Evidence map›Paper›PMID 31153590›Full record

ArticleBiophysical journal2019

Quantitative Mapping of Triacylglycerol Chain Length and Saturation Using Broadband CARS Microscopy.

Alexandra Paul, Yujen Wang, Cecilia Brännmark, Sachin Kumar, Mischa Bonn, Sapun H Parekh

Open access · bronzeAbstract read
In one paragraph

Article in Biophysical journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.1field-weighted citation impact, top 11% 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

5 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
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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

6 authors at 3 institutions in 3 countries.

Alexandra PaulDivision of Chemical Biology, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden; Department of Molecular Spectroscopy, Max Planck Institute for Polymer Research, Mainz, Germany.
Yujen WangDepartment of Molecular Spectroscopy, Max Planck Institute for Polymer Research, Mainz, Germany; Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas.
Cecilia BrännmarkInstitute of Neuroscience and Physiology, Unit of Metabolic Physiology, Department of Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.
Sachin KumarDepartment of Molecular Spectroscopy, Max Planck Institute for Polymer Research, Mainz, Germany; Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas.
Mischa BonnDepartment of Molecular Spectroscopy, Max Planck Institute for Polymer Research, Mainz, Germany.
Sapun H ParekhDepartment of Molecular Spectroscopy, Max Planck Institute for Polymer Research, Mainz, Germany; Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas. Electronic address: sparekh@utexas.edu.
Max Planck Institute for Polymer Research · DEThe University of Texas at Austin · USUniversity of Gothenburg · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lipid droplets (LDs), present in many cell types, are highly dynamic organelles that store neutral lipids, primarily triacylglycerols (TAGs). With the discovery of new LD functions (e.g., in immune response, protein clearage, and occurrence with disease), new methods to study LD chemical composition in situ are necessary. We present an approach for in situ, quantitative TAG analysis using label-free, coherent Raman microscopy that allows deciphering LD TAG composition in different biochemically complex samples with submicrometer spatial resolution. Employing a set of standard TAGs, we generate a spectral training matrix capturing the variation caused in Raman-like spectra by TAG backbone, chain length, and number of double bonds per chain, as well as the presence of proteins or other diluting molecules. Comparing our fitting approach to gas chromatography measurements for mixtures of standard TAGs and food oils, we find the root mean-square error for the prediction of TAG chemistry to be 0.69 CH

Indexed as

MicroscopySpectrum Analysis, RamanAnimalsCell LineHumansLipid DropletsMiceTriglyceridesTriglycerides

Identifiers

PMID31153590
PMCPMC6588730
OpenAlexW2951491183

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.