Evidence map›Paper›PMID 37431772›Full record

ReviewThe journal of physical chemistry. B2023

Raman Imaging Reveals Insights into Membrane Phase Biophysics in Cells.

Yihui Shen, Lu Wei, Wei Min

Open access · greenAbstract readReview
In one paragraph

Review in The journal of physical chemistry. B, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.8field-weighted citation impact, top 13% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. 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 at 3 institutions in 1 country.

Yihui ShenChemistry and Lewis Sigler Institute of Genomics, Princeton University, Princeton, New Jersey 08540, United States.
Lu WeiDivision of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, United States.ORCID 0000-0001-9170-2283
Wei MinDepartment of Chemistry, Columbia University, New York, New York 10027, United States.ORCID 0000-0003-2570-3557
California Institute of Technology · USColumbia University · USPrinceton University · US

Funding

High-resolution volumetric imaging of metabolic activity in tissues and its application to tumor metabolismR01EB029523 · NIBIB · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI MIN, WEI · 2020 to 2023
$1.6M
NIBIB NIH HHS R01 EB029523
6 · The paper itself

Abstract

Cellular membranes are essential components of all living organisms. They are composed of a complex mixture of lipids with diverse chemical structures and crucial biological functions. The dynamic and heterogeneous nature of cellular membranes presents a challenge for studying their biophysical properties and organization in vivo. Raman imaging, particularly coherent Raman scattering techniques such as stimulated Raman scattering (SRS) microscopy, have emerged as powerful tools for studying cellular membranes with high spatial and temporal resolution and minimal perturbation. In this Review, we discuss the scientific importance and technical challenges of characterizing membrane composition in cellular contexts and how the advances of Raman imaging can provide unique insights into membrane phase behavior and organization. We also highlight recent applications of Raman imaging in studying cellular membranes and implications in diseases. In particular, the discovery of phase separation and a solid-phase intracellular membrane on endoplasmic reticulum is reviewed in detail, shedding light on the biology of lipotoxicity.

Indexed as

Intracellular MembranesMicroscopyCell MembraneMembranesSpectrum Analysis, Raman

Identifiers

PMID37431772
PMCPMC11209838
OpenAlexW4383872742

What OpenQuestion holds

Textmetadata
LicenceTDM
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.