Biology subjects

Healey, R.

Publications and source records attributed to Healey, R..

3 recordsLinked to original sources

bioRxiv2026

3D printing and deep learning enable holistic and dynamic analyses of tens of thousands of parasites infecting hundreds of genotypes

Host-parasite interactions are dynamic systems, where parasites usually outnumber hosts by one or more orders of magnitude. However, our understanding is often limited by the assessment of parts of the host, at arbitrary time points, and/or aggregate parasite responses. Here we combined custom-built 3D-printed hardware and deep-learning-based algorithms to enable holistic (i.e. all infecting individuals on the whole plant), spatio-temporal, and parasite-centric analyses of plant-parasitism by nematodes from timelapse videos of infection over months. In so doing, we tracked the dynamic growth and development of all individual parasites, at the organismal level, for thousands of hosts across hundreds of genotypes of Arabidopsis thaliana. Categorising traits into the static (i.e. in an acquired image at a given time point) and dynamic (i.e. phenotypic changes over time), we revealed a greater extent of host-genetic control of parasite traits, and new physiological limits of the species under these conditions. Using this capability, we identify Quantitative Trait Loci (QTL) in the host plant associated with 18 phenotypic traits in the parasite as a resource for the community. Finally, we leverage the large and diverse dataset to understand fundamental features of the parasite, independent of host genotype, revealing aspects of the life cycle which are pseudo-deterministic as well as local, deleterious interactions between co-infecting parasites. Given that plant-parasitic nematodes cause an estimated $100 billion in agricultural damages per year, these insights are contextualised in a global challenge driven by plant-parasitic nematodes.

pathology↗

bioRxiv2025

The Stop Signal Stepping Task: how action cancellation commands disrupt step initiation in young and healthy older adults

Action cancellation - the ability to rapidly cancel an initiated movement in response to unexpected events - has been extensively studied in the upper limb using the stop signal task (SST). During gait, action cancellation is needed to stop and modify steps to avoid hazards and prevent falls. By adapting the SST to step initiation, this study investigated how the anticipatory postural adjustment (APA) and foot-lift phases of forward stepping were affected by action cancellation commands, and whether this changed with healthy ageing. The SST was performed in stepping, foot tap, and finger button conditions in 27 young (Mage = 28.7 years) and 29 healthy older adults (Mage = 70.1 years). Across conditions, older adults exhibited slower response speed compared to young adults and greater proactive slowing of responses when stop cues were anticipated. However, there was no significant difference in stopping speed between young and older adults. Stopping speed was fastest in the finger tap condition, and slowest in the step condition. When an APA was initiated in a step cancellation trial, the magnitude of the weight shift toward the step leg did not differ between successful and unsuccessful foot-lift cancellations. Foot-lift could be cancelled when stop cues were presented at similar phases of step preparation for young and older adults. These results suggest that the initial loading of the step leg is a ballistic process, however as weight is shifted toward the stance leg, action cancellation commands responding to external stimuli can decouple the APA and foot-lift step phases. Key PointsO_LIThe stop signal task (SST) - which allows an estimation of stopping speed independently of response speed - was applied to voluntary stepping in young and older adults. C_LIO_LIWhile response speed was slower for older than young adults, stopping speed was not significantly different between age groups in the upper limb, lower limb when seated, and during forward stepping. C_LIO_LIWhen stop cues were introduced, response speed slowed more in older than young adults, and more in the upper than the lower limb (i.e., Foot Tap and Step conditions). C_LIO_LIThe initial preparatory weight shift toward the stepping foot was not significantly different between successfully cancelled steps and normal steps, highlighting the ballistic nature of the early phase of step preparation. C_LIO_LIPrior to foot-lift, action cancellation commands could decouple the preparatory weight shift phase from foot-lift at similar stages of step initiation in young and healthy older adults. C_LI

neuroscience↗

bioRxiv2022

A low-cost and open-source solution to automate imaging and analysis of cyst nematode infection assays for Arabidopsis thaliana

BackgroundCyst nematodes are one of the major groups of plant-parasitic nematode, responsible for considerable crop losses worldwide. Improving genetic resources, and therefore resistant cultivars, is an ongoing focus of many pest management strategies. One of the major bottlenecks in identifying the plant genes that impact the infection, and thus the yield, is phenotyping. The current available screening method is slow, has unidimensional quantification of infection limiting the range of scorable parameters, and does not account for phenotypic variation of the host. The ever-evolving field of computer vision may be the solution for both the above-mentioned issues. To utilise these tools, a specialised imaging platform is required to take consistent images of nematode infection in quick succession. ResultsHere, we describe an open-source, easy to adopt, imaging hardware and trait analysis software method based on a pre-existing nematode infection screening method in axenic culture. A cost-effective, easy-to-build and -use, 3D-printed imaging device was developed to acquire images of the root system of Arabidopsis thaliana infected with the cyst nematode Heterodera schachtii, replacing costly microscopy equipment. Coupling the output of this device to simple analysis scripts allowed the measurement of some key traits such as nematode number and size from collected images, in a semi-automated manner. Additionally, we used this combined solution to quantify an additional trait, root area before infection, and showed both the confounding relationship of this trait on nematode infection and a method to account for it. ConclusionTaken together, this manuscript provides a low-cost and open-source method for nematode phenotyping that includes the biologically relevant nematode size as a scorable parameter, and a method to account for phenotypic variation of the host. Together these tools highlight great potential in aiding our understanding of nematode parasitism.

plant biology↗