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Cited by 446

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Phospholipid spherules (liposomes) as a model for biological membranes

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Sessa, Grazia, Weissmann, Gerald·1968·Journal of Lipid Research

Abstract

This review describes the properties of artificial spherules composed of phospholipids and various long-chain anions or cations. The lipids, which are in the liquid-crystal state, trap aqueous solutes such as cations, anions, glucose, or glycine in aqueous compartments between a series of lipid bilayers. The diffusion of these solutes from the spherules can be studied in the same way that diffusion across biological membranes is studied. The spherules exhibit many of the properties of natural membrane-bounded structures: they are capable of ion-discrimination, osmotic swelling, and response to a variety of physiologic and pharmacologic agents. These agents (steroids, drugs, toxins, antibiotics) accelerate or retard diffusion of ions or molecules from the spherules in a way that qualitatively mimics their action on erythrocytes, lysosomes, or mitochondria. Thus the spherules constitute a valuable model system with which to study the properties of biological membranes that may be dependent on their lipid components.

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Crossref · 10.1016/s0022-2275(20)43097-4

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Metadata

Authors
Sessa, G., & Weissmann, G.
Venue
Journal of Lipid Research
Publisher
Elsevier BV
Published
1968-05
Volume
9
Issue
3
Pages
310-318
ISSN
0022-2275 (ISSN-L)
OpenAlex
W1925296672
Cited by
446
References
1
FWCI
5.86
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Phospholipid spherules (liposomes) as a model for biological membranes. https://app.cochat.ai/papers/10.1016/s0022-2275(20)43097-4
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Sessa, G., & Weissmann, G. (1968). Phospholipid spherules (liposomes) as a model for biological membranes. Journal of Lipid Research. https://doi.org/10.1016/s0022-2275(20)43097-4

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.