Proof of concept for multiple nerve transfers to a single target muscle

  1. Matthias Luft
  2. Johanna Klepetko
  3. Silvia Muceli
  4. Jaime Ibáñez
  5. Vlad Tereshenko
  6. Christopher Festin
  7. Gregor Laengle
  8. Olga Politikou
  9. Udo Maierhofer
  10. Dario Farina
  11. Oskar C Aszmann
  12. Konstantin Davide Bergmeister  Is a corresponding author
  1. Medical University of Vienna, Austria
  2. Chalmers University of Technology, Sweden
  3. Imperial College London, United Kingdom
  4. Karl Landsteiner University of Health Sciences, Austria

Abstract

Surgical nerve transfers are used to efficiently treat peripheral nerve injuries, neuromas, phantom limb pain or improve bionic prosthetic control. Commonly, one donor nerve is transferred to one target muscle. However, the transfer of multiple nerves onto a single target muscle may increase the number of muscle signals for myoelectric prosthetic control and facilitate the treatment of multiple neuromas. Currently, no experimental models are available for multiple nerve transfers to a common target muscle in the upper extremity. This study describes a novel experimental model to investigate the neurophysiological effects of peripheral double nerve transfers. For this purpose, we developed a forelimb model to enable tension-free transfer of one or two donor nerves in the upper extremity. Anatomic dissections were performed to design the double nerve transfer model (n=8). In 62 male Sprague-Dawley rats the ulnar nerve of the antebrachium alone (n=30) or together with the anterior interosseus nerve (n=32) was transferred to reinnervate the long head of the biceps brachii. Before neurotization, the motor branch to the biceps’ long head was transected at the motor entry point and resected up to its original branch to prevent auto-reinnervation. In all animals, coaptation of both nerves to the motor entry point could be performed tension-free. Mean duration of the procedure was 49 ± 13 min for the single nerve transfer and 78 ± 20 min for the double nerve transfer. Twelve weeks after surgery, muscle response to neurotomy, behavioral testing, retrograde labeling and structural analyses were performed to assess reinnervation. These analyses indicated that all nerves successfully reinnervated the target muscle. No aberrant reinnervation was observed by the originally innervating nerve. Our observations suggest a minimal burden for the animal with no signs of functional deficit in daily activities or auto-mutilation in both procedures. Furthermore, standard neurophysiological analyses for nerve and muscle regeneration were applicable. This newly developed nerve transfer model allows for the reliable and standardized investigation of neural and functional changes following the transfer of multiple donor nerves to one target muscle.

Data availability

Muscle mass data have been deposited in Dryad under the DOI: https://doi.org/10.5061/dryad.3j9kd51jb.Retrograde labeling data has been deposited in Dryad under the DOI: https://doi.org/10.5061/dryad.6q573n60c.

The following data sets were generated

Article and author information

Author details

  1. Matthias Luft

    Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9161-4125
  2. Johanna Klepetko

    Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
  3. Silvia Muceli

    Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0310-1021
  4. Jaime Ibáñez

    Department of Bioengineering, Imperial College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  5. Vlad Tereshenko

    Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7761-5191
  6. Christopher Festin

    Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
  7. Gregor Laengle

    Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1011-3482
  8. Olga Politikou

    Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
  9. Udo Maierhofer

    Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
  10. Dario Farina

    Department of Bioengineering, Imperial College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7883-2697
  11. Oskar C Aszmann

    Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
  12. Konstantin Davide Bergmeister

    Karl Landsteiner University of Health Sciences, St. Poelten, Austria
    For correspondence
    kbergmeister@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3910-9727

Funding

European Research Council (ERC Synergy Grant: No 810346)

  • Matthias Luft
  • Vlad Tereshenko
  • Christopher Festin
  • Gregor Laengle
  • Olga Politikou
  • Udo Maierhofer
  • Dario Farina
  • Oskar C Aszmann
  • Konstantin Davide Bergmeister

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Samantha R Santacruz, The University of Texas at Austin, United States

Ethics

Animal experimentation: The protocols for the experiments were approved by the ethics committee of the Medical University of Vienna and the Austrian Ministry for Research and Science (reference number BMBWF- 66.009/0413-V/3b/2019) and strictly followed the principles of laboratory animal care as recommended by the Federation of European Laboratory Animal Science Associations (FELASA).

Version history

  1. Received: June 16, 2021
  2. Preprint posted: July 10, 2021 (view preprint)
  3. Accepted: September 30, 2021
  4. Accepted Manuscript published: October 1, 2021 (version 1)
  5. Version of Record published: October 21, 2021 (version 2)

Copyright

© 2021, Luft et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,097
    views
  • 147
    downloads
  • 5
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Matthias Luft
  2. Johanna Klepetko
  3. Silvia Muceli
  4. Jaime Ibáñez
  5. Vlad Tereshenko
  6. Christopher Festin
  7. Gregor Laengle
  8. Olga Politikou
  9. Udo Maierhofer
  10. Dario Farina
  11. Oskar C Aszmann
  12. Konstantin Davide Bergmeister
(2021)
Proof of concept for multiple nerve transfers to a single target muscle
eLife 10:e71312.
https://doi.org/10.7554/eLife.71312

Share this article

https://doi.org/10.7554/eLife.71312

Further reading

    1. Neuroscience
    Zilu Liang, Simeng Wu ... Chao Liu
    Research Article

    People form impressions about others during daily social encounters and infer personality traits from others' behaviors. Such trait inference is thought to rely on two universal dimensions: competence and warmth. These two dimensions can be used to construct a ‘social cognitive map’ organizing massive information obtained from social encounters efficiently. Originating from spatial cognition, the neural codes supporting the representation and navigation of spatial cognitive maps have been widely studied. Recent studies suggest similar neural mechanism subserves the map-like architecture in social cognition as well. Here we investigated how spatial codes operate beyond the physical environment and support the representation and navigation of social cognitive map. We designed a social value space defined by two dimensions of competence and warmth. Behaviorally, participants were able to navigate to a learned location from random starting locations in this abstract social space. At the neural level, we identified the representation of distance in the precuneus, fusiform gyrus, and middle occipital gyrus. We also found partial evidence of grid-like representation patterns in the medial prefrontal cortex and entorhinal cortex. Moreover, the intensity of grid-like response scaled with the performance of navigating in social space and social avoidance trait scores. Our findings suggest a neurocognitive mechanism by which social information can be organized into a structured representation, namely cognitive map and its relevance to social well-being.

    1. Neuroscience
    Alina Tetereva, Narun Pat
    Research Article

    One well-known biomarker candidate that supposedly helps capture fluid cognition is Brain Age, or a predicted value based on machine-learning models built to predict chronological age from brain MRI. To formally evaluate the utility of Brain Age for capturing fluid cognition, we built 26 age-prediction models for Brain Age based on different combinations of MRI modalities, using the Human Connectome Project in Aging (n=504, 36–100 years old). First, based on commonality analyses, we found a large overlap between Brain Age and chronological age: Brain Age could uniquely add only around 1.6% in explaining variation in fluid cognition over and above chronological age. Second, the age-prediction models that performed better at predicting chronological age did NOT necessarily create better Brain Age for capturing fluid cognition over and above chronological age. Instead, better-performing age-prediction models created Brain Age that overlapped larger with chronological age, up to around 29% out of 32%, in explaining fluid cognition. Third, Brain Age missed around 11% of the total variation in fluid cognition that could have been explained by the brain variation. That is, directly predicting fluid cognition from brain MRI data (instead of relying on Brain Age and chronological age) could lead to around a 1/3-time improvement of the total variation explained. Accordingly, we demonstrated the limited utility of Brain Age as a biomarker for fluid cognition and made some suggestions to ensure the utility of Brain Age in explaining fluid cognition and other phenotypes of interest.