Biology subjects

Maguire, L.

Publications and source records attributed to Maguire, L..

6 recordsLinked to original sources

bioRxiv2024

Aggregation of an FG nucleoporin under crowded conditions

Macromolecular crowding can affect the aggregation behavior of intrinsically disordered proteins in unexpected ways. We studied the aggregation of a peptide derived from the disordered FG nucleoporins which line the nuclear pore complex. We measured its aggregation kinetics in the presence of both inert and non-specifically interacting crowding agents. Using fluorescence emission and NMR spectroscopy, we probed differences in the local chemical microenvironment of the peptides residues. Our results indicate differences in aggregation kinetics and residue microenvironment depending on the identity of the crowder, including differences between crowding with PEG and PVP, two polymers which are often used interchangeably as inert crowding agents.

biophysics↗

bioRxiv2019

Bound-state diffusion due to binding to flexible polymers in a selective biofilter

Selective biofilters are used by cells to control the transport of proteins, nucleic acids, and other macromolecules. Biological filters demonstrate both high specificity and rapid motion or high flux of proteins. In contrast, high flux comes at the expense of selectivity in many synthetic filters. Binding can lead to selective transport in systems in which the bound particle can diffuse, but the mechanisms that lead to bound diffusion remain unclear. Previous theory has proposed a molecular mechanism of bound-state mobility based only on transient binding to flexible polymers. However, this mechanism has not been directly tested in experiments. We demonstrate that bound mobility via tethered diffusion can be engineered into a synthetic gel using protein fragments derived from the nuclear pore complex. The resulting bound-state diffusion is quantitatively consistent with theory. Our results suggest that synthetic biological filters can be designed to to take advantage of tethered diffusion to give rapid, selective transport.\n\nSIGNIFICANCEBiological filters control the passage of proteins and other macromolecules between compartments of living systems. Determination of molecular mechanisms giving selective transport would enable the design of both selective filters and particles designed to penetrate biological barriers for drug delivery. One such mechanism arises from transient binding to dynamic polymer tethers. We designed a biomaterial which supports this type of tethered diffusion, demonstrating the potential to engineer bio-inspired filters.

biophysics↗

bioRxiv2019

Design principles of selective transport through biopolymer barriers

In biological systems, polymeric materials block the movement of some macromolecules while allowing the selective passage of others. In some cases, binding enables selective transport, while in others the most inert particles appear to transit most rapidly. To study the general principles of filtering, we develop a model motivated by features of the nuclear pore complex (NPC) which are highly conserved and could potentially be applied to other biological systems. The NPC allows selective transport of proteins called transport factors which transiently bind to disordered, flexible proteins called FG Nups. While the NPC is tuned for transport factors and their cargo, we show that a single feature is sufficient for selective transport: the bound-state motion resulting from transient binding to flexible filaments. Interchain transfer without unbinding can further improve selectivity, especially for crosslinked chains. We generalize this observation to model nanoparticle transport through mucus and show that bound-state motion accelerates transport of transient nanoparticle application, even with clearance by mucus flow. Our model provides a framework to control binding-induced selective transport in bipolymeric materials.

biophysics↗

bioRxiv2019

Metastable neural dynamics underlies cognitive performance across multiple behavioural paradigms

Despite resting state networks being associated with a variety of cognitive abilities, it remains unclear how these local areas act in concert to express particular cognitive operations. Theoretical and empirical accounts indicate that large-scale resting state networks reconcile dual tendencies toward integration and segregation by operating in a metastable regime of their coordination dynamics. One proposal is that metastability confers important behavioural qualities by dynamically binding distributed local areas into large-scale neurocognitive entities. We tested this hypothesis by analysing fMRI data in a large cohort of healthy individuals (N=566) and comparing the metastability of the brains large-scale resting network architecture at rest and during the performance of several tasks. Task-based reasoning was principally characterised by high metastability in cognitive control networks and low metastability in sensory processing areas. Although metastability between resting state networks increased during task performance, cognitive ability was more closely linked to spontaneous activity. High metastability in the intrinsic connectivity of cognitive control networks was linked to novel problem solving (or fluid intelligence) but was less important in tasks relying on prior experience (or crystallised intelligence). Crucially, subjects with resting architectures similar or pre-configured to a task-general arrangement demonstrated superior cognitive performance. Taken together, our findings support a critical linkage between the spontaneous metastability of the large-scale networks of the cerebral cortex and cognition.

neuroscience↗

bioRxiv2019

A practical computerized decision support system for predicting the severity of Alzheimer’s disease of an individual

Computerized clinical decision support systems can help to provide objective, standardized, and timely dementia diagnosis. However, current computerized systems are mainly based on the group analysis, discrete classification of disease stages, or expensive and not readily accessible biomarkers, while current clinical practice relies relatively heavily on cognitive and functional assessments (CFA). In this study, we developed a computational framework using a suite of machine learning tools for identifying key markers in predicting the severity of Alzheimers disease (AD) from a large set of biological and clinical measures. Six machine learning approaches, namely Kernel Ridge Regression (KRR), Support Vector Regression (SVR), and k-Nearest Neighbor (kNNreg) for regression and Support Vector Machine (SVM), Random Forest (RF), and k-Nearest Neighbor (kNNclass) for classification, were used for the development of predictive models. We demonstrated high predictive power of CFA. Predictive performance of models incorporating CFA was shown to be consistently higher accuracy than those based solely on biomarker modalities. We found that KRR and SVM were the best performing regression and classification methods respectively. The optimal SVM performance was observed for a set of four CFA test scores (FAQ, ADAS13, MoCA, MMSE) with multi-class classification accuracy of 83.0%, 95%CI = (72.1%, 93.8%) while the best performance of the KRR model was reported with combined CFA and MRI neuroimaging data, i.e., R2 = 0.874, 95%CI = (0.827, 0.922). Given the high predictive power of CFA and their widespread use in clinical practice, we then designed a data-driven and self-adaptive computerized clinical decision support system (CDSS) prototype for evaluating the severity of AD of an individual on a continuous spectrum. The system implemented an automated computational approach for data pre-processing, modelling, and validation and used exclusively the scores of selected cognitive measures as data entries. Taken together, we have developed an objective and practical CDSS to aid AD diagnosis.

neuroscience↗

bioRxiv2019

Primary care use of laboratory tests in Northern Ireland Western Health and Social Care Trust: a cross-sectional study

ObjectivesTo describe the laboratory test ordering patterns by general practitioners (GPs) in Northern Ireland Western Health and Social Care Trust (WHSCT) and establish demographic and socio-economic associations with test requesting.\n\nDesignCross-sectional study.\n\nSettingWestern Health and Social Care Trust, Northern Ireland\n\nParticipants55 WHSCT general practices requesting laboratory tests in the period from 1 April 2011 to 31 March 2016\n\nOutcomesTo identify the temporal patterns of laboratory test ordering behaviour for 8 commonly requested clinical biochemistry tests/test groups in WHSCT. To analyse the extent of variations in laboratory test requests by GPs and to determine whether these variations can be accounted for by clinical outcomes or geographical, demographic, and socioeconomic characteristics.\n\nResultsWe identified substantial changes in the median number of request rates over five consecutive years of the study period as well as a large variation of adjusted test request rates for individual tests (lowest for electrolyte profiles, liver profiles, and HbA1c and highest for immunoglobulins). No statistically significant relationship between ordering activity and either demographic (age and gender) and socioeconomic factors (deprivation) or Quality and Outcome Framework (QOF) scores was observed. We found that practice setting accounted for some of the between-practice variation in test requesting. Rural practices were characterized by both higher between practice variability and median number of order tests than urban practices at all time points.\n\nConclusionsA large between-practice variation in GP laboratory test requesting appears unrelated to demographic and socioeconomic indicators of the practices or crude clinical outcome indicators, most likely reflects differences in the clinical practice of individuals, potentially amenable to change through clinical interventions.\n\nStrengths and limitations of this studyO_LIThe study provides a comprehensive analysis of temporal changes in laboratory test utilization patterns and establishes the extent of variability in test requesting activity across general practices in Northern Irelands Western Health and Social Care Trust.\nC_LIO_LIThe substantial variation in test ordering, not related to demographic and socioeconomic characteristics of practices, practice location or clinical outcome indicators, may reflect inappropriate laboratory test utilization and hence, suggest a potential for more efficient demand management of laboratory services.\nC_LIO_LIGiven a cohort of general practices within one catchment area, our results provide evidence of differences in behaviour of individual GPs when managing patients with similar clinical symptoms.\nC_LIO_LIFailure to collect and cross-tabulate data on characteristics of general practitioners (GPs), such as GPs age, years of experience, medical training was a study limitation and a missed opportunity in assessing the influence of practitioner factors on the variation in test ordering behaviour.\nC_LI

biochemistry↗