Biology subjects

Seal, M.

Publications and source records attributed to Seal, M..

13 recordsLinked to original sources

bioRxiv2026

Reported estimates of human airway dimensions are inconsistent across studies

RationaleRespiratory diseases are a source of immense socioeconomic burden globally. In silico approaches can predict changes in human lung function due to disease or response to therapy. By stratifying patient-specific response a priori, these models can enable clinical-scale deployment of precision medicine strategies. Key to this is developing accurate organ geometries on which the models can be simulated. However, we lack analyses assessing the clinical applicability of reported airway dimension estimates. ObjectiveTo investigate physiologically-/anatomically-relevant airway dimension estimates and evaluate consistency across reported literature. MethodsWe conducted a systematic review of 37 published datasets. Airway wall thickness estimates were mined for healthy subjects and patients, and standardised to the Horsfield order airway generations. We simulated dynamic lung function to quantitatively assess their physiological relevance. We created an online database to make all datasets available to the research community. Measurements and Main ResultsReported human airway wall thickness estimates are inconsistent across studies. K-means clustering divided estimates for healthy subjects and patients into three and four clusters, respectively. Only one of the clusters in each category yielded anatomically-relevant estimates. Pressure-volume curves generated to assess physiological relevance also showed that only one cluster in each category exhibited plausible physiology. Principal Component Analysis weakly implicated imaging modalities to explain this inconsistency. ConclusionsReported airway dimension estimates are inconsistent and lack standardisation. To support future modelling efforts, we report physiologically-relevant estimates and introduce an open-access airway-dimension database to help standardise geometric inputs and quantify how measurement variability propagates to functional predictions.

biophysics↗

bioRxiv2024

Pubertal hormones and the early adolescent female brain: a multimodality brain MRI study

Puberty is a critical developmental process that is associated with changes in steroid hormone levels, which are believed to influence adolescent behaviour via their effects on the developing brain. So far, there are limited and inconsistent findings regarding the relationship between steroid hormones and brain structure and function in adolescent females, with many existing studies employing small sample sizes. Thus, in this study, we explored the association between oestradiol (E2), testosterone (Tes) and dehydroepiandrosterone (DHEA) and brain structure (gray matter volume, sulcal depth, cortical thickness and white matter microstructure) and function (resting-state connectivity, emotional n-back task-related function) in 3024 adolescent females (age 8.92 - 13.33 years, mean age (SD) = 10.37 (0.94) years) from the Adolescent Brain Cognitive DevelopmentSM (ABCD(R)) Study. We used elastic-net regression with cross- validation to investigate associations between hormones and brain phenotypes derived from multiple imaging modalities. We found that structural brain features, including cortical thickness, sulcal depth, and white matter microstructure, were among the most important features associated with hormones. E2 was most strongly associated with prefrontal and premotor regions involved in working memory and emotion processing, while Tes and DHEA were most strongly associated with parietal and occipital regions involved in visuospatial functioning. All three hormones were also associated with prefrontal, temporoparietal junction and insula cortices. Thus, using an advanced methodological approach, this study suggests both unique and overlapping neural correlates of pubertal hormones in adolescent females and sheds light on the mechanisms by which puberty influences adolescent development and behaviour.

neuroscience↗

bioRxiv2024

First record of Culex pipiens (Diptera: Culicidae) in Alberta: Expanding distributions and ecotype patterns in a western Canadian province

Culex pipiens is an invasive mosquito found in temperate regions globally. It is considered among the most important disease vectors worldwide and is responsible for transmission of a range of pathogens, including West Nile virus, avian malaria, Saint Louis encephalitis, and filarial worms. Throughout its northern temperate range, this mosquito is found in two ecotypes: form pipiens and form molestus. In Canada, this mosquito was previously thought restricted to the Pacific coast of British Columbia and the eastern provinces of Ontario, Quebec, and the Maritimes. Through routine mosquito surveillance and targeted trapping for Cx. pipiens, we detected this mosquito in two Albertan municipalities earlier than suggested by species distribution modelling based on climate change data. We confirmed the identity of putative Cx. pipiens specimens using DNA sequencing and found that form pipiens was the most common ecotype found in Alberta. Further, we compared the frequency of ecotypes in Alberta to elsewhere in North America and found a general trend of increased form pipiens in more northern latitudes, similar to previously reported results. We discuss our findings in context of vector-borne disease activity in Canada, particularly West Nile virus.

ecology↗

bioRxiv2022

Peptide-RNA Coacervates as a Cradle for the Evolution of Folded Domains

Peptide-RNA coacervates can result in the concentration and compartmentalization of simple biopolymers. Given their primordial relevance, peptide-RNA coacervates may have also been a key site of early protein evolution. However, the extent to which such coacervates might promote or suppress the exploration of novel peptide conformations is fundamentally unknown. To this end, we used electron paramagnetic resonance (EPR) spectroscopy to characterize the structure and dynamics of an ancient and ubiquitous nucleic acid binding element, the helix-hairpin-helix (HhH) motif, alone and in the presence of RNA, with which it forms coacervates. Double electron-electron resonance (DEER) spectroscopy applied to singly labeled peptides containing one HhH motif reveals the presence of dimers, even in the absence of RNA, and transient -helical character. Moreover, dimer formation is promoted upon RNA binding and was detectable within peptide-RNA coacervates. The distance distributions between spin labels are consistent with the symmetric (HhH)2-Fold, which is generated upon duplication and fusion of a single HhH motif and traditionally associated with dsDNA binding. These results support the hypothesis that coacervates are a unique testing ground for peptide oligomerization and that phase-separating peptides could have been a resource for the construction of complex protein structures via common evolutionary processes, such as duplication and fusion.

biophysics↗

bioRxiv2021

Participant followup rate can bias structural imaging measures in longitudinal studies

Longitudinal MRI analysis is essential to accurately describe neuroanatomical changes over time. Loss of participants to followup (dropout) in longitudinal studies is inevitable and can lead to great difficulty in interpretation of statistical results if dropout is correlated with a study outcome or exposure. Beyond this, technical aspects of longitudinal MRI analysis require specialised processing pipelines to improve reliability while avoiding bias towards individual timepoints. In this article we test whether there is an additional problem that must be considered in longitudinal imaging studies, namely whether dropout has an impact on the function of FreeSurfer, a popular software pipeline used to estimate important structural brain metrics. We find that the number of acquisitions available per individual can impact the estimation of cortical thickness and brain volume using the FreeSurfer longitudinal pipeline, and can induce group differences in brain metrics. The effect on trajectories of brain metrics is smaller than the effect on brain metrics. HighlightsO_LILongitudinal MRI analysis is essential to accurately track neuroanatomical changes over time C_LIO_LILongitudinal MRI analysis requires specialised processing pipelines to reduce bias towards single timepoints C_LIO_LIParticipant drop out or loss can bias neuroanatomical measures derived from longitudinal pipelines C_LIO_LIWe find that group differences in the number of acquisitions available to analyse can cause group differences in estimated cortical thickness and brain volume C_LIO_LIThis bias appears to be due to the number of scans used to create individualised templates in the Freesurfer longitudinal pipeline C_LIO_LIThe effect on estimates of brain metric trajectories appears smaller than the effect on the estimates of brain metrics C_LI

neuroscience↗

bioRxiv2019

Longitudinal white matter development in children is associated with puberty, attentional difficulties, and mental health

The pubertal period involves dynamic white matter development. This period also corresponds with rapid gains in higher cognitive functions including attention, as well as increased risk of developing mental health difficulties. This longitudinal study comprised children aged 9-13 years (n=130). Diffusion magnetic resonance imaging (dMRI) data were acquired (b=2800 s/mm2, 60 directions) at two time-points. We derived measures of fibre density and morphology using the fixel-based analysis framework and performed a tract-based mixed-effects modelling analysis to understand patterns of white matter development with respect to age, pubertal stage, attentional difficulties, and internalising and externalising problems. We observed significant increases in apparent fibre density across a large number of white matter pathways, including major association and commissural pathways. We observed a linear relationship between fibre density and morphology with pubertal stage, in the right superior longitudinal fasciculus and in the right inferior longitudinal fasciculus. In terms of symptom severity, fibre density was positively associated with attentional dysfunction in the right uncinate fasciculus. Overall, white matter development across ages 9-13 years involved the expansion of major white matter fibre pathways, with key right-lateralised association pathways linked with pubertal development and attentional difficulties.

neuroscience↗

bioRxiv2019

Parcellation of the cortex using Surface-based Melbourne Children's Regional Infant Brain atlases (M-CRIB-S)

BackgroundLongitudinal studies of cortical morphology are best facilitated by parcellation schemes that are compatible across all life stages. Until recently, neonatal atlases derived strictly from neonatal data, rather than warping brain labels from an adult atlas, did not exist. The Melbourne Childrens Regional Infant Brain (M-CRIB) and M-CRIB 2.0 atlases now provide voxel-based parcellations of the cerebral cortex within T2-weighted neonatal images. These atlases are compatible with the Desikan-Killiany (DK) and the Desikan-Killiany-Tourville (DKT) cortical labelling schemes commonly used for older children and adults. However, there is still a need for a surface-based approach for parcellating neonatal images using these atlases. AimsWe aimed to introduce surface-based versions of the M-CRIB and M-CRIB 2.0 atlases, termed M-CRIB-S(DK) and M-CRIB-S(DKT), along with a pipeline for automated parcellation with FreeSurfer tools. We also aimed to evaluate the automated parcellation accuracy of our M-CRIB-S atlases using cross-validation with manually labelled data; and to evaluate accuracy of the proposed automated parcellation pipeline for the M-CRIB-S labels against the publicly available surface-based University of North Carolina (UNC) 4D neonatal atlas, which has labels derived from the DK adult atlas. MethodsUsing datasets of 10 M-CRIB or M-CRIB 2.0 manually labelled ground truth images and 48 unlabelled T2-weighted magnetic resonance images (MRI) of healthy neonates, cortical surfaces were extracted using the Deformable module within MIRTK. Cortical regions from the labelled images were encoded into a spherical template space using FreeSurfer tools wherein M-CRIB-S(DK) and M-CRIB-S(DKT) atlases were constructed. Automatic parcellation of the labelled and unlabelled (L+U) images (n=58) using the M-CRIB-S(DK) and M-CRIB-S(DKT) atlases were computed with Bayesian labelling using FreeSurfer tools. Accuracy was assessed by comparison with manually labelled ground truth data (n=10) using Dice coefficients and within a Leave-One-Out (LOO) cross-validation framework. Agreement of the UNC atlas parcellations with manual M-CRIB labelling was also evaluated using Dice coefficients. ResultsWhen comparing automated parcellations from the M-CRIB-S atlases to manual labels, disagreements were mostly closely confined to region boundaries, suggesting high overlap overall. Quantitatively, average regional Dice coefficients were 0.88 (L+U) and 0.83 (LOO) for the M-CRIB 2.0 labels and 0.87 (L+U), 0.80 (LOO) for the M-CRIB labels, and 0.67 for the UNC atlas. ConclusionsThe M-CRIB-S atlases and automatic pipeline described in this paper allow infant cortical surfaces to be accurately parcellated according to the DK or DKT parcellation schemes. This will help facilitate surface-based investigations of brain function at the neonatal time point, and potentially longitudinally across the lifespan. The use of M-CRIB-S outperformed a technique that relies on an adult-derived atlas. The atlases, averaged white, inflated, pial and spherical surfaces, along with customised scripts for segmentation, cortical surface extraction and parcellation, are available for public download.

neuroscience↗

bioRxiv2018

Individualised MRI training for paediatric neuroimaging in autism spectrum disorders: A child-focused approach

Magnetic Resonance Imaging (MRI) in paediatric cohorts is often complicated by reluctance to enter the scanner and head motion-related imaging artefacts. The MRI scanner environment is highly unusual and may distress younger cohorts, especially in children with sensory sensitivity and separation anxiety. The issue is particularly challenging in children with Autism Spectrum Disorders (ASD), where delivery of instructions for novel task demands in an unfamiliar setting may be limited or less effective due to communication disorder or intellectual disability. These issues together often give rise to excessive head motion that can significantly reduce the quality of images acquired, or render data unusable. Here we report an individualised MRI training procedure that enables young children with ASD to better tolerate the MRI scanner environment based on a child-focused approach and an individualised familiarisation strategy. The training procedure was implemented in a locally recruited study of monozygotic twins (n=12; 6 twin pairs; age range 7.1 to 12.85 years) concordant or discordant for ASD. MRI image quality indices were better or comparable to images acquired from an independent multi-centre ASD cohort. The success of these findings is promising and may be useful to improve the quality of paediatric neuroimaging in similar clinical populations.

neuroscience↗

bioRxiv2018

Quantifying individual differences in brain morphometry underlying symptom severity in Autism Spectrum Disorders

The neurobiology of heterogeneous neurodevelopmental disorders such as autism spectrum disorders (ASD) are still unclear. Despite extensive efforts, most findings are difficult to reproduce due to high levels of individual variance in phenotypic expression. To quantify individual differences in brain morphometry in ASD, we implemented a novel subject-level, distance-based method on subject-specific attributes. In a large multi-cohort sample, each subject with ASD (n=100; n=84 males; mean age: 11.43 years; mean IQ: 110.58) was strictly matched to a control participant (n=100; n=84 males; mean age: 11.43 years; mean IQ: 110.70). Intrapair Euclidean distance of MRI brain morphometry and symptom severity measures were entered into a regularised machine learning pipeline for feature selection, with rigorous out-of-sample validation and bootstrapped permutation testing. Subject-specific structural morphometry features significantly predicted individual variation in ASD symptom severity (19 cortical thickness features, p=0.01, n=5000 permutations; 10 surface area features, p=0.006, n=5000 permutations). Findings remained robust across subjects and were replicated in validation samples. Identified cortical regions implicate key hubs of the salience and default mode networks as neuroanatomical features of social impairment in ASD. Present results highlight the importance of subject-level markers in ASD, and offer an important step forward in understanding the neurobiology of heterogeneous disorders.

neuroscience↗

bioRxiv2018

Development of white matter fibre density and morphology over childhood: a longitudinal fixel-based analysis

PurposeWhite matter fibre development in childhood involves dynamic changes to microstructural organisation driven by increasing axon diameter, density, and myelination. However, there is a lack of longitudinal studies that have quantified advanced diffusion metrics to identify regions of accelerated fibre maturation, particularly across the early pubertal period. We applied a novel longitudinal fixel-based analysis (FBA) framework, in order to estimate microscopic and macroscopic white matter changes over time.\n\nMethodsDiffusion-weighted imaging (DWI) data were acquired for 59 typically developing children (27 female) aged 9 - 13 years at two time-points approximately 16 months apart (time-point 1: 10.4 {+/-} 0.4 years, time-point 2: 11.7 {+/-} 0.5 years). Whole brain FBA was performed using the connectivity-based fixel enhancement method, to assess longitudinal changes in fibre microscopic density and macroscopic morphological measures, and how these changes are affected by sex, pubertal stage, and pubertal progression. Follow-up analyses were performed in sub-regions of the corpus callosum to confirm the main findings using a Bayesian repeated measures approach.\n\nResultsThere was a statistically significant increase in fibre density over time localised to medial and posterior commissural and association fibres, including the forceps major and bilateral superior longitudinal fasciculus. Increases in fibre cross-section were substantially more widespread. The rate of fibre development was not associated with age or sex. In addition, there was no significant relationship between pubertal stage or progression and longitudinal fibre development over time. Follow-up Bayesian analyses were performed to confirm the findings, which supported the null effect of the longitudinal pubertal comparison.\n\nConclusionUsing a novel longitudinal fixel-based analysis framework, we demonstrate that white matter fibre density and fibre cross-section increased within a 16-month scan rescan period in specific regions. The observed increases might reflect increasing axonal diameter or axon count. Pubertal stage or progression did not influence the rate of fibre development in the early stages of puberty. Future work should focus on quantifying these measures across a wider age range to capture the full spectrum of fibre development across the pubertal period.

neuroscience↗

bioRxiv2017

Age, sex, and puberty related development of the corpus callosum: a multi-technique diffusion MRI study

PurposeThe corpus callosum is integral to the central nervous system, and continually develops with age by virtue of increasing axon diameter and ongoing myelination. Magnetic resonance imaging (MRI) techniques offer a means to disentangle these two aspects of white matter development. We investigate the profile of microstructural metrics across the corpus callosum, and assess the impact of age, sex and pubertal development on these processes.\n\nMethodsThis study made use of two independent paediatric populations. Multi-shell diffusion MRI data were analysed to produce a suite of diffusion tensor imaging (DTI), neurite orientation density and dispersion imaging (NODDI), and apparent fibre density (AFD) metrics. A multivariate profile analysis was performed for each diffusion metric across 10 subdivisions of the corpus callosum.\n\nResultsAll diffusion metrics significantly varied across the length of the corpus callosum. AFD exhibited a strong relationship with age across the corpus callosum (partial{eta} 2 = .65), particularly in the posterior body of the corpus callosum (partial{eta} 2 = .72). In addition, females had significantly higher AFD compared with males, most markedly in the anterior splenium (partial{eta} 2 = .14) and posterior genu (partial{eta} 2 = .13). Age-matched pubertal group differences were localised to the splenium.\n\nConclusionWe present evidence of a strong relationship between apparent fibre density and age, sex, and puberty during development. These results are consistent with ex vivo studies of fibre morphology, providing insights into the dynamics of axonal development in childhood and adolescence using diffusion MRI.\n\nTarget journalsBrain Structure & Function; HBM; NeuroImage; Developmental Cognitive Neuroscience

neuroscience↗

bioRxiv2017

Different Brain Networks Underlying Intelligence In Autism Spectrum Disorders And Typically Developing Children

BackgroundThere has been sustained clinical and cognitive neuroscience research interest in how network correlates of brain-behaviour relationships might be altered in Autism Spectrum Disorders (ASD) and other neurodevelopmental disorders. As previous work has mostly focused on adults, the nature of whole-brain connectivity networks underlying intelligence in pediatric cohorts with abnormal neurodevelopment requires further investigation.\n\nMethodsWe used network-based statistics (NBS) to examine the association between resting-state functional Magnetic Resonance Imaging (fMRI) connectivity and fluid intelligence ability in male children (n=50) with Autism Spectrum Disorders (ASD; M=10.45, SD=1.58 years and in controls (M=10.38, SD=0.96 years) matched on fluid intelligence performance, age and sex. Repeat analyses were performed in independent sites for validation and replication.\n\nResultsDespite being equivalent on fluid intelligence ability to strictly matched neurotypical controls, boys with ASD displayed a subnetwork of significantly increased associations between functional connectivity and fluid intelligence. Between-group differences remained significant at higher edge thresholding, and results were validated in independent-site replication analyses in an equivalent age and sex-matched cohort with ASD. Regions consistently implicated in atypical connectivity correlates of fluid intelligence in ASD were the angular gyrus, posterior middle temporal gyrus, occipital and temporo-occipital regions.\n\nConclusionDevelopment of fluid intelligence neural correlates in young ASD males is aberrant, with an increased strength in intrinsic connectivity association during childhood. Alterations in whole-brain network correlates of fluid intelligence in ASD may be a compensatory mechanism that allows equal task performance to neurotypical peers.

neuroscience↗

bioRxiv2017

Network component analysis reveals developmental trajectories of structural connectivity and specific alterations in autism spectrum disorder

The structural organisation of the brain can be characterised as a hierarchical ensemble of segregated modules linked by densely interconnected hub regions that facilitate distributed functional interactions. Disturbances to this network may be an important marker of abnormal development. Recently, several neurodevelopmental disorders, including autism spectrum disorder (ASD), have been framed as disorders of connectivity but the full nature and timing of these disturbances remain unclear.\n\nIn this study, we use non-negative matrix factorisation, a data-driven, multivariate approach, to model the structural network architecture of the brain as a set of superposed subnetworks, or network components.\n\nIn an openly available dataset of 196 subjects scanned between 5 to 85 years we identify a set of robust and reliable subnetworks that develop in tandem with age and reflect both anatomically local and long-range, network hub connections. In a second experiment, we compare network components in a cohort of 51 high-functioning ASD adolescents to a group of age-matched controls. We identify a specific subnetwork representing an increase in local connection strength in the cingulate cortex in ASD (t=3.44, p<0.001).\n\nThis work highlights possible long-term implications of alterations to the developmental trajectories of specific cortical subnetworks.

neuroscience↗