Evidence map›Paper›PMID 33013841›Full record

ArticleFrontiers in immunology2020

Toward a Membrane-Centric Biology.

Yan Shi, Hefei Ruan

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2020. 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
0.4field-weighted citation impact, top 40% 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, 7 citations in OpenAlex.

  1. Review
  2. Article
  3. Membrane Rafts: Portals for Viral Entry.Frontiers in microbiology · 2021
    Review
  4. Frontiers in physiology · 2021
    Article
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.

Yan ShiTsinghua-Peking University Joint Center for Life Sciences, Tsinghua University, Beijing, China.
Hefei RuanTsinghua-Peking University Joint Center for Life Sciences, Tsinghua University, Beijing, China.
Tsinghua University · CNUniversity of Calgary · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With advancements of modern biophysical tools and superresolution imaging, cell biology is entering a new phase of research with technological power fitting for membrane dynamics analyses. However, our current knowledge base of cellular signaling events is mostly built on a network of protein interactions, which is incompatible with the essential roles of membrane activities in those events. The lack of a theoretical platform is rendering biophysical analyses of membrane biology supplementary to the protein-centric paradigm. We hypothesize a framework of signaling events mediated by lipid dynamics and argue that this is the evolutionarily obligatory developmental path of cellular complexity buildup. In this framework, receptors are the late comers, integrating into the pre-existing membrane based signaling events using their lipid interface as the point of entry. We further suggest that the reason for cell surface receptors to remain silent at the resting state is via the suppression effects of their surrounding lipids. The avoidance of such a suppression, via ligand binding or lipid domain disruption, enables the receptors to autonomously integrate themselves into the preexisting networks of signaling cascades.

Indexed as

Signal TransductionAnimalsCell MembraneHumansLigandsMembrane LipidsMembrane ProteinsReceptors, Cell SurfaceLigandsMembrane LipidsMembrane ProteinsReceptors, Cell Surfaceevolutionlipid interactionlipid raftsplasma membranereceptor activation mechanismreceptor ligand model

Identifiers

PMID33013841
PMCPMC7509146
OpenAlexW3083785934

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.