Biology subjects

Matthews, C.

Publications and source records attributed to Matthews, C..

8 recordsLinked to original sources

bioRxiv2026

Sleep-Related Respiratory Disruption is Associated with Altered Spindle Morphology and Poorer Attention in Children

Study ObjectivesTo determine whether sleep-related respiratory disruption is associated with regionally specific alterations in sleep spindle topography and whether hypopnea-sensitive spindle features are associated with attentional performance in children. MethodsWe recorded overnight high-density EEG in children across a wide range of respiratory disruption severity. Slow and fast spindle metrics were extracted per channel, and channel-wise regression models characterized topographic associations with hypopnea index (HI). Cluster-based permutation testing controlled for multiple comparisons. Hierarchically defined regions of interest were tested as predictors of attentional performance on the Test of Variables of Attention (TOVA). ResultsCanonical slow-anterior and fast-posterior spindle organization was detectable across the cohort. Two HI-related topographic effects survived cluster-based permutation correction: higher HI was associated with shortened anterior fast spindle duration and with slower anterior slow spindle peak frequency. In cognitive models, anterior fast spindle duration was the strongest and most consistent predictor of attentional performance, associated with higher signal detection sensitivity, fewer omission errors, and fewer commission errors. By contrast, slow spindle peak frequency showed no attentional associations. ConclusionsPediatric respiratory disruption is associated with regionally specific alterations in spindle morphology rather than global spindle reduction. Shortened anterior fast spindle duration showed convergent respiratory and attentional associations, suggesting that localized spindle integrity may provide a neurophysiological marker of cognitive vulnerability in pediatric sleep-disordered breathing beyond conventional clinical respiratory metrics. HighlightsO_LIHigher hypopnea index was associated with shortened anterior fast spindle duration and slower anterior slow spindle peak frequency C_LIO_LIAnterior fast spindle duration predicted attentional performance in children C_LIO_LIRespiratory disruption may impair attention by disrupting thalamocortical spindle activity C_LI Statement of SignificanceChildren with sleep-disordered breathing can show neurocognitive difficulties that are not well explained by standard respiratory indices alone. This study uses high-density EEG to show that hypopnea burden is associated with regionally specific alterations in sleep spindle morphology, particularly shortened anterior fast spindle duration, rather than a global reduction in spindle occurrence. Anterior fast spindle duration was also the spindle feature most consistently associated with attentional performance. These findings suggest that localized spindle morphology may provide a sleep-neurophysiological readout of cognitive vulnerability in pediatric sleep-disordered breathing. Longitudinal and treatment studies are needed to determine whether spindle duration changes with respiratory improvement and whether such changes track cognitive recovery.

neuroscience↗

bioRxiv2026

Microelectrode arrays enable directional stereo-EEG during kainate-mediated seizures

Surgical planning for drug-resistant epilepsy often relies on stereo-EEG (sEEG) recordings obtained with cylindrical ring electrodes. Prior modeling studies, including lead-field analysis, suggest that microelectrodes distributed around an sEEG-sized insulating body offer superior source amplification and directional sensitivity that are not available with either a ring design or microelectrodes on micro-structures, e.g. Neuropixel. However, these advantages have not been demonstrated in seizure models. This study evaluated high-density sEEG recordings using directional microelectrode arrays in a kainate-mediated rat model (n=6). Two 64-channel microelectrode arrays were implanted near the hippocampus, and the signals were spatially averaged to emulate virtual ring electrodes for comparison. Device locations were reconstructed and placed in copies of the Waxholm Space Rat Brain Atlas registered to subject-specific MRI scans. In subjects exhibiting seizures (n=4), automated line length detection showed that microelectrode signals identified epileptiform activity sooner and with greater specificity than ring electrodes. In subjects that only seized post-kainate injection (n=3), manual review by a board-certified epileptologist confirmed that microelectrodes provided the earliest onset detection times. Furthermore, the microelectrode arrays high resolution revealed distinct instances of hyperactivity occurring at similar depths but from different directions -- a feature indistinguishable to standard ring electrodes. These results demonstrate that microelectrodes on a large insulating body significantly enhance signal quality and spatial localization. This technology offers a potential advancement over current clinical standards for identifying seizure foci during surgical planning. SIGNIFICANCESurgical treatment for drug-resistant epilepsy depends on accurately identifying the brain regions where seizures begin. Current stereo-EEG electrodes sample activity with ring contacts that average signals around the probe shaft, potentially obscuring directional differences in nearby neural activity. This study shows that microelectrodes distributed around an sEEG-sized insulating body can improve seizure-related signal detection and spatial localization compared with ring-like recordings from the same implant locations. By resolving activity that conventional ring electrodes cannot distinguish, high-density directional sEEG may provide more informative recordings for seizure mapping. These findings support the development of next-generation intracranial electrodes for improving epilepsy surgical planning.

neuroscience↗

bioRxiv2025

TNFR2 is Expressed by a Discrete Subset of Epidermal γ δ T Cells with an IL-17 Gene Signature during Psoriasis

Psoriasis is a chronic skin disease that results in scaly patches and affects 2-3% of people worldwide. Therapeutic treatment targets the TNF-/IL-17 axis to disrupt keratinocyte hyperproliferation and inflammation. While more is known about the role of dermal {beta} and {gamma}{delta} T cells in IL-17 production, less is understood about the role of resident epidermal T cells. Here, we examine how TNF- modulates epidermal {gamma}{delta} T cell activation and function. We show that a subset of activated epidermal {gamma}{delta} T cells expresses TNFR2 with or without TNFR1. Stimulation with TNF- induces epidermal {gamma}{delta} T cells to produce IL-17 family cytokines and chemokines. Epidermal {gamma}{delta} T cells do not require TNFR1 or 2 for development or homing to the skin. Instead, TNFR2 plays roles in epidermal {gamma}{delta} T cell function skewing them toward a T{gamma}{delta}17 phenotype during psoriasis. Investigation of the mechanisms by which TNF- associated inflammation impacts epidermal {gamma}{delta} T cell function may help identify new cellular targets for immunotherapy or mark them as early regulators of skin inflammation.

immunology↗

bioRxiv2024

μPIX: Leveraging Generative AI for Enhanced, Personalized and Sustainable Microscopy

Fluorescence microscopy is a critical tool in bio-cellular research, enabling the visualization of biological tissues and cellular structures. However, the inevitable aging of microscopes can degrade their performance posing challenges for long-term scientific investigations. In this study, we introduce {micro}PIX, a personalized deep learning workflow based on a Generative Adversarial Network (GAN) utilizing a Pix2Pix architecture. The network is trained in a supervised manner to denoise images, optimize pre-processing for binary segmentation, and compensate for equipment aging. Our results, evaluated using standard image quality and binary segmentation metrics, demonstrate that {micro}PIX outperforms popular deep learning architectures based on convolutional auto-encoder networks for similar tasks. Additionally, our generative model effectively rejuvenates older detectors to perform on par with newer ones, not only by improving image quality but also by preserving resolution in depth and maintaining a near-linear response between original and generated images in terms of pixel intensity (crucial for quantitative imaging). These findings suggest that generative deep learning approaches can significantly contribute to more sustainable, cost-effective microscopy, fostering continued innovation and discovery in biological research.

bioinformatics↗

bioRxiv2024

Heterogeneous brain region-specific responses to astrocytic mitochondrial DNA damage in mice

Astrocytes use Ca2+ signals to regulate multiple aspects of normal and pathological brain function. Astrocytes display context-specific diversity in their functions, and in their response to noxious stimuli between brain regions. Indeed, astrocytic mitochondria have emerged as key players in governing astrocytic functional heterogeneity, given their ability to dynamically adapt their morphology to regional demands on their ATP generation and Ca2+ buffering functions. Although there is reciprocal regulation between mitochondrial dynamics and mitochondrial Ca2+ signaling in astrocytes, the extent of this regulation into the rich diversity of astrocytes in different brain regions remains largely unexplored. Brain-wide, experimentally induced mitochondrial DNA (mtDNA) loss in astrocytes showed that mtDNA integrity is critical for proper astrocyte function, however, few insights into possible diverse responses to this noxious stimulus from astrocytes in different brain areas were reported in these experiments. To selectively damage mtDNA in astrocytes in a brain-region-specific manner, we developed a novel adeno-associated virus (AAV)-based tool, Mito-PstI, which expresses the restriction enzyme PstI, specifically in astrocytic mitochondria. Here, we applied Mito-PstI to two distinct brain regions, the dorsolateral striatum, and the hippocampal dentate gyrus, and we show that Mito-PstI can induce astrocytic mtDNA loss in vivo, but with remarkable brain-region-dependent differences on mitochondrial dynamics, spontaneous Ca2+ fluxes and astrocytic as well as microglial reactivity. Thus, AAV-Mito-PstI is a novel tool to explore the relationship between astrocytic mitochondrial network dynamics and astrocytic mitochondrial Ca2+ signaling in a brain-region-selective manner.

neuroscience↗

bioRxiv2020

The buds of Oscarella lobularis (Porifera): a new convenient model for sponge cell and developmental biology

The comparative study of the four non-bilaterian phyla (Cnidaria, Placozoa, Ctenophora, Porifera) should provide insights into the origin of bilaterian traits. Except for Cnidaria, present knowledge on the cell biology and development of these animals is so far limited. Non-bilaterian models are needed to get further into cell architecture and molecular mechanisms. Given the developmental, histological, ecological and genomic differences between the four sponge classes, we develop a new sponge model: the buds of the Oscarella lobularis (class Homoscleromorpha). This experimental model supplements the two other most famous sponge models Amphimedon queenslandica and Ephydatia muelleri, both belonging to the class Demospongiae. Budding is a natural and spontaneous asexual reproduction mean, but budding can be triggered in vitro ensuring availability of biological material all year long. We provide a full description of buds, from their formation to their development into juveniles. Their transparency enables fluorescent and live imaging, and their abundance allows for experimental replicates. Moreover, regeneration and cell reaggregation capabilities provide interesting experimental morphogenetic contexts. The numerous techniques now mastered on these buds make it a new suitable sponge model. Summary statementStudying sponge biology is needed to understand the evolution of metazoans. We developed a new model suitable for experimental biology that allows to study morphogenetic processes with modern tools.

zoology↗

bioRxiv2019

Bayesian Modeling Reveals Ultrasensitivity Underlying Metabolic Compensation in the Cyanobacterial Circadian Clock

Mathematical models can enable a predictive understanding of mechanism in cell biology by quantitatively describing complex networks of interactions, but such models are often poorly constrained by available data. Owing to its relative biochemical simplicity, the core circadian oscillator in Synechococcus elongatus has become a prototypical system for studying how collective dynamics emerge from molecular interactions. The oscillator consists of only three proteins, KaiA, KaiB, and KaiC, and near-24-h cycles of KaiC phosphorylation can be reconstituted in vitro. Here, we formulate a molecularly-detailed but mechanistically agnostic model of the KaiA-KaiC subsystem and fit it directly to experimental data within a Bayesian parameter estimation framework. Analysis of the fits consistently reveals an ultrasensitive response for KaiC phosphorylation as a function of KaiA concentration, which we confirm experimentally. This ultrasensitivity primarily results from the differential affinity of KaiA for competing nucleotide-bound states of KaiC. We argue that the ultrasensitive stimulus-response relation is critical to metabolic compensation by suppressing premature phosphorylation at nighttime. SynopsisThis study takes a data-driven kinetic modeling approach to characterizing the interaction between KaiA and KaiC in the cyanobacterial circadian oscillator and understanding how the oscillator responds to changes in cellular metabolic conditions. O_LIAn extensive dataset of KaiC autophosphorylation measurements was gathered and fit to a detailed yet mechanistically agnostic kinetic model within a Bayesian parameter estimation framework. C_LIO_LIKaiA concentration tunes the sensitivity of KaiC autophosphorylation and the period of the full oscillator to %ATP. C_LIO_LIThe model reveals an ultrasensitive dependence of KaiC phosphorylation on KaiA concentration as a result of differential KaiA binding affinity to ADP- vs. ATP-bound KaiC. C_LIO_LIUltrasensitivity in KaiC phosphorylation contributes to metabolic compensation by suppressing premature phosphorylation at nighttime. C_LI

systems biology↗

bioRxiv2019

Killer whale genomes reveal a complex history of recurrent admixture and vicariance

Reconstruction of the demographic and evolutionary history of populations assuming a consensus tree-like relationship can mask more complex scenarios, which are prevalent in nature. An emerging genomic toolset, which has been most comprehensively harnessed in the reconstruction of human evolutionary history, enables molecular ecologists to elucidate complex population histories. Killer whales have limited extrinsic barriers to dispersal and have radiated globally, and are therefore a good candidate model for the application of such tools. Here, we analyse a global dataset of killer whale genomes in a rare attempt to elucidate global population structure in a non-human species. We identify a pattern of genetic homogenisation at lower latitudes and the greatest differentiation at high latitudes, even between currently sympatric lineages. The processes underlying the major axis of structure include high drift at the edge of species range, likely associated with founder effects and allelic surfing during post-glacial range expansion. Divergence between Antarctic and non-Antarctic lineages is further driven by ancestry segments with up to four-fold older coalescence time than the genome-wide average; relicts of a previous vicariance during an earlier glacial cycle. Our study further underpins that episodic gene flow is ubiquitous in natural populations, and can occur across great distances and after substantial periods of isolation between populations. Thus, understanding the evolutionary history of a species requires comprehensive geographic sampling and genome-wide data to sample the variation in ancestry within individuals.

evolutionary biology↗