Biology subjects

Hart, M. G.

Publications and source records attributed to Hart, M. G..

3 recordsLinked to original sources

bioRxiv2025

The role of STN beta oscillations on lower extremity muscle activity in Parkinsonian stepping

Freezing of gait (FOG) is a devastating symptom of Parkinsons disease (PD) often resulting in disabling falls and loss of independence. It affects half of patients, yet current therapeutic strategies are insufficient, and the underlying neural mechanisms remain poorly understood. This study investigated beta oscillation dynamics in the STN during different locomotor states, while examining the effects of levodopa. In particular, it aimed to identify pathological activity by analysing the relationship between the STN and lower limb muscles during stepping. Local field potentials (LFP) in the STN and muscle activity (EMG) of the gastrocnemius and peroneus longus were recorded in 14 PD patients during standing and stepping, ON and OFF levodopa. Levodopa reduced stepping variability, implying improved stepping abilities. Distinct STN beta patterns were observed between stepping and standing, with lower high-beta and higher low-beta during stepping compared to standing, suggesting a distinct role of these frequency bands in motor control during postural and movement states. Levodopa reduced low-beta but increased high-beta activity, highlighting a potential physiological function of high-beta in the STN during standing and stepping. In addition, step-phase specific effects of levodopa included reduced broad-beta band activity in the STN and lower limb muscles during the late-stance and pushing-off phase of the contralateral leg when ON medication. Further analyses suggest that pathological STN activity amplifies muscle activation around movement initiation, potentially reducing the ability of the patient to move freely. These findings offer insight for developing phase-specific stimulation strategies targeting STN beta oscillations during gait.

neuroscience↗

bioRxiv2024

A novel HLA Class II presentation prediction algorithm deciphers immunogenic CD4 epitopes specific to KRAS G12C

Accurate prediction of peptide presentation by HLA molecules is important for generation of effective individualized cancer vaccines and immunotherapies. While presentation prediction algorithms for HLA class I have been successfully applied in the context of such therapies, improved prediction algorithms for class II are needed. EDGE-II is a novel algorithm based on a protein large language model that has a learned allele deconvolution network trained on existing and new immunopeptidomics data. It delivers state-of-the-art performance on prediction of peptide presentation by HLA class II and immunogenicity elicited by CD4+ T-cell epitopes. In a patient with a KRAS G12C positive tumor treated with a KRAS G12C targeting immunotherapy, EDGE-II identified KRAS G12C class II neoantigens that elicited clonally expanded CD4+ T cells with cytotoxic transcriptional profiles post-vaccination. EDGE-II could play an important role in the development of effective cancer immunotherapies by elucidating an enriched understanding of the immunopeptidome.

bioinformatics↗

bioRxiv2017

Global Effects Of Focal Brain Tumours On Functional Complexity And Network Robustness

BackgroundNeurosurgical management of brain tumours has entered a new paradigm of supra-marginal resections that demands thorough understanding of their peri-tumoural functional effects. Historically the effects of tumours have been considered as local, and long-range effects have not been considered. This work tests the hypothesis that focal tumours affect the brain at a global level producing long-range gradients in cortical function.\n\nMethodsResting state functional (f)MRI data were acquired from 11 participants with glioblastoma and split into discovery and validation datasets. Fractal complexity was computed with a wavelet-based estimator of the Hurst exponent. Distance related effects of the tumours were tested with a tumour mask dilation technique and parcellation of the underlying Hurst maps. Functional connectivity networks were constructed and validated with different parcellation and statistical dependency methods prior to graph theory analysis.\n\nResultsFractal complexity, measured through the Hurst exponent and tumour mask dilation technique, demonstrates a penumbra of suppression in the peri-tumoural region. At a global level, as distance from the tumour increases, this initial suppression is balanced by a subsequent over-activity before finally normalizing. These effects were best fit by a quadratic model, and were consistent across different network construction pipelines. The Hurst exponent was significantly correlated with multiple graph theory measures of centrality including network robustness, but graph theory measures did not demonstrate distance dependent effects.\n\nConclusionsThis work provides evidence to support the theory that focal brain tumours produce long-range and non-linear gradients in function. Consequently the effects of focal lesions, and the resultant clinical effects, need to be interpreted in terms of the global changes on whole brain functional complexity and network architecture rather than purely in terms of functional localisation. Determining whether the peri-tumoural changes represent adaption or potential plasticity, for example, may facilitate extended resection of the tumour without functional cost.

neuroscience↗