Evidence map›Paper›PMID 33196026›Full record

ArticleiScience2020

Development and Application of High-Throughput Single Cell Lipid Profiling: A Study of

Stuart G Snowden, Hugo J R Fernandes, Josh Kent, Stefanie Foskolou, Peri Tate, Sarah F Field, Emmanouil Metzakopian, Albert Koulman

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
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

12 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. CRISPRi: a way to integrate iPSC-derived neuronal models.Biochemical Society transactions · 2024
    Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
  12. 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

8 authors.

Stuart G SnowdenCore Metabolomics and Lipidomics Laboratory, Metabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Level 4 Pathology, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK.
Hugo J R FernandesUK Dementia Research Institute, University of Cambridge, Department of Clinical Neurosciences, Cambridge Biomedical Campus, Cambridge CB2 0AH, UK.
Josh KentCore Metabolomics and Lipidomics Laboratory, Metabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Level 4 Pathology, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK.
Stefanie FoskolouUK Dementia Research Institute, University of Cambridge, Department of Clinical Neurosciences, Cambridge Biomedical Campus, Cambridge CB2 0AH, UK.
Peri TateDepartment of Biological Sciences, Royal Holloway University of London, Egham, Surrey Tw20 0EX, UK.
Sarah F FieldUK Dementia Research Institute, University of Cambridge, Department of Clinical Neurosciences, Cambridge Biomedical Campus, Cambridge CB2 0AH, UK.
Emmanouil MetzakopianUK Dementia Research Institute, University of Cambridge, Department of Clinical Neurosciences, Cambridge Biomedical Campus, Cambridge CB2 0AH, UK.
Albert KoulmanCore Metabolomics and Lipidomics Laboratory, Metabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Level 4 Pathology, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK.

Funding

Medical Research Council MC_UU_00014/5Medical Research Council MC_UU_12012/5
6 · The paper itself

Abstract

Advances in single cell genomics and transcriptomics have shown that at tissue level there is complex cellular heterogeneity. To understand the effect of this inter-cell heterogeneity on metabolism it is essential to develop a single cell lipid profiling approach that allows the measurement of lipids in large numbers of single cells from a population. This will provide a functional readout of cell activity and membrane structure. Using liquid extraction surface analysis coupled with high-resolution mass spectrometry we have developed a high-throughput method for untargeted single cell lipid profiling. This technological advance highlighted the importance of cellular heterogeneity in the functional metabolism of individual human dopamine neurons, suggesting that A53T alpha-synuclein (

Indexed as

Cellular NeuroscienceLipidomicsMetabolomicsMolecular Neuroscience

Identifiers

PMID33196026
PMCPMC7644967

What OpenQuestion holds

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Registered trials

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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.