Evidence map›Paper›PMID 37047330›Full record

ArticleInternational journal of molecular sciences2023

Innovative Computerized Dystrophin Quantification Method Based on Spectral Confocal Microscopy.

Anna Codina, Mònica Roldán, Daniel Natera-de Benito, Carlos Ortez, Robert Planas, Leslie Matalonga, Daniel Cuadras, Laura Carrera, Jesica Exposito, Jesus Marquez and 4 more

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 19% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

14 authors at 4 institutions in 1 country.

Anna CodinaNeuromuscular Unit, Hospital Sant Joan de Déu, Esplugues de Llobregat, 08950 Barcelona, Spain.ORCID 0000-0003-0673-9087
Mònica RoldánInstitut de Recerca Sant Joan de Déu, Esplugues de Llobregat, 08950 Barcelona, Spain.ORCID 0000-0002-9530-6234
Daniel Natera-de BenitoNeuromuscular Unit, Hospital Sant Joan de Déu, Esplugues de Llobregat, 08950 Barcelona, Spain.ORCID 0000-0001-7764-2085
Carlos OrtezNeuromuscular Unit, Hospital Sant Joan de Déu, Esplugues de Llobregat, 08950 Barcelona, Spain.
Robert PlanasInstitut de Robòtica i Informàtica Industrial, Technical University of Catalonia (UPC) and the Spanish Council for Scientific Research (CSIC) Llorens i Artigas 4-6, 08028 Barcelona, Spain.ORCID 0000-0001-7761-7795
Leslie MatalongaCNAG-CRG Centro Nacional de Análisis Genomico (CNAG)-Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Baldiri Reixac 4, 08028 Barcelona, Spain.
Daniel CuadrasInstitut de Recerca Sant Joan de Déu, Esplugues de Llobregat, 08950 Barcelona, Spain.ORCID 0000-0001-8780-1764
Laura CarreraNeuromuscular Unit, Hospital Sant Joan de Déu, Esplugues de Llobregat, 08950 Barcelona, Spain.
Jesica ExpositoNeuromuscular Unit, Hospital Sant Joan de Déu, Esplugues de Llobregat, 08950 Barcelona, Spain.ORCID 0000-0002-6233-823X
Jesus MarquezBiobank, Hospital Sant Joan de Déu, Esplugues de Llobregat, 08950 Barcelona, Spain.
Cecilia Jimenez-MallebreraNeuromuscular Unit, Hospital Sant Joan de Déu, Esplugues de Llobregat, 08950 Barcelona, Spain.ORCID 0000-0001-8203-7103
Josep M PortaInstitut de Robòtica i Informàtica Industrial, Technical University of Catalonia (UPC) and the Spanish Council for Scientific Research (CSIC) Llorens i Artigas 4-6, 08028 Barcelona, Spain.ORCID 0000-0002-5056-1717
Andres NascimentoNeuromuscular Unit, Hospital Sant Joan de Déu, Esplugues de Llobregat, 08950 Barcelona, Spain.
Cristina JouNeuromuscular Unit, Hospital Sant Joan de Déu, Esplugues de Llobregat, 08950 Barcelona, Spain.
Hospital Sant Joan de Déu Barcelona · ESInstitut de Robòtica i Informàtica Industrial · ESCentre for Genomic Regulation · ESSant Joan de Déu Research Foundation · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several clinical trials are working on drug development for Duchenne and Becker muscular dystrophy (DMD and BMD) treatment, and, since the expected increase in dystrophin is relatively subtle, high-sensitivity quantification methods are necessary. There is also a need to quantify dystrophin to reach a definitive diagnosis in individuals with mild BMD, and in female carriers. We developed a method for the quantification of dystrophin in DMD and BMD patients using spectral confocal microscopy. It offers the possibility to capture the whole emission spectrum for any antibody, ensuring the selection of the emission peak and allowing the detection of fluorescent emissions of very low intensities. Fluorescence was evaluated first on manually selected regions of interest (ROIs), proving the usefulness of the methodology. Later, ROI selection was automated to make it operator-independent. The proposed methodology correctly classified patients according to their diagnosis, detected even minimal traces of dystrophin, and the results obtained automatically were statistically comparable to the manual ones. Thus, spectral imaging could be implemented to measure dystrophin expression and it could pave the way for detailed analysis of how its expression relates to the clinical course. Studies could be further expanded to better understand the expression of dystrophin-associated protein complexes (DAPCs).

Indexed as

DystrophinMuscular Dystrophy, DuchenneFemaleHumansDystrophinBecker muscular dystrophyconfocal microscopyDuchenne muscular dystrophydystrophinfluorescence quantificationspectral imaging

Identifiers

PMID37047330
PMCPMC10094132
OpenAlexW4361213764

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.