Evidence map›Paper›PMID 36222833›Full record

ArticleACS nano2022

DNA-Based Optical Quantification of Ion Transport across Giant Vesicles.

Marcus Fletcher, Jinbo Zhu, Roger Rubio-Sánchez, Sarah E Sandler, Kareem Al Nahas, Lorenzo Di Michele, Ulrich F Keyser, Ran Tivony

Abstract read
In one paragraph

Article in ACS nano, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Emerging Designs and Applications for Biomembrane Biosensors.Annual review of analytical chemistry (Palo Alto, Calif.) · 2024
    Review
  8. 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

8 authors.

Marcus FletcherCavendish Laboratory, University of Cambridge, J.J. Thomson Avenue, CambridgeCB3 0HE, U.K.ORCID 0000-0003-3036-1168
Jinbo ZhuCavendish Laboratory, University of Cambridge, J.J. Thomson Avenue, CambridgeCB3 0HE, U.K.ORCID 0000-0003-4935-825X
Roger Rubio-SánchezDepartment of Chemistry, Molecular Sciences Research Hub, Imperial College London, LondonW12 0BZ, U.K.ORCID 0000-0001-5574-5809
Sarah E SandlerCavendish Laboratory, University of Cambridge, J.J. Thomson Avenue, CambridgeCB3 0HE, U.K.ORCID 0000-0001-9689-8684
Kareem Al NahasCavendish Laboratory, University of Cambridge, J.J. Thomson Avenue, CambridgeCB3 0HE, U.K.ORCID 0000-0003-4568-5894
Lorenzo Di MicheleDepartment of Chemistry, Molecular Sciences Research Hub, Imperial College London, LondonW12 0BZ, U.K.ORCID 0000-0002-1458-9747
Ulrich F KeyserCavendish Laboratory, University of Cambridge, J.J. Thomson Avenue, CambridgeCB3 0HE, U.K.ORCID 0000-0003-3188-5414
Ran TivonyCavendish Laboratory, University of Cambridge, J.J. Thomson Avenue, CambridgeCB3 0HE, U.K.ORCID 0000-0003-0331-9538

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate measurements of ion permeability through cellular membranes remains challenging due to the lack of suitable ion-selective probes. Here we use giant unilamellar vesicles (GUVs) as membrane models for the direct visualization of mass translocation at the single-vesicle level. Ion transport is indicated with a fluorescently adjustable DNA-based sensor that accurately detects sub-millimolar variations in K

Indexed as

GramicidinUnilamellar LiposomesDNAIon ChannelsIonsIon TransportLipid BilayersOctanolsPotassiumProtonsDNAGramicidinIon ChannelsIonsLipid BilayersOctanolsPotassiumProtonsUnilamellar Liposomesgiant unilamellar vesiclesG-quadruplexion channelsion sensorion transportmicrofluidics

Identifiers

PMID36222833
PMCPMC9620405

What OpenQuestion holds

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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.