Evidence map›Paper›PMID 21573783›Full record

ReviewCellular and molecular life sciences : CMLS2011

Lipid complexes with cationic peptides and OAKs; their role in antimicrobial action and in the delivery of antimicrobial agents.

Raquel F Epand, Amram Mor, Richard M Epand

Abstract readReview
In one paragraph

Review in Cellular and molecular life sciences : CMLS, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Novel formulations for antimicrobial peptides.International journal of molecular sciences · 2014
    Review
  6. Review
  7. Review
  8. Article
  9. Article
  10. Review
  11. Designing antimicrobial peptides: form follows function.Nature reviews. Drug discovery · 2011
    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.

Raquel F EpandDepartment of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, L8N 3Z5, Canada. epand@mcmaster.ca
Amram Mor
Richard M Epand

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antimicrobial agents are toxic to bacteria by a variety of mechanisms. One mechanism that is very dependent on the lipid composition of the bacterial membrane is the clustering of anionic lipid by cationic antimicrobial agents. Certain species of oligo-acyl-lysine (OAK) antimicrobial agents are particularly effective in clustering anionic lipids in mixtures mimicking the composition of bacterial membranes. The clustering of anionic lipids by certain cationic antimicrobial agents contributes to the anti-bacterial action of these agents. Bacterial membrane lipids are a determining factor, resulting in some species of bacteria being more susceptible than others. In addition, lipids can be used to increase the effectiveness of antimicrobial agents when administered in vivo. Therefore, we review some of the structures in which lipid mixtures can assemble, to more effectively be utilized as antimicrobial delivery systems. We describe in more detail the complexes formed between mixtures of lipids mimicking bacterial membranes and an OAK and their usefulness in synergizing with antibiotics to overcome bacterial multidrug resistance.

Indexed as

Drug Delivery SystemsAnti-Bacterial AgentsAntimicrobial Cationic PeptidesBacteriaCell MembraneDrug Resistance, BacterialDrug Resistance, Multiple, BacterialHumansLiposomesLysineMembrane LipidsAnti-Bacterial AgentsAntimicrobial Cationic PeptidesLiposomesLysineMembrane Lipids

Identifiers

PMID21573783
PMCPMC11114973

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.