Evidence map›Paper›PMID 31341183›Full record

ArticleScientific reports2019

The MyoRobot technology discloses a premature biomechanical decay of skeletal muscle fiber bundles derived from R349P desminopathy mice.

Michael Haug, Charlotte Meyer, Barbara Reischl, Gerhard Prölß, Kristina Vetter, Julian Iberl, Stefanie Nübler, Sebastian Schürmann, Stefan J Rupitsch, Michael Heckel and 6 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 35% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

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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

16 authors at 4 institutions in 2 countries.

Michael HaugInstitute of Medical Biotechnology, Friedrich-Alexander-University (FAU) Erlangen-Nürnberg, Erlangen, Germany.
Charlotte MeyerInstitute of Medical Biotechnology, Friedrich-Alexander-University (FAU) Erlangen-Nürnberg, Erlangen, Germany.
Barbara ReischlInstitute of Medical Biotechnology, Friedrich-Alexander-University (FAU) Erlangen-Nürnberg, Erlangen, Germany.
Gerhard PrölßInstitute of Medical Biotechnology, Friedrich-Alexander-University (FAU) Erlangen-Nürnberg, Erlangen, Germany.
Kristina VetterInstitute of Medical Biotechnology, Friedrich-Alexander-University (FAU) Erlangen-Nürnberg, Erlangen, Germany.
Julian IberlInstitute of Medical Biotechnology, Friedrich-Alexander-University (FAU) Erlangen-Nürnberg, Erlangen, Germany.
Stefanie NüblerInstitute of Medical Biotechnology, Friedrich-Alexander-University (FAU) Erlangen-Nürnberg, Erlangen, Germany.
Sebastian SchürmannInstitute of Medical Biotechnology, Friedrich-Alexander-University (FAU) Erlangen-Nürnberg, Erlangen, Germany.
Stefan J RupitschChair of Sensor Technology, FAU Erlangen-Nürnberg, Erlangen, Germany.
Michael HeckelInstitute of Multi Scale Simulation of Particulate Systems, FAU Erlangen-Nürnberg, Erlangen, Germany.
Thorsten PöschelInstitute of Multi Scale Simulation of Particulate Systems, FAU Erlangen-Nürnberg, Erlangen, Germany.
Lilli WinterInstitute of Neuropathology, University Hospital Erlangen, Erlangen, Germany.
Harald HerrmannInstitute of Neuropathology, University Hospital Erlangen, Erlangen, Germany.
Christoph S ClemenDepartment of Neurology, Heimer Institute for Muscle Research, University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany.
Rolf SchröderInstitute of Neuropathology, University Hospital Erlangen, Erlangen, Germany.
Oliver FriedrichInstitute of Medical Biotechnology, Friedrich-Alexander-University (FAU) Erlangen-Nürnberg, Erlangen, Germany. oliver.friedrich@fau.de.
Friedrich-Alexander-Universität Erlangen-Nürnberg · DEUniversitätsklinikum Erlangen · DEBG University Hospital Bergmannsheil Bochum · DEUNSW Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mutations in the Des gene coding for the muscle-specific intermediate filament protein desmin lead to myopathies and cardiomyopathies. We previously generated a R349P desmin knock-in mouse strain as a patient-mimicking model for the corresponding most frequent human desmin mutation R350P. Since nothing is known about the age-dependent changes in the biomechanics of affected muscles, we investigated the passive and active biomechanics of small fiber bundles from young (17-23 wks), adult (25-45 wks) and aged (>60 wks) heterozygous and homozygous R349P desmin knock-in mice in comparison to wild-type littermates. We used a novel automated biomechatronics platform, the MyoRobot, to perform coherent quantitative recordings of passive (resting length-tension curves, visco-elasticity) and active (caffeine-induced force transients, pCa-force, 'slack-tests') parameters to determine age-dependent effects of the R349P desmin mutation in slow-twitch soleus and fast-twitch extensor digitorum longus small fiber bundles. We demonstrate that active force properties are not affected by this mutation while passive steady-state elasticity is vastly altered in R349P desmin fiber bundles compatible with a pre-aged phenotype exhibiting stiffer muscle preparations. Visco-elasticity on the other hand, was not altered. Our study represents the first systematic age-related characterization of small muscle fiber bundle preparation biomechanics in conjunction with inherited desminopathy.

Indexed as

Age FactorsAnimalsAutomation, LaboratoryBiomechanical PhenomenaBiotechnologyCardiomyopathiesDesminFemaleGene Knock-In TechniquesMaleMiceMice, TransgenicMuscle Fibers, Fast-TwitchMuscle Fibers, SkeletalMuscle Fibers, Slow-TwitchMuscular DystrophiesDesmin

Identifiers

PMID31341183
PMCPMC6656739
OpenAlexW2964259230

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.