Biology subjects

Heyn, C.

Publications and source records attributed to Heyn, C..

3 recordsLinked to original sources

bioRxiv2022

Sensitivity of diffusion-tensor and correlated diffusion imaging to white-matter microstructural abnormalities: application in COVID-19

There has been growing attention on the effect of COVID-19 on white-matter microstructure, especially among those that self-isolated after being infected. There is also immense scientific interest and potential clinical utility to evaluate the sensitivity of single-shell diffusion MRI methods for detecting such effects. In this work, the sensitivities of three single-shell-compatible diffusion MRI modeling methods are compared for detecting the effect of COVID-19, including diffusion-tensor imaging, diffusion-tensor decomposition of orthogonal moments and correlated diffusion imaging. Imaging was performed on self-isolated patients at baseline and 3-month follow-up, along with age- and sex-matched controls. We demonstrate through simulations and experimental data that correlated diffusion imaging is associated with far greater sensitivity, being the only one of the three single-shell methods to demonstrate COVID-19-related brain effects. Results suggest less restricted diffusion in the frontal lobe in COVID-19 patients, but also more restricted diffusion in the cerebellar white matter, in agreement with several existing studies highlighting the vulnerability of the cerebellum to COVID-19 infection. These results, taken together with the simulation results, suggest that a significant proportion of COVID-19 related white-matter microstructural pathology manifests as a change in water diffusivity. Interestingly, different b-values also confer different sensitivities to the effects. No significant difference was observed in patients at the 3-month follow-up, likely due to the limited size of the follow-up cohort. To summarize, correlated diffusion imaging is shown to be a sensitive single-shell diffusion analysis approach that allows us to uncover opposing patterns of diffusion changes in the frontal and cerebellar regions of COVID-19 patients, suggesting the two regions react differently to viral infection.

biophysics↗

bioRxiv2021

Deep Bayesian networks for uncertainty estimation and adversarial resistance of white matter hyperintensity segmentation

White matter hyperintensities (WMH) are frequently observed on structural neuroimaging of elderly populations and are associated with cognitive decline and increased risk of dementia. Many existing WMH segmentation algorithms produce suboptimal results in populations with vascular lesions or brain atrophy, or require parameter tuning and are computationally expensive. Additionally, most algorithms do not generate a confidence estimate of segmentation quality, limiting their interpretation. MRI-based segmentation methods are often sensitive to acquisition protocols, scanners, noise-level, and image contrast, failing to generalize to other populations and out-of-distribution datasets. Given these concerns, we propose a novel Bayesian 3D Convolutional Neural Network (CNN) with a U-Net architecture that automatically segments WMH, provides uncertainty estimates of the segmentation output for quality control and is robust to changes in acquisition protocols. We also provide a second model to differentiate deep and periventricular WMH. 432 subjects were recruited to train the CNNs from four multi-site imaging studies. A separate test set of 158 subjects was used for evaluation, including an unseen multi-site study. We compared our model to two established state-of-the-art techniques (BIANCA and DeepMedic), highlighting its accuracy and efficiency. Our Bayesian 3D U-Net achieved the highest Dice similarity coefficient of 0.89 {+/-} 0.08 and the lowest modified Hausdorff distance of 2.98 {+/-} 4.40 mm. We further validated our models highlighting their robustness on clinical adversarial cases simulating data with low signal-to-noise ratio, low resolution, and different contrast (stemming from MRI sequences with different parameters). Our pipeline and models are available at: https://hypermapp3r.readthedocs.io

neuroscience↗

bioRxiv2020

A negative feedback loop mediated by the NR4A family of nuclear hormone receptors restrains expansion of B cells that receive signal one in the absence of signal two

Ag stimulation (signal 1) triggers B cell activation and proliferation, and primes B cells to recruit, engage, and respond to T cell help (signal 2). However, failure to receive signal 2 within a defined window of time results in an abortive round of proliferation, followed by anergy or apoptosis. Although the molecular basis of T cell help has been extensively dissected, the mechanisms that restrain Ag-stimulated B cells, and enforce dependence upon co-stimulation, are incompletely understood. Nr4a1-3 encode a small family of orphan nuclear receptors that are rapidly induced by B cell receptor (BCR) stimulation, yet little is known about their function in humoral immune responses. Here we use germline and conditional loss-of-function mouse models to show that Nr4a1 and Nr4a3 play partially redundant roles to restrain both the survival and proliferation of B cells that receive signal 1 in the absence of co-stimulatory signals, and do so in part by repressing expression of BATF and consequently c-MYC. Correspondingly, Ab responses to TI-2 immunogens are enhanced in the absence of Nr4a1, but are unaltered in response to immunogens that incorporate co-stimulatory signals. Unexpectedly, we also identify a role for the NR4A family in restraining B cell access to T cell help by repressing expression of the T cell chemokines CCL3/4, as well as CD86 and ICAM1, and show that this is relevant under conditions of competition for limiting T cell help. Our studies collectively reveal a novel negative feedback loop mediated by the NR4A family that increases B cell dependence upon T cell help and restrains strongly Ag-activated B cell clones from monopolizing limiting amounts of T cell help. We speculate that this imposes B cell tolerance and dampens immunodominance to facilitate preservation of clonal diversity during an immune response.

immunology↗