Evidence map›Paper›PMID 42181696›Full record

ArticleMolecular therapy. Nucleic acids2026

AAV9-mediated targeting of natural antisense transcript as a novel treatment for Dravet syndrome.

Juan Antinao Diaz, Ellie M Chilcott, Amanda Almacellas Barbanoj, Anna Keegan, Sonam Gurung, Valda Pauzuolyte, Zak Waddington, Maria Kyriacou, Amy McTague, J Helen Cross and 4 more

Abstract read
In one paragraph

Article in Molecular therapy. Nucleic acids, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Juan Antinao DiazEGA Institute for Women's Health, University College London, London WC1E 6HX, UK.
Ellie M ChilcottEGA Institute for Women's Health, University College London, London WC1E 6HX, UK.
Amanda Almacellas BarbanojResearch Department of Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK.
Anna KeeganEGA Institute for Women's Health, University College London, London WC1E 6HX, UK.
Sonam GurungUCL Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK.
Valda PauzuolyteEGA Institute for Women's Health, University College London, London WC1E 6HX, UK.
Zak WaddingtonEGA Institute for Women's Health, University College London, London WC1E 6HX, UK.
Maria KyriacouEGA Institute for Women's Health, University College London, London WC1E 6HX, UK.
Amy McTagueUCL Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK.
J Helen CrossUCL Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK.
Stephanie SchorgeDivision of Biosciences, Medical Science Building, University College London, London WC1E 6BT, UK.
Gabriele LignaniResearch Department of Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK.
Simon N WaddingtonEGA Institute for Women's Health, University College London, London WC1E 6HX, UK.
Rajvinder KardaEGA Institute for Women's Health, University College London, London WC1E 6HX, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dravet syndrome (DS) is a severe childhood developmental and epileptic encephalopathy. Symptoms usually manifest in the first year of life and include prolonged severe seizures, developmental delay, severe intellectual disability, and increased mortality. Approximately, 90% of patients carry a heterozygous loss-of-function mutation in

Indexed as

AAVdelivery strategiesDravet syndromegene therapyMTnatural antisense transcriptNaV1.1pre-clinicalSMEI

Identifiers

PMID42181696
PMCPMC13196359

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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.