at least 5%.

Indexed as

CholesterolLipid BilayersMagnetic Resonance SpectroscopyPolycyclic CompoundsXenon IsotopesCholesterolcryptophane ALipid BilayersPolycyclic CompoundsXenon Isotopes

Identifiers

PMID24655505
PMCPMC3984979

What OpenQuestion holds

Textmetadata
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.