Evidence map›Paper›PMID 33067560›Full record

ArticleCommunications biology2020

Quantification of clinically applicable stimulation parameters for precision near-organ neuromodulation of human splenic nerves.

Isha Gupta, Antonino M Cassará, Ilya Tarotin, Matteo Donega, Jason A Miranda, David M Sokal, Sebastien Ouchouche, Wesley Dopson, Paul Matteucci, Esra Neufeld and 10 more

Open access · goldAbstract read
In one paragraph

Article in Communications biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

22 citing papers in PubMed, 27 citations in OpenAlex.

  1. Review
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  6. Multi-Organ Denervation: The Past, Present and Future.Journal of clinical medicine · 2025
    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

20 authors at 6 institutions in 3 countries.

Isha GuptaGalvani Bioelectronics, Gunnels Wood Road, Stevenage, SG1 2NY, UK. Isha.8.gupta@galvani.bio.ORCID 0000-0003-3766-0857
Antonino M CassaráFoundation for Research on Information Technologies in Society (IT'IS), Zeughausstrasse 43, 8004, Zurich, Switzerland.ORCID 0000-0003-3375-7440
Ilya TarotinGalvani Bioelectronics, Gunnels Wood Road, Stevenage, SG1 2NY, UK.
Matteo DonegaGalvani Bioelectronics, Gunnels Wood Road, Stevenage, SG1 2NY, UK.
Jason A MirandaGalvani Bioelectronics, Gunnels Wood Road, Stevenage, SG1 2NY, UK.ORCID 0000-0002-1459-2022
David M SokalGalvani Bioelectronics, Gunnels Wood Road, Stevenage, SG1 2NY, UK.ORCID 0000-0003-3150-7990
Sebastien OuchoucheGalvani Bioelectronics, Gunnels Wood Road, Stevenage, SG1 2NY, UK.
Wesley DopsonGalvani Bioelectronics, Gunnels Wood Road, Stevenage, SG1 2NY, UK.
Paul MatteucciGalvani Bioelectronics, Gunnels Wood Road, Stevenage, SG1 2NY, UK.
Esra NeufeldFoundation for Research on Information Technologies in Society (IT'IS), Zeughausstrasse 43, 8004, Zurich, Switzerland.ORCID 0000-0001-5528-6147
Matthew A SchieferSimNeurix, LLC, Gainesville, FL, USA.
Alison RowlesNon Clinical Safety, Research and Development, GlaxoSmithKline, Park Road, Ware, SG12 0DP, UK.
Paul McGillBioimaging, GlaxoSmithKline, Park Road, Ware, SG12 0DP, UK.
Justin PerkinsThe Royal Veterinary College, Hawkshead Lane, North Mymms, Hatfield, AL9 7TA, UK.
Nikola DolezalovaDepartment of Surgery, University of Cambridge, and NIHR Cambridge Biomedical Research Centre, Cambridge, CB2 0QQ, UK.ORCID 0000-0002-9665-1275
Kourosh Saeb-ParsyDepartment of Surgery, University of Cambridge, and NIHR Cambridge Biomedical Research Centre, Cambridge, CB2 0QQ, UK.ORCID 0000-0002-0633-3696
Niels KusterFoundation for Research on Information Technologies in Society (IT'IS), Zeughausstrasse 43, 8004, Zurich, Switzerland.
Refet Firat YaziciogluGalvani Bioelectronics, Gunnels Wood Road, Stevenage, SG1 2NY, UK.
Jason WitheringtonGalvani Bioelectronics, Gunnels Wood Road, Stevenage, SG1 2NY, UK.
Daniel J ChewGalvani Bioelectronics, Gunnels Wood Road, Stevenage, SG1 2NY, UK. Daniel.j.chew@galvani.bio.ORCID 0000-0002-4937-4797
BioElectronics (United States) · USFoundation for Research on Information Technologies in Society · CHGlaxoSmithKline (United Kingdom) · GBUniversity of Cambridge · GBETH Zurich · CHRoyal Veterinary College · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neuromodulation is a new therapeutic pathway to treat inflammatory conditions by modulating the electrical signalling pattern of the autonomic connections to the spleen. However, targeting this sub-division of the nervous system presents specific challenges in translating nerve stimulation parameters. Firstly, autonomic nerves are typically embedded non-uniformly among visceral and connective tissues with complex interfacing requirements. Secondly, these nerves contain axons with populations of varying phenotypes leading to complexities for axon engagement and activation. Thirdly, clinical translational of methodologies attained using preclinical animal models are limited due to heterogeneity of the intra- and inter-species comparative anatomy and physiology. Here we demonstrate how this can be accomplished by the use of in silico modelling of target anatomy, and validation of these estimations through ex vivo human tissue electrophysiology studies. Neuroelectrical models are developed to address the challenges in translation of parameters, which provides strong input criteria for device design and dose selection prior to a first-in-human trial.

Indexed as

Electric StimulationAnimalsElectric Stimulation TherapyElectrophysiological PhenomenaHumansSpleenSwine

Identifiers

PMID33067560
PMCPMC7568572
OpenAlexW3093070218

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.