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publications
Human breast cancer cells demonstrate electrical excitability
Published in Frontiers in Neuroscience, 2020
We present for the first time non-invasive in vitro electrical recordings of strongly metastatic MDA-MB-231 and weakly/non-metastatic MCF-7 breast cancer cell lines using an ultra-low noise sensor that exploits large-area electrodes, of 2 mm2, which maximizes the double-layer capacitance and concomitant detection sensitivity. We show that the current recorded after adherence of the cells is dominated by the opening of voltage-gated sodium channels (VGSCs), confirmed by application of the highly specific inhibitor, tetrodotoxin (TTX). We also recorded an activity pattern with characteristics similar to that of Random Telegraph Signal (RTS) noise. The RTS noise power spectral density showed a Lorentzian shape, which revealed the presence of a low-frequency signal across MDA-MB-231 cell populations with propagation speeds of the same order as those reported for intercellular Ca2+ waves. Our recording platform paves the way for real-time investigations of the bioelectricity of cancer cells, their ionic/pharmacological properties and relationship to metastatic potential.
Recommended citation: Ribeiro M, Elghajiji A, Fraser SP, Burke ZD, Tosh D, Djamgoz MBA and Rocha PRF (2020) "Human Breast Cancer Cells Demonstrate Electrical Excitability." Front. Neurosci. 14:404. doi: 10.3389/fnins.2020.00404 https://www.frontiersin.org/articles/10.3389/fnins.2020.00404/full
An Ultra-Sensitive Biosensor to Investigate Random Telegraph Noise in Human Breast Cancer Cells
Published in IECB 2020, 2020
This paper introduces a novel strategy for conducting such recordings on highly metastatic MDA-MB-231 cells, via an ultra-low noise biosensor based on a large electrode area which maximises the Helmholtz double-layer capacitance. The extracellular sensitivity of our biosensor allows the detection of pA-level random telegraph signal (RTS) noise superimposed with an omnipresent 1/f noise. The RTS noise is validated and modelled using a Markov chain. The analysis of slow cooperative potentials across the large area electrode suggests the involvement of cohort calcium signalling, and the 1/f noise analysis suggests a strong contribution of resting membrane noise. Overall, this work shows the potential of the new recording platform and statistical analysis for better understanding and predicting the underlying signalling mechanisms of metastatic breast cancer cells. In future, this platform could highlight the effects of compounds, or drugs, on the underlying activity of cancer cell cohorts in a clinical setting.
Recommended citation: Ribeiro M, Rocha P.R.F, Metcalfe B (2020) "An Ultra-Sensitive Biosensor to Investigate Random Telegraph Noise in Human Breast Cancer Cells." MDPI IECB 2020 60:27. doi: 10.3390/IECB2020-07223 https://www.mdpi.com/2504-3900/60/1/27
Microfluidics Integration into Low-Noise Multi-Electrode Arrays
Published in Micromachines, 2021
This work shows a transition from a no-flow (static) multi-electrode array (MEA) to a continuous-flow (dynamic) MEA, assuring a continuous and homogeneous transfer of an electrolyte solution across the measurement chamber. The process through which the microfluidic system was designed, simulated, and fabricated is described, and electrical characterisation of the whole structure under static solution and a continuous flow rate of 80 µL/min was performed. The latter reveals minimal background disturbance, with a background noise below 30 µVpp for all flow rates and areas. This microfluidic MEA, therefore, opens new avenues for more accurate and long-term recordings in Organ-on-Chip systems.
Recommended citation: Ribeiro M, Ali P, Metcalfe B, Moschou D, Rocha PRF (2020) "Microfluidics Integration into Low-Noise Multi-Electrode Arrays." Micromachines 12:727. doi: 10.3390/mi12060727 https://www.mdpi.com/2072-666X/12/6/727
Pig Ulnar Nerve Recording with Sinusoidal and Temporal Interference Stimulation
Published in 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022
This paper expands the current range of experimental methods by demonstrating in vivo extraneural recordings from the ulnar nerve of a pig while applying temporal interference stimulation at a location targeting a distal part of the nerve. The main aim of the experiment was to compare neural activation using sinusoidal stimulation (100 Hz, 2 kHz, 4 kHz) and temporal interference stimulation (2 kHz and 4 kHz). The recordings showed a significant increase in the magnitude of stimulation artefacts at higher frequencies. While those artefacts could be removed and provided an indication of the depth of modulation, they resulted in the saturation of the amplifiers, limiting the stimulation currents and amplifier gains used. The results of the 100 Hz sine wave stimulation showed clear neural activity correlated to the stimulation waveform. However, this was not observed with temporal interference stimulation. The results suggest that, despite its greater penetration, higher currents might be required to observe a neural response with temporal interference stimulation, and more complex artefact rejection techniques may be required to validate the method.
Recommended citation: Jabban L, Ribeiro M, Andreis FR, Nielsen TGNdS and Metcalfe B (2022) "Pig Ulnar Nerve Recording with Sinusoidal and Temporal Interference Stimulation." 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) pp. 5084-5088. doi: 10.1109/EMBC48229.2022.9871603 https://ieeexplore.ieee.org/abstract/document/9871603
Adaptation of the Two-CAP Method for Conduction Velocity Distribution Estimation in Multi-Channel Recordings
Published in 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022
This work extends the Two-CAP method and demonstrates its application to bipolar in-vivo recordings made with multiple-electrode arrays. A sensitivity analysis was conducted using simulated data with ground truth to ascertain the stability and limits of the algorithm before experimental data was examined. The sensitivity analysis highlighted that recording distance shows a considerable impact on the performance of this extended Two-CAP method, as well as the velocity interval chosen when creating the model. The in-vivo data was also compared against an equivalent simulated model, and a relatively low mean squared error was obtained when comparing the two distributions.
Recommended citation: Ribeiro M, Wozniak K, Andreis FR, Nielsen TGNdS and Metcalfe B (2022) "Adaptation of the Two-CAP Method for Conduction Velocity Distribution Estimation in Multi-Channel Recordings." 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) pp. 4109-4114. doi: 10.1109/EMBC48229.2022.9871895 https://ieeexplore.ieee.org/abstract/document/9871895
An in-vitro system for closed loop neuromodulation of peripheral nerves
Published in 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022
This paper describes the development of an in-vitro system for electrically recording and stimulating large animal nerves. This is demonstrated experimentally using explanted pig ulnar nerves, which show evoked compound action potentials (eCAPs) when stimulated. These eCAPs were examined both in the time and velocity domain at a baseline temperature of 20° C, and at temperatures increasing up to those seen in-vivo (37°C). The results highlight that as the temperature is increased within the in-vitro system, faster conduction velocities (CVs) similar to those present in-vivo can be observed. To our knowledge, this is the first time an in-vitro peripheral nerve system has been validated against in-vivo data, which is crucial for promoting more widespread adoption of such systems for the optimisation of neural interfaces.
Recommended citation: Ribeiro M, Jabban L, Andreis FR, Nielsen TGNdS, Rocha PRF and Metcalfe B (2022) "An in-vitro system for closed loop neuromodulation of peripheral nerves." 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) pp. 2361-2364. doi: 10.1109/EMBC48229.2022.9871933 https://ieeexplore.ieee.org/abstract/document/9871933
The assessment list for trustworthy artificial intelligence: A review and recommendations
Published in Frontiers in Artificial Intelligence, 2023
Prior research on ALTAI has focused primarily on specific application areas, but there has yet to be a comprehensive analysis and broader recommendations aimed at proto-regulators and industry practitioners. This paper therefore starts with an overview of this tool, including an assessment of its strengths and limitations. The authors then consider the success by which the ALTAI tool is likely to be of utility to industry in improving understanding of the risks inherent in AI systems and best practices to mitigate such risks. It is highlighted how research and practices from fields such as Environmental Sustainability, Social Justice, and Corporate Governance (ESG) can be of benefit for addressing similar challenges in ethical AI development and deployment. Also explored is the extent to which the tool is likely to be successful in being taken up by industry, considering various factors pertaining to its likely adoption. Finally, the authors also propose recommendations applicable internationally to similar bodies to the HLEG-AI regarding the gaps needing to be addressed between high-level principles and practical support for those on the front-line developing or commercializing AI tools. In all, this work provides a comprehensive analysis of the ALTAI tool, as well as recommendations to relevant stakeholders, with the broader aim of promoting more widespread adoption of such a tool in industry.
Recommended citation: Radclyffe C, Ribeiro M and Wortham RH (2023) The assessment list for trustworthy artificial intelligence: A review and recommendations. Front. Artif. Intell. 6:1020592. doi: 10.3389/frai.2023.1020592 https://www.frontiersin.org/articles/10.3389/frai.2023.1020592/full
Denoising and decoding spontaneous vagus nerve recordings with machine learning
Published in 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2023
In recent years, machine learning (ML) models have shown outstanding performance in regression and classification problems, but it is often unclear how to translate and assess these for novel tasks in biomedical engineering. This paper aims to adapt existing ML algorithms to carry out unsupervised denoising of neural recordings instead. This is achieved by applying bandpass filtering and two novel ML algorithms to in-vivo spontaneous, low-SNR vagus nerve recordings. The performance of each approach is compared using the task of extracting respiratory afferent activity and validated using cross-correlation, MSE, and accuracy in terms of extracting the true respiratory rate. A variational autoencoder (VAE) model in particular produces results that show better correlation with respiratory activity compared to bandpass filtering, highlighting that these models have the potential to preserve relevant features in complex neural recordings.
Recommended citation: Ribeiro M, Koh RGL, Donnelly T, Lutteroth C, Proulx MJ, Rocha PRF, and Metcalfe B (2022) "Denoising and decoding spontaneous vagus nerve recordings with machine learning." 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) pp. 1-4. doi: 10.1109/EMBC40787.2023.10340443 https://ieeexplore.ieee.org/abstract/document/10340443
Ex-vivo systems for neuromodulation: A comparison of ex-vivo and in-vivo large animal nerve electrophysiology
Published in Journal of Neuroscience Methods, 2024
Little research exists on extending ex-vivo systems to large animal nerves, and to the best of our knowledge, there has yet to be a study comparing these against in-vivo data. This paper details the first ex-vivo system for large animal peripheral nerves to be compared with in-vivo results. Detailed ex-vivo and in-vivo closed-loop neuromodulation experiments were conducted on pig ulnar nerves. Pig ulnar nerves were sustained ex-vivo up to 5 h post-explantation. CV distributions of ex-vivo and in-vivo data were compared, showing closer correspondence at 37 °C. Regression analysis results also demonstrated that modal CV and time since explantation were negatively correlated, whereas modal CV and temperature were positively correlated. The proposed ex-vivo system results were compared with those seen in-vivo, providing new insights into large animal nerve activity post-explantation. Such a system is crucial for complementing in-vivo experiments, maximising collected experimental data, and accelerating neural interface development.
Recommended citation: M. Ribeiro, F.R. Andreis, L. Jabban et al., Ex-vivo systems for neuromodulation: A comparison of ex-vivo and in-vivo large animal nerve electrophysiology. Journal of Neuroscience Methods (2024), doi: https://doi.org/10.1016/j.jneumeth.2024.110116 https://www.sciencedirect.com/science/article/pii/S016502702400061X
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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