Evidence map›Paper›PMID 37735238›Full record

ReviewThe Journal of membrane biology2023

Cationic Proteins Rich in Lysine Residue Trigger Formation of Non-bilayer Lipid Phases in Model and Biological Membranes: Biophysical Methods of Study.

Meiyi Li, Edward S Gasanoff

Abstract readReview
PubMed Publisher
In one paragraph

Review in The Journal of membrane biology, 2023. 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
3.1field-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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  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 2 countries.

Meiyi LiSTEM Research Centre, Science Department, Chaoyang Kaiwen Academy, Beijing, 100018, China.
Edward S GasanoffSTEM Research Centre, Science Department, Chaoyang Kaiwen Academy, Beijing, 100018, China. edward.gasanoff@cy.kaiwenacademy.cn.ORCID 0000-0002-5097-3973
Beijing Chaoyang Emergency Medical Center · CNLomonosov Moscow State University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cationic membrane-active toxins are the most abundant group of proteins in the venom of snakes and insects. Cationic proteins such as cobra venom cytotoxin and bee venom melittin are known for their pharmacological reactions including anticancer and antimicrobial effects which arise from the toxin-induced alteration in the dynamics and structure of plasma membranes and membranes of organelles. It has been established that these cationic toxins trigger the formation of non-bilayer lipid phase transitions in artificial and native mitochondrial membranes. Remarkably, the toxin-induced formation of non-bilayer lipid phase increases at certain conditions mitochondrial ATP synthase activity. This observation opens an intriguing avenue for using cationic toxins in the development of novel drugs for the treatment of cellular energy deficiency caused by aging and diseases. This observation also warrants a thorough investigation of the molecular mechanism(s) of lipid phase polymorphisms triggered by cationic proteins. This article presents a review on the application of powerful biophysical methods such as resonance spectroscopy (

Indexed as

CardiolipinsLysineAdenosine TriphosphateCell MembraneIonsLipid BilayersPhospholipidsAdenosine TriphosphateCardiolipinsIonsLipid BilayersLysinePhospholipids31P-, 1H-, 2H-NMRArtificial and biological membranesDifferential scanning microcalorimetryEPRLipid phase polymorphismLuminescence spectroscopy

Identifiers

PMID37735238
OpenAlexW4386916161

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.