Biology subjects

Rutherford, M. A.

Publications and source records attributed to Rutherford, M. A..

15 recordsLinked to original sources

bioRxiv2025

Heat-shock pathway activation by TRC051384 protects spiral ganglion neurons from noise-induced hearing loss

Noise-induced hearing loss (NIHL) is a major public health problem caused by damage to cochlear hair cells, synapses, and spiral ganglion neurons (SGNs). Since effective treatments are lacking, we investigated cellular stress responses induced by moderate and loud noise in a mouse model of cochlear synaptopathy. RNA sequencing and spatial transcriptomics revealed that noise exposure elicited a robust but transient upregulation of endoplasmic reticulum chaperones and proteasome subunits in SGNs and their supporting cells. To target this response, we administered TRC051384, a small-molecule activator of the heat shock transcription factor Hsf1, prior to noise exposure. TRC051384 crossed the blood-labyrinth barrier and reached the cochlea, induced heat shock protein gene expression, and restored ubiquitin-proteasome function in SGNs. Notably, TRC051384 treatment enhanced auditory brainstem response threshold recovery, preserved Wave I amplitudes, and maintained ribbon synapse density. These findings establish proteotoxic stress in SGNs as a key driver of NIHL and identify HSF1 activation as a promising therapeutic strategy.

neuroscience↗

bioRxiv2025

Persistence of vestibular function in the absence of glutamatergic transmission from hair cells

Quantal synaptic transmission in vestibular end-organs is glutamatergic. Although genetic deletion of Slc17a8 (termed Vglut3) leads to deafness in mice, the dependence of vestibular function on VGLUT3-mediated quantal transmission is unknown. Here, we investigated the vestibular phenotype of Vglut3-/- mice at the cellular, systems, and behavioral levels. The type-II vestibular hair cells (VHCs) in Vglut3+/+mice were strongly immunoreactive for VGLUT3, while type-I VHCs showed poor immunoreactivity. In Vglut3-/- mice quantal synaptic transmission in utricular calyces was reduced in rate and amplitude by > 95%. In vivo recordings of spontaneous activity in the vestibular nerve revealed similar action potential rates and regularity in Vglut3+/+and Vglut3-/- mice, suggesting a divergent underlying mechanism compared to the silent Vglut3-/- auditory nerve. In behavioral studies, Vglut3-/- mice did not exhibit considerable sensorimotor or balance deficits. Collectively, these data support the view that non-quantal transmission is the predominant mode of neurotransmission between type I VHCs and vestibular calyceal afferent neurons. We propose that non-quantal transmission alone underlies the apparently normal vestibular nerve physiology and behavioral function in Vglut3-/- mice.

neuroscience↗

bioRxiv2024

Female mice lacking GluA3 show early onset of hearing loss, synaptopathy, and afferent swellings in ambient sound levels

AMPA-type glutamate receptors (AMPAR) mediate excitatory cochlear transmission. However, the unique roles of AMPAR subunits are unresolved. Lack of subunit GluA3 (Gria3KO) in male mice reduced cochlear output by 8-weeks of age. Since Gria3 is X-linked and considering sex differences in hearing vulnerability, we hypothesized accelerated presbycusis in Gria3KO females. Here, auditory brainstem responses (ABR) were similar in 3-week-old female Gria3WTand Gria3KO mice. However, when raised in ambient sound, ABR thresholds were elevated and wave-1 amplitudes were diminished at 5-weeks and older in Gria3KO. In contrast, these metrics were similar between genotypes when raised in quiet. Paired synapses were similar in number, but lone ribbons and ribbonless synapses were increased in female Gria3KOmice in ambient sound compared to Gria3WT or to either genotype raised in quiet. Synaptic GluA4:GluA2 ratios increased relative to Gria3WT, particularly in ambient sound, suggesting an activity-dependent increase in calcium-permeable AMPARs in Gria3KO. Swollen afferent terminals were observed by 5-weeks only in Gria3KO females reared in ambient sound. We propose that lack of GluA3 induces sex-dependent vulnerability to AMPAR-mediated excitotoxicity.

neuroscience↗

bioRxiv2023

BOUNTI: Brain vOlumetry and aUtomated parcellatioN for 3D feTal MRI

Fetal MRI is widely used for quantitative brain volumetry studies. However, currently, there is a lack of universally accepted protocols for fetal brain parcellation and segmentation. Published clinical studies tend to use different segmentation approaches that also reportedly require significant amounts of time-consuming manual refinement. In this work, we propose to address this challenge by developing a new robust deep learning-based fetal brain segmentation pipeline for 3D T2w motion corrected brain images. At first, we defined a new refined brain tissue parcellation protocol with 19 regions-of-interest using the new fetal brain MRI atlas from the Developing Human Connectome Project. This protocol design was based on evidence from histological brain atlases, clear visibility of the structures in individual subject 3D T2w images and the clinical relevance to quantitative studies. It was then used as a basis for developing an automated deep learning brain tissue parcellation pipeline trained on 360 fetal MRI datasets with different acquisition parameters using semi-supervised approach with manually refined labels propagated from the atlas. The pipeline demonstrated robust performance for different acquisition protocols and GA ranges. Analysis of tissue volumetry for 390 normal participants (21-38 weeks gestational age range), scanned with three different acquisition protocols, did not reveal significant differences for major structures in the growth charts. Only minor errors were present in < 15% of cases thus significantly reducing the need for manual refinement. In addition, quantitative comparison between 65 fetuses with ventriculomegaly and 60 normal control cases were in agreement with the findings reported in our earlier work based on manual segmentations. These preliminary results support the feasibility of the proposed atlas-based deep learning approach for large-scale volumetric analysis. The created fetal brain volumetry centiles and a docker with the proposed pipeline are publicly available online at https://hub.docker.com/r/fetalsvrtk/segmentation (tag brain bounti tissue).

neuroscience↗

bioRxiv2022

Comprehensive volumetric phenotyping of the neonatal brain in Down syndrome.

Down syndrome (DS) is the most common genetic cause of intellectual disability with a wide spectrum of neurodevelopmental outcomes. Magnetic resonance imaging (MRI) has been used to investigate differences in whole and/or regional brain volumes in DS from infancy to adulthood. However, to date, there have been relatively few in vivo neonatal brain imaging studies in DS, despite the presence of clearly identifiable characteristics at birth. Improved understanding of early brain development in DS is needed to assess phenotypic severity and identify appropriate time windows for early intervention. In this study, we used in vivo brain MRI to conduct a comprehensive volumetric phenotyping of the neonatal brain in DS. Using a robust cross-sectional reference sample of close to 500 preterm- to term-born control neonates, we have performed normative modelling and quantified volumetric deviation from the normative mean in 25 individual infants with DS [postmenstrual age at scan, median (range) = 40.57 (32.43 - 45.57) weeks], corrected for sex, age at scan and age from birth. We found that absolute whole brain volume was significantly reduced in neonates with DS (pFDR <0.0001), as were most underlying absolute tissue volumes, except for the lentiform nuclei and the extracerebral cerebrospinal fluid (eCSF), which were not significantly different, and the lateral ventricles, which were significantly enlarged (pFDR <0.0001). Relative volumes, adjusting for underlying differences in whole brain volume, revealed a dynamic shift in brain proportions in neonates with DS. In particular, the cerebellum, as well as the cingulate, frontal, insular and occipital white matter (WM) segments were significantly reduced in proportion (pFDR <0.0001). Conversely, deep grey matter (GM) structures, such as the thalami and lentiform nuclei, as well as CSF-filled compartments, such as the eCSF and the lateral ventricles were significantly enlarged in proportion (pFDR <0.0001). We also observed proportionally reduced frontal and occipital lobar volumes, in contrast with proportionally enlarged temporal and parietal lobar volumes. Lastly, we noted age-related volumetric differences between neonates with and without a congenital heart defect (CHD), indicating that there may be a baseline brain phenotype in neonates with DS, which is further altered in the presence of CHD. In summary, we provide a comprehensive volumetric phenotyping of the neonatal brain in DS and observe many features that appear to follow a developmental continuum, as noted in older age cohorts. There are currently no paediatric longitudinal neuroimaging investigations in DS, starting from the earliest time points, which greatly impedes our understanding of the developmental continuum of neuroanatomical parameters in DS. Whilst life expectancy of individuals with DS has greatly improved over the last few decades, early interventions may be essential to help improve outcomes and quality of life. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC="FIGDIR/small/510205v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@15cc92aorg.highwire.dtl.DTLVardef@9af99dorg.highwire.dtl.DTLVardef@79b7dborg.highwire.dtl.DTLVardef@115adfc_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2022

Postsynaptic GluA3 subunits are required for the appropriate assembly of AMPA receptor GluA2 and GluA4 subunits on mammalian cochlear afferent synapses and for presynaptic ribbon modiolar-pillar morphological distinctions

The encoding of acoustic signals in the cochlea depends on -amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptors (AMPARs), but relatively little is known about their reliance on specific pore-forming subunits. With 5-week-old male GluA3KO mice, we determined cochlear function, synapse ultrastructure, and AMPAR subunit molecular anatomy at ribbon synapses between inner hair cells (IHCs) and spiral ganglion neurons (SGNs). GluA3KO and wild-type (GluA3WT) mice reared in ambient sound pressure level (SPL) of 55-75 dB had similar ABR thresholds, wave-1 amplitudes, and latencies. Ultrastructurally, the IHC modiolar-pillar differences in presynaptic ribbon size and shape, and synaptic vesicle size seen in GluA3WT were diminished or reversed in GluA3KO. The quantity of paired synapses (presynaptic ribbons juxtaposed with postsynaptic GluA2 and GluA4) was similar, however, GluA2-lacking synapses (ribbons paired with GluA4 but not GluA2) were observed only in GluA3KO. SGNs of GluA3KO mice had AMPAR arrays of smaller overall volume, containing less GluA2 and greater GluA4 immunofluorescence intensity relative to GluA3WT (3-fold difference in mean GluA4:GluA2 ratio). The expected modiolar-pillar gradient in ribbon volume was observed in IHCs of GluA3WT but not GluA3KO. Unexpected modiolar-pillar gradients in GluA2 and GluA4 volume were present in GluA3KO. GluA3 is essential to the morphology and molecular composition of IHC-ribbon synapses. We propose the hearing loss seen in older male GluA3KO mice results from progressive synaptopathy evident in 5-week-old mice as increased abundance of GluA2-lacking, GluA4 monomeric, Ca2+-permeable AMPARs.

neuroscience↗

bioRxiv2022

3D MRI atlases of congenital aortic arch anomalies and normal fetal heart: application to automated multi-label segmentation

Background3D image-domain reconstruction of black blood contrast T2w SSTSE fetal MRI datasets using slice-to-volume registration methods showed to provide high-resolution 3D images of the heart with superior visualisation of fetal aortic arch anomalies [1]. However, there is a lack of formalisation of the MRI appearance of fetal cardiovascular anatomy and standardisation of vessel segmentation protocols. MethodsIn this work, we present the first set of 3D fetal MRI atlases defining normal and abnormal fetal aortic arch anatomy created from 3D reconstructed images from 87 subjects scanned between 29-34 weeks of gestation with postnatally confirmed outcomes. We also implement and evaluate atlas-guided registration and deep learning (UNETR) methods for automated 3D multi-label fetal heart vessel segmentation. ResultsWe created four atlases representing the average anatomy of the normal fetal heart, coarctation of the aorta, right aortic arch and suspected double aortic arch. Inspection of atlases confirmed the expected pronounced differences in the anatomy of the aortic arch. The results of the multi-label heart vessel UNETR segmentation showed 100% per-vessel detection rate for both normal and abnormal aortic arch anatomy. ConclusionsThis work introduces the first set of 3D black blood T2w MRI atlases of the normal and abnormal fetal cardiovascular anatomy along with detailed segmentation of the major cardiovascular structures. We also demonstrated the feasibility of using deep learning for multi-label vessel segmentation.

bioinformatics↗

bioRxiv2021

Automated 3D reconstruction of the fetal thorax in the standard atlas space from motion-corrupted MRI stacks for 21-36 weeks GA range

Slice-to-volume registration (SVR) methods allow reconstruction of high-resolution 3D images from multiple motion-corrupted stacks. SVR-based pipelines have been increasingly used for motion correction for T2-weighted fetal MRI since they allow more informed and detailed diagnosis of brain and body anomalies including congenital heart defects (Lloyd et al., 2019). Recently, fully automated rigid SVR reconstruction of the fetal brain in the atlas space was achieved in (Salehi et al., 2019) that used convolutional neural networks (CNNs) for segmentation and pose estimation. However, these CNN-based methods have not yet been applied to the fetal trunk region. Meanwhile, the existing rigid and deformable SVR (DSVR) solutions (Uus et al., 2020) for the fetal trunk region are limited by the requirement of manual input as well the narrow capture range of the classical gradient descent based registration methods that cannot resolve severe fetal motion frequently occurring at the early gestational age (GA). Furthermore, in our experience, the conventional 2D slice-wise CNN-based brain masking solutions are reportedly prone to errors that require manual corrections when applied on a wide range of acquisition protocols or abnormal cases in clinical setting. In this work, we propose a fully automated pipeline for reconstruction of the fetal thorax region for 21-36 weeks GA range T2-weighted MRI datasets. It includes 3D CNN-based intra-uterine localisation of the fetal trunk and landmark-guided pose estimation steps that allow automated DSVR reconstruction in the standard radiological space irrespective of the fetal trunk position or the regional stack coverage. The additional step for generation of the common template space and rejection of outliers provides the means for automated exclusion of stacks affected by low image quality or extreme motion. The pipeline was evaluated on a series of experiments including fetal MRI datasets and simulated rotation motion. Furthermore, we performed a qualitative assessment of the image reconstruction quality in terms of the definition of vascular structures on 100 early (median 23.14 weeks) and late (median 31.79 weeks) GA group MRI datasets covering 21 to 36 weeks GA range.

bioinformatics↗

bioRxiv2021

Multi-channel 4D parametrized Atlas of Macro- and Microstructural Neonatal Brain Development

Structural and diffusion MRI provide complimentary anatomical and microstructural characterization of early brain maturation. The existing models of the developing brain in time include only either structural or diffusion channels. Furthermore, there is a lack of tools for combined analysis of structural and diffusion MRI in the same reference space. In this work we propose methodology to generate multi-channel (MC) continuous spatio-temporal parametrized atlas of brain development based on MC registration driven by both T2-weighted and orientation distribution functions (ODF) channels along with the Gompertz model (GM) fitting of the signals and spatial transformations in time. We construct a 4D MC atlas of neonatal brain development during 38 to 44 week PMA range from 170 normal term subjects from developing Human Connectomme Project. The resulting atlas consists of fourteen spatio-temporal microstructural indices and two parcellation maps delineating white matter tracts and neonatal transient structures. We demonstrate applicability of the atlas for quantitative region-specific comparison of 140 term and 40 preterm subjects scanned at the term-equivalent age. We show multi-parametric microstructural differences in multiple white matter regions, including the transient compartments. The atlas and software will be available after publication of the article.

neuroscience↗

bioRxiv2020

Individualized characterization of volumetric development in the preterm brain

The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process regression to create normative curves characterising brain volumetric development in 274 term-born infants, modelling for age at scan and sex. We then compared 89 preterm infants scanned at termequivalent age to these normative charts, relating individual deviations from typical volumetric development to perinatal risk factors and later neurocognitive scores. To test generalisability, we used a second independent dataset comprising of 253 preterm infants scanned using different acquisition parameters and scanner. We describe rapid, non-uniform brain growth during the neonatal period. In both preterm cohorts, cerebral atypicalities were widespread, often multiple, and varied highly between individuals. Deviations from normative development were associated with respiratory support, nutrition, birth weight, and later neurocognition, demonstrating their clinical relevance. Group-level understanding of the preterm brain disguise a large degree of individual differences. We provide a method and normative dataset that offer a more precise characterisation of the cerebral consequences of preterm birth by profiling the individual neonatal brain.

neuroscience↗

bioRxiv2019

Fetal whole-heart 4D flow cine MRI using multiple non-coplanar balanced SSFP stacks

PurposeTo develop an MRI framework for reconstruction of 4D velocity vector blood flow volumes for visualisation and quantification of circulation in the fetal heart and major vessels.\n\nMethodsA novel method of velocity-encoding using multiple non-coplanar stacks of bSSFP phase images was combined with a previous framework for reconstruction of motion-corrected 4D magnitude cine volumes to generate spatiotemporally-paired 4D flow cine volumes of the fetal circulatory system. The multiple stack velocity-encoding scheme was validated in a simulated flow phantom and compared with a gold-standard method for velocity-encoding in a physical flow phantom. The 4D flow cine framework was evaluated in seven fetal subjects. Reconstructed 4D flow volumes were evaluated by an expert fetal cardiologist and preliminary flow measurements were taken in various major vessels of the heart.\n\nResultsPhantom experiments showed that the multiple non-coplanar stack velocity-encoding scheme was accurate. The 4D flow cine reconstruction framework was robust in fetal subjects and generated multi-dimensional velocity vector maps of blood flow through the cardiac cycle. Directionality of blood flow was consistent with expected fetal circulatory hemodynamics. Relative blood flow rates in the major vessels were in line with previous observations, although absolute values were underestimated by a factor of approximately two due to limitations of spatial and temporal resolution.\n\nConclusion4D flow cine volumes can be reconstructed from multiple non-coplanar stacks of slices. The proposed framework was used to visualise and quantify flow through the whole fetal heart and great vessels, but is applicable to any imaging scenario where motion is a major challenge.

bioengineering↗

bioRxiv2018

Abnormal microstructural development of the cerebral cortex in neonates with congenital heart disease is associated with impaired cerebral oxygen delivery

BackgroundAbnormal macrostructural development of the cerebral cortex has been associated with hypoxia in infants with congenital heart disease (CHD). Animal studies have suggested that hypoxia results in cortical dysmaturation at the cellular level. New magnetic resonance imaging (MRI) techniques offer the potential to investigate the relationship between cerebral oxygen delivery and microstructural development of the cortex in newborn infants with CHD.\n\nMethodsWe measured macrostructural and microstructural properties of the cortex in 48 newborn infants with complex CHD and 48 age-matched healthy controls. Cortical volume and gyrification index were calculated from high resolution structural MRI. Neurite density and orientation dispersion indices were modelled using high angular resolution diffusion MRI. Cerebral oxygen delivery was estimated in infants with CHD using phase contrast MRI and pre-ductal pulse oximetry. We used tract-based spatial statistics to examine voxel-wise group differences in cortical microstructure.\n\nResultsMicrostructural development of the cortex was abnormal in 48 infants with CHD, with regions of increased fractional anisotropy (FA) and reduced orientation dispersion index (ODI) compared to 48 healthy controls, correcting for gestational age at birth and scan (FWE-corrected for multiple comparisons at P<0.05). Regions of reduced cortical ODI in infants with CHD were related to impaired cerebral oxygen delivery (R2=0.637, n=39). Cortical ODI was associated with gyrification index (R2=0.589, P<0.0001, n=48).\n\nConclusionsThis study suggests that the primary component of cerebral cortex dysmaturation in CHD is impaired dendritic arborisation, which may underlie abnormal macrostructural findings reported in this population. The degree of impairment was related to cerebral oxygen delivery, supporting the hypothesis that maternal oxygen therapy may be beneficial in this population.

neuroscience↗

bioRxiv2018

Higher order spherical harmonics reconstruction of fetal diffusion MRI with intensity correction

We present a comprehensive method for reconstruction of fetal diffusion MRI signal using a higher order spherical harmonics representation, that includes motion, distortion and intensity correction. By applying constrained spherical deconvolution and whole brain tractography to reconstructed fetal diffusion MRI we are able to identify main WM tracts and anatomically plausible fiber crossings. The proposed methodology facilitates detailed investigation of developing brain connectivity and microstructure in-utero.

neuroscience↗

bioRxiv2018

Unbiased construction of a temporally consistent morphological atlas of neonatal brain development

Premature birth increases the risk of developing neurocognitive and neurobe-havioural disorders. The mechanisms of altered brain development causing these disorders are yet unknown. Studying the morphology and function of the brain during maturation provides us not only with a better understanding of normal development, but may help us to identify causes of abnormal development and their consequences. A particular difficulty is to distinguish abnormal patterns of neurodevelopment from normal variation. The Developing Human Connectome Project (dHCP) seeks to create a detailed four-dimensional (4D) connectome of early life. This connectome may provide insights into normal as well as abnormal patterns of brain development. As part of this project, more than a thousand healthy fetal and neonatal brains will be scanned in vivo. This requires computational methods which scale well to larger data sets. We propose a novel groupwise method for the construction of a spatio-temporal model of mean morphology from cross-sectional brain scans at different gestational ages. This model scales linearly with the number of images and thus improves upon methods used to build existing public neonatal atlases, which derive correspondence between all pairs of images. By jointly estimating mean shape and longitudinal change, the atlas created with our method overcomes temporal inconsistencies, which are encountered when mean shape and intensity images are constructed separately for each time point. Using this approach, we have constructed a spatio-temporal atlas from 275 healthy neonates between 35 and 44 weeks post-menstrual age (PMA). The resulting atlas qualitatively preserves cortical details significantly better than publicly available atlases. This is moreover confirmed by a number of quantitative measures of the quality of the spatial normalisation and sharpness of the resulting template brain images.

neuroscience↗

bioRxiv2017

The Developing Human Connectome Project: a Minimal Processing Pipeline for Neonatal Cortical Surface Reconstruction

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity.

neuroscience↗