Biology subjects

Roche, A.

Publications and source records attributed to Roche, A..

5 recordsLinked to original sources

bioRxiv2026

Analytic Bounds on GAMLSS Model Variability of Normative White Matter Brain Charts

Brain charts, or normative models of quantitative neuroimaging measures, can identify trajectories of brain development and abnormalities in groups and individuals by leveraging large populations. Recent work has extended these brain charts to model microstructural and macrostructural features of white matter. Assessments of variance for these brain charts are necessary to determine whether the models being used for these data are stable. We implement an analytic approach to characterize variability of the parameters in previously released brain charts created using the generalized additive models for location, scale, and shape (GAMLSS) framework. Additionally, we empirically validate the accuracy of each analytic model through a comparison to a bootstrapping approach from 0.2 to 90 years of age. We find that across all models, the analytic coefficient of variation (COV) remains below 5% for ages greater than 0.25 years, with the maximum empirical observed COV reaching 7% at 0.2 years of age. Further, the empirical assessment shows high agreement with the analytic assessment, with COV estimates averaged across the lifespan for all models having a Pearson correlation coefficient of 0.776 and a mean difference of 4 x 10-4. Both methods exhibit volume and surface area as the features with the largest average COV for the majority of tracts. However, the analytic assessment yields axial diffusivity as the feature most frequently having the smallest COV, whereas the corresponding feature for the empirical assessment is average length. These results suggest that the analytic approach overestimates model stability for WM brain charts when the COV is low and that the validation method is suitable for assessing whether GAMLSS models are unstable.

bioengineering↗

bioRxiv2025

Neuromodulation of a peripheral nerve using fully polymeric cuff electrodes: Understanding predictability of selective stimulation

Peripheral nerve stimulation (PNS) offers therapeutic benefits across numerous clinical applications but suffers from limitations in high resolution spatial selectivity, especially in mixed nerves. This study presents a fully polymeric, transverse, multipolar nerve cuff made from a conductive elastomer (CE), designed for selective activation of individual fascicles. Fabricated with laser-based manufacturing techniques, the CE nerve cuff offers mechanical conformity and high charge injection capacity. Ex vivo experiments on the rat sciatic nerve demonstrate reliable compound action potential recordings and fascicular selectivity (SI > 0.65). The non-metal electrodes enable microCT-aided 3D reconstruction of nerve-electrode geometries without imaging artefacts, informing anatomically accurate simulations via the ASCENT pipeline. While in silico simulations predict some selective fascicular activation, discrepancies were observed between predicted and experimental selectivity magnitudes and electrode positions, particularly for the sural and tibial fascicles. The model was more sensitive to neuroanatomical variation than the experimental data, indicating limitations in current perineurium and CE electrode modelling assumptions. This work validates CE-based cuffs as viable alternatives to metallic devices for selective fascicular peripheral nerve activation and highlights the potential of imaging-informed simulations to optimize nerve interface design. Future improvements in electrode and nerve tissue modelling are needed to enhance in silico prediction accuracy and further advance spatially selective PNS technologies.

bioengineering↗

bioRxiv2025

Lifespan Trajectories of Asymmetry in White Matter Tracts

Asymmetry in white matter is believed to give rise to the brains capacity for specialized processing and is involved in the lateralization of various cognitive processes, such as language and visuo-spatial reasoning. Although studies of white matter asymmetry have been previously documented, they have often been constrained by limited age ranges, sample sizes, or the scope of the tracts and structural features examined. While normative lifespan charts for brain structures are emerging, comprehensive charts detailing white matter asymmetries across numerous pathways and diverse structural measures have been notably absent. This study addresses this gap by leveraging a large-scale dataset of 35,120 typically developing and aging individuals, ranging from 0 to 100 years of age, from 50 primary neuroimaging studies. We generated comprehensive lifespan trajectories for 30 lateralized association and projection white matter tracts, examining 6 distinct microstructural and macrostructural features of these pathways. Our findings reveal that: (1) asymmetries are widespread across the brains white matter and are present in all 30 pathways; (2) for a given pathway, the degree and direction of asymmetry differ between features of tissue microstructure and pathway macrostructure; (3) asymmetries vary across and within pathway types (association and projection tracts); and (4) these asymmetries are not static, following unique trajectories across the lifespan, with distinct changes during development, and a general trend of becoming more asymmetric with increasing age (particularly in later adulthood) across pathways. This study represents the most extensive characterization of white matter asymmetry across the lifespan to date, charting how lateralization patterns emerge, mature, and change throughout life. It provides a foundational resource for understanding the principles of white matter organization from early to late life, its relation to functional specialization and inter-individual variability, and offers a key reference for interpreting deviations during healthy development and aging as well as those associated with clinical populations.

neuroscience↗

bioRxiv2025

AURKA inhibition amplifies DNA replication stress to foster WEE1 kinase dependency and synergistic antitumor effects with WEE1 inhibition in cancers

Highly elevated expression of the oncogene Aurora kinase A (AURKA) occurs in numerous human cancers harboring defective p53, nominating AURKA as a potential vulnerability in TP53-mutated cancer. However, clinical trials have indicated modest monotherapy activity of AURKA inhibitors. Here, we demonstrate that AURKA inhibition promotes phosphorylation of Replication Protein A (RPA), resulting in stalled DNA replication fork progression and eliciting a replication stress response in multiple TP53-mutated models, creating a druggable dependence on the mitotic checkpoint kinase WEE1. Combined inhibition of AURKA and WEE1 synergistically enhanced replication stress, tumor-specific apoptotic cell death, and mitotic catastrophe, and lead to marked tumor regression in cell line- and patient-derived xenograft models of TP53-mutated cancer. Our findings define enhanced DNA replication stress as underlying the strong synergy between AURKA and WEE1 inhibitors and offer preclinical confirmation of efficacy, indicating high potential for clinical translation of this synthetic lethal strategy for TP53-mutated carcinomas. Statement of significanceWe demonstrate that a small molecule AURKA inhibitor amplifies DNA replication stress in TP53-mutated carcinomas. This amplification of DNA replication stress can be leveraged this for synthetic lethal therapy in a combination with WEE1 inhibition that enhances antitumor effects in in vitro, in xenografts and in patient-derived xenograft models, advancing a promising novel combination therapy.

cancer biology↗

bioRxiv2025

White matter microstructure and macrostructure brain charts across the human lifespan

Normative reference charts are widely used in healthcare, especially for assessing the development of individuals by benchmarking anatomic and physiological features against population trajectories across the lifespan. Recent work has extended this concept to gray matter morphology in the brain, but no such reference framework currently exists for white matter (WM) even though WM constitutes the essential substrate for neuronal communication and large-scale network integration. Here, we present the first comprehensive WM brain charts, which describe how microstructural and macrostructural features of WM evolve across the lifespan, by leveraging over 35,120 diffusion MRI scans from 50 harmonized studies. Using generalized additive models for location, scale, and shape (GAMLSS), we estimate age- and sex-stratified trajectories for 72 individual white matter pathways, quantifying both tract-specific microstructural and morphometric features. We demonstrate that these WM brain charts enable four important applications: (1) defining normative trajectories of WM maturation and decline across distinct pathways, (2) identifying previously uncharacterized developmental milestones and spatial gradients of tract maturation, (3) detecting individualized deviations from normative patterns with clinical relevance across multiple neurological disorders, and (4) facilitating standardized, cross-study centile scoring of new datasets. By establishing a unified, interpretable reference framework for WM structure, these brain charts provide a foundational metric for research and clinical neuroscience. The accompanying open-access trajectories, centile scoring tools, and harmonization methods facilitate precise mapping of WM development, aging, and pathology across diverse populations. We release the brain charts and provide an out-of-sample alignment process as a Docker image: https://zenodo.org/records/17561821.

neuroscience↗