Biology subjects

Overton, T.

Publications and source records attributed to Overton, T..

3 recordsLinked to original sources

bioRxiv2025

Limb Position Effect in Myoelectric Control: Strategies for Optimisation and Standardisation

ObjectiveMyoelectric control uses electromyography (EMG) signals for muscle-machine interfacing with applications in prostheses, augmented/virtual reality, and consumer electronics. However, factors such as changes in the limbs position during activities of daily living reduce the controllers reliability. Therefore, there is a need to develop techniques that reduce this limb position effect to increase the widespread adoption of these technologies. ApproachWe developed an open-source device to standardise myoelectric control experiments. The device has sixteen locations for automatically positioning the participants arms to perform hand gestures or grasp objects, with lights and sensors for guidance and timekeeping. We used this device to collect data from eighteen healthy participants in a five-session study under three modalities: performing five hand gestures with a static or dynamic limb and moving three objects. We recorded forearm electromyography and kinematics of the upper limb and trained a linear discriminant analysis model to assess the classifiers accuracy across different modalities and arm positions. Main resultsThe classifiers accuracy with a static limb was decreased when tested on untrained positions, confirming the limb position effect. More training positions improved accuracy, with four optimally balancing the training burden and classifier accuracy. Classifiers trained with data from dynamic movements outperformed when tested on dynamic data. Furthermore, adding kinematic data to the classifier increased accuracy yet significantly reduced learning rates. However, training with a dynamic limb improved this learning rate. SignificanceThe limb position effect can be countered by training with multiple positions and including kinematic data. Classifiers with EMG and kinematic data should be trained using a dynamic limb to achieve high accuracy with reasonable amounts of training data. Our open-source, automated device will help standardise datasets between laboratories, aiding the further development of robust and widespread myoelectric control.

bioengineering↗

bioRxiv2022

A Rapid, High Throughput, Viral Infectivity Assay using Automated Brightfield Microscopy with Machine Learning

Infectivity assays are essential for the development of viral vaccines, antiviral therapies and the manufacture of biologicals. Traditionally, these assays take 2-7 days and require several manual processing steps after infection. We describe an automated assay (AVIA), using machine learning (ML) and high-throughput brightfield microscopy on 96 well plates that can quantify infection phenotypes within hours, before they are manually visible, and without sample preparation. ML models were trained on HIV, influenza A virus, coronavirus 229E, vaccinia viruses, poliovirus, and adenoviruses, which together span the four major categories of virus (DNA, RNA, enveloped, and non-enveloped). A sigmoidal function, fit to virus dilution curves, yielded an R2 higher than 0.98 and a linear dynamic range comparable to or better than conventional plaque or TCID50 assays. Because this technology is based on sensitizing AIs to specific phenotypes of infection, it may have potential as a rapid, broad-spectrum tool for virus identification.

microbiology↗

bioRxiv2021

Efflux only impacts drug accumulation in actively growing cells

For antibiotics with intracellular targets, effective treatment of bacterial infections requires the drug to accumulate to a high concentration inside cells. Bacteria produce a complex cell envelope and possess drug-export efflux pumps to limit drug accumulation inside cells. Decreasing cell envelope permeability and increasing efflux pump activity can reduce intracellular accumulation of antibiotics, and are commonly seen in antibiotic resistant strains. Here, we show that the balance between influx and efflux differs depending on bacterial growth phase in Gramnegative bacteria. Accumulation of the model fluorescent drug, ethidium bromide (EtBr) was measured in S. Typhimurium SL1344 (wild-type) and efflux deficient ({Delta}acrB) strains during growth. In SL1344, EtBr accumulation remained low, regardless of growth phase and did not correlate with acrAB transcription. EtBr accumulation in {Delta}acrB was high in exponential phase but dropped sharply later in growth, with no significant difference to SL1344 in stationary phase. Low EtBr accumulation in stationary phase was not due to the upregulation of other efflux pumps, but instead, due to decreased permeability of the envelope in stationary phase. RNAseq identified changes in expression of several pathways that remodel the envelope in stationary phase, leading to lower permeability. This study shows that efflux is only important for maintaining low drug accumulation in actively growing cells, and that envelope permeability is the predominant factor dictating the rate of drug entry in stationary phase cells. This conclusion means that (i) antibiotics with intracellular targets may be less effective in complex non-growing or slow-growing bacterial infections where intracellular accumulation may be low, (ii) efflux inhibitors may be successful in potentiating the activity of existing antibiotics, but potentially only for bacterial infections where cells are actively growing and (iii) the remodelling of the cell envelope prior to stationary phase could provide novel drug targets.

microbiology↗