Biology subjects

Gray, B.

Publications and source records attributed to Gray, B..

4 recordsLinked to original sources

bioRxiv2026

Automated Neuron Tracing with Imitation Learning

Reconstructing neuronal morphology from large 3D microscopy volumes is essential for quantitative neuro-science but remains challenging due to noise, low contrast, and complex branching geometry. We present an automated neuron tracing method that formulates reconstruction as a sequential decision-making problem and trains a 3D convolutional policy via imitation learning. The key technical contribution is an online expert-action retrieval scheme that derives locally valid continuation directions directly from a gold-standard SWC tree, including at bifurcations. Combined with DAgger-style dataset aggregation, the policy is trained under its own state distribution without requiring handcrafted reward functions or a separate segmentation-to-skeleton postprocessing stage. We package the approach into an end-to-end tracing pipeline with optional path refinement operations and tools for quantitative evaluation and interactive editing. On the BigNeuron Gold166 benchmark, our method achieves state-of-the-art reconstruction accuracy, outperforming all competing challenge methods under both morphology-based aggregate metrics and geometric distance comparisons.

neuroscience↗

bioRxiv2025

Spatial genomics of the cardiac sarcomere

Structure-function mapping of proteins has improved our understanding of disease mechanisms and protein domains while human population genetics has provided a window into variational tolerance that can be modeled at a structural level. Here, to reveal novel insight into the cardiac sarcomere, the motor unit of the heart, we develop a novel analytical framework to integrate data from over 17,000 patients with hypertrophic cardiomyopathy (HCM) and combine it with two population-scale genomic databases that incorporate data from more than 800,000 individuals. We integrate in silico genetic predictions of gene variant pathogenicity with 3 dimensional integrative spatial scanning across multiple structural models of cardiac motor proteins. Results reveal both recognized and novel regions of structural variant intolerance across the critical genes of the cardiac sarcomere including novel insights into protein function. We discuss the structural relevance of variant enrichment in the context of sarcomere organization and destabilization of sequestered myosin leading to hypercontractility seen in HCM, by incorporating the recently defined high-resolution structure of human cardiac myosin filament. We extend and validate these findings through pathogenic variant class enrichment and reveal novel associations with the earlier onset of disease in a large clinical cohort. In summary, our study provides a multi-dimensional framework for integrating structural, genomic, and modeling data to reveal novel insight into the cardiac sarcomere.

genomics↗

bioRxiv2025

Validation of Structure Tensor Analysis for Orientation Estimation in Brain Tissue Microscopy

Accurate localization of white matter pathways using diffusion MRI is critical to investigating brain connectivity, but the accuracy of current methods is not thoroughly understood. A fruitful approach to validating accuracy is to consider microscopy data that have been co-registered with MRI of post mortem samples. In this setting, structure tensor analysis is a standard approach to computing local orientations for validation. However, structure tensor analysis itself has not been well-validated and is subject to uncertainty in its angular resolution, and selectivity to specific spatial scales. In this work, we conducted a simulation study to investigate the accuracy of using structure tensors to estimate the orientations of fibers arranged in configurations with and without crossings. We examined a range of simulated conditions, with a focus on investigating the methods behavior on images with anisotropic resolution, which is particularly common in microscopy data acquisition. We also analyzed 2D and 3D optical microscopy data. Our results show that parameter choice in structure tensor analysis has relatively little effect on accuracy for estimating single orientations, although accuracy decreases with anisotropy. On the other hand, when estimating the orientations of crossing fibers, the choice of parameters becomes critical, and poor choices result in orientation estimates that are essentially random. This work provides a set of recommendations for researchers seeking to apply structure tensor analysis effectively in the study of axonal orientations in brain imaging data and quantifies the methods limitations, particularly in the case of anisotropic data. HighlightsO_LIStructure tensor estimates of homogeneous orientations are robust to parameter choice C_LIO_LIAccuracy in crossing-fiber regions is highly sensitive to parameter choice C_LIO_LIImage anisotropy has a large effect on accuracy in 3D images C_LIO_LISimulations provide guidelines for choosing parameters based on image characteristics C_LI

neuroscience↗

bioRxiv2019

Assessment of chemotherapy-induced organ damage with 68Ga-labeled duramycin

Compared to standard toxicological techniques in preclinical toxicity studies, non-invasive imaging of organ toxicity enables fast and longitudinal investigation of the whole animal. Therefore, we set out to evaluate [68Ga]Ga-NODAGA-duramycin as a positron emission tomography (PET)-tracer of cell death for detecting chemotherapy-induced organ toxicity.\n\nMethodsNODAGA-duramycin was radiolabeled with 68Ga, and quality control was done by thin layer chromatography and high performance liquid chromatography. Tracer specificity was determined in vitro by performing competitive binding experiments on ethanol treated cells. To optimize the timing of the PET/CT-based tracer evaluation, kinetic studies were performed in untreated and cisplatin-treated (20 mg/kg BW, intraperitoneal (i.p.)) BALB/cAnNRj mice. Organ uptake was analyzed in doxorubicin (4 mg/kg BW, i.p.)-, busulfan (18.8 mg/kg KG, i.p.)-, and cisplatin-treated (20 mg/kg BW, i.p.) mice, and in untreated control mice 2 hours after intravenous injection of 5-10 MBq [68Ga]Ga-NODAGA-duramycin. For immunofluorescence validation, tissue sections were stained with anti-active caspase-3 antibody. Blood and serum samples were collected to determine platelet count, aspartate transaminase, alanine transaminase, urea, creatinine, and creatine kinase values.\n\nResultsIn vitro experiments confirmed specific binding of [68Ga]Ga-NODAGA-duramycin to dying cells. The biodistribution analysis revealed a blood half-life of 10-17 minutes and a predominantly urinary excretion of the radiotracer. Doxorubicin-, busulfan-, and cisplatin-induced organ toxicities were detected successfully using [68Ga]Ga-NODAGA-duramycin PET/CT and confirmed by immunohistochemistry as well as blood parameter analysis. Busulfan-related spleno-, cardio-, and pneumotoxicity as well as cisplatin-induced cardio- and pneumotoxicity were detected even earlier by [68Ga]Ga-NODAGA-duramycin PET/CT than by blood parameters and histological stainings. In livers and kidneys, differences between treated and untreated animals tended to occur in PET/CT at later time points than in histology due to the relatively high background in these organs. However, trends over time were comparable.\n\nConclusion[68Ga]Ga-NODAGA-duramycin PET/CT was successfully applied to non-invasively detect chemotherapy-induced organ toxicity with high sensitivity in preclinical studies. It even depicted some toxic effects prior to immunohistochemistry and blood parameter analysis and represents a promising alternative or complementary method to standard toxicological analyses. Furthermore, the tracer has a high translational potential and may provide a valuable link between preclinical and clinical research.

pharmacology and toxicology↗