Imperial College London

Ruby Sedgwick

Faculty of EngineeringDepartment of Computing

Research Postgraduate
 
 
 
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Contact

 

r.sedgwick19 Website

 
 
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Location

 

Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
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2 results found

Sedgwick R, Goertz J, Stevens M, Misener R, Wilk MVDet al., 2020, Design of Experiments for Verifying Biomolecular Networks

Working paper

Bianchi F, Sedgwick R, Ye H, Thompson MSet al., 2018, Strain partitioning between nerves and axons: Estimating axonal strain using sodium channel staining in intact peripheral nerves, Journal of Neuroscience Methods, Vol: 309, Pages: 1-5, ISSN: 0165-0270

Background Peripheral nerves carry afferent and efferent signals between the central nervous system and the periphery of the body. When nerves are strained above physiological levels, conduction blocks occur, resulting in debilitating loss of motor and sensory function. Understanding the effects of strain on nerve function requires knowledge of the multi-scale mechanical behaviour of the tissue, and how this is transferred to the cellular environment. New method The aim of this work was to establish a technique to measure the partitioning of strain between tissue and axons in axially loaded peripheral nerves. This was achieved by staining extracellular domains of sodium channels clustered at nodes of Ranvier, without altering tissue mechanical properties by fixation or permeabilisation. Results Stained nerves were imaged by multi-photon microscopy during in situ tensile straining, and digital image correlation was used to measure axonal strain with increasing tissue strain. Strain was partitioned between tissue and axon scales by an average factor of 0.55. Comparisons with existing methods This technique allows non-invasive probing of cell-level strain within the physiological tissue environment. Conclusions This technique can help understand the mechanisms behind the onset of conduction blocks in injured peripheral nerves, as well as to evaluate changes in multi-scale mechanical properties in diseased nerves.

Journal article

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