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Curvature, Lipid Packing, and Electrostatics of Membrane Organelles: Defining Cellular Territories in Determining Specificity
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Whereas some rare lipids contribute to the identity of cell organelles, we focus on the abundant lipids that form the matrix of organelle membranes. Observations using bioprobes and peripheral proteins, notably sensors of membrane curvature, support the prediction that the cell contains two broad membrane territories: the territory of loose lipid packing, where cytosolic proteins take advantage of membrane defects, and the territory of electrostatics, where proteins are attracted by negatively charged lipids. The contrasting features of these territories provide specificity for reactions occurring along the secretory pathway, on the plasma membrane, and also on lipid droplets and autophagosomes.
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Self-citation
Metadata
- Authors
- Bigay, J., & Antonny, B.
- Venue
- Developmental Cell
- Publisher
- Elsevier BV
- Published
- 2012-11
- Volume
- 23
- Issue
- 5
- Pages
- 886-895
- ISSN
- 1534-5807 (ISSN-L)
- OpenAlex
- W2046189032
- Cited by
- 567
- References
- 96
- FWCI
- 9.64
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.