Loss of cardiomyocyte CYB5R3 impairs redox equilibrium and causes sudden cardiac death

Sudden cardiac death (SCD) in patients with heart failure (HF) is allied with an imbalance in reduction and oxidation (redox) signaling in cardiomyocytes; however, the basic pathways and mechanisms governing redox homeostasis in cardiomyocytes are not fully understood. Here, we show that cytochrome b5 reductase 3 (CYB5R3), an enzyme known to regulate redox signaling in erythrocytes and vascular cells, is essential for cardiomyocyte function. Using a conditional cardiomyocyte-specific CYB5R3-knockout mouse, we discovered that deletion of CYB5R3 in male, but not female, adult cardiomyocytes causes cardiac hypertrophy, bradycardia, and SCD. The increase in SCD in CYB5R3-KO mice is associated with calcium mishandling, ventricular fibrillation, and cardiomyocyte hypertrophy. Molecular studies reveal that CYB5R3-KO hearts display decreased adenosine triphosphate (ATP), increased oxidative stress, suppressed coenzyme Q levels, and hemoprotein dysregulation. Finally, from a translational perspective, we reveal that the high-frequency missense genetic variant rs1800457, which translates into a CYB5R3 T117S partial loss-of-function protein, associates with decreased event-free survival (~20%) in Black persons with HF with reduced ejection fraction (HFrEF). Together, these studies reveal a crucial role for CYB5R3 in cardiomyocyte redox biology and identify a genetic biomarker for persons of African ancestry that may potentially increase the risk of death from HFrEF.These studies were supported by NIH grants R35 HL 161177 (to ACS), R01 HL 133864 (to ACS), R01 HL 128304 (to ACS), R41 HL15098 (to GS), R01 GM 122091 (to PHT), GM125944 (to FJS), R01 DK112854 (to FJS), R21 NS112787 (to MF), NS121706 (to YLW), EB023507 (to YLW), F31 HL149241 (to HMS), and F31 HL151173 (to JCG). Support was also provided by American Heart Association grants 19EIA34770095 (to ACS), AHA 18CDA34140024 (to YLW), and 19PRE34380152 (to NTC); the Spanish Ministry of Health (grant FIS PI17-01286); Junta de Andalucía BIO-177 and the FEDER Funding Program from the European Union and CIBERER (U729)-ISCIII (to PN); Department of Defense W81XWH1810070 (to YLW); and Vitalant. This research was supported in part by the University of Pittsburgh Center for Research Computing through the resources provided. Specifically, this work used the HTC cluster, which is supported by NIH award number S10OD028483.Peer reviewe

Physics‐informed deep learning for T2‐deblurred superresolution turbo spin echo MRI

Abstract: Purpose: Deep learning superresolution (SR) is a promising approach to reduce MRI scan time without requiring custom sequences or iterative reconstruction. Previous deep learning SR approaches have generated low‐resolution training images by simple k‐space truncation, but this does not properly model in‐plane turbo spin echo (TSE) MRI resolution degradation, which has variable T2 relaxation effects in different k‐space regions. To fill this gap, we developed a T2‐deblurred deep learning SR method for the SR of 3D‐TSE images. Methods: A SR generative adversarial network was trained using physically realistic resolution degradation (asymmetric T2 weighting of raw high‐resolution k‐space data). For comparison, we trained the same network structure on previous degradation models without TSE physics modeling. We tested all models for both retrospective and prospective SR with 3 × 3 acceleration factor (in the two phase‐encoding directions) of genetically engineered mouse embryo model TSE‐MR images. Results: The proposed method can produce high‐quality 3 × 3 SR images for a typical 500‐slice volume with 6–7 mouse embryos. Because 3 × 3 SR was performed, the image acquisition time can be reduced from 15 h to 1.7 h. Compared to previous SR methods without TSE modeling, the proposed method achieved the best quantitative imaging metrics for both retrospective and prospective evaluations and achieved the best imaging‐quality expert scores for prospective evaluation. Conclusion: The proposed T2‐deblurring method improved accuracy and image quality of deep learning–based SR of TSE MRI. This method has the potential to accelerate TSE image acquisition by a factor of up to 9

Improved Subspace Estimation for Low-Rank Model-Based Accelerated Cardiac Imaging

Sparse sampling methods have emerged as effective tools to accelerate cardiac magnetic resonance imaging (MRI).Low-rank model-based cardiac imaging uses a predetermined temporal subspace for image reconstruction from highly undersampled (k, t)-space data and has been demonstrated effective for high-speed cardiac MRI. The accuracy of the temporal subspace isa key factor in these methods, yet little work has been published on data acquisition strategies to improve subspace estimation. This paper investigates the use of non-Cartesian k-space trajectories to replace the Cartesian trajectories that are omnipresent but are highly sensitive to readout direction. We also propose "self-navigated" pulse sequences that collect both navigator data (for determining the temporal subspace) and imaging data after every RF pulse, allowing for even greater acceleration. We investigate subspace estimation strategies through analysis of phantom images and demonstrate in vivo cardiac imaging in rats and mice without the use of ECG or respiratory gating. The proposed methods achieved 3-D imaging of wall motion, first-pass myocardial perfusion, and late gadolinium enhancement in rats at 74 frames/s,as well as 2-D imaging of wall motion in mice at 97 frames/s

Abcc8 (sulfonylurea receptor-1) knockout mice exhibit reduced axonal injury, cytotoxic edema and cognitive dysfunction vs. wild-type in a cecal ligation and puncture model of sepsis

Abstract Sepsis-associated brain injury (SABI) is characterized by an acute deterioration of mental status resulting in cognitive impairment and acquisition of new and persistent functional limitations in sepsis survivors. Previously, we reported that septic mice had evidence of axonal injury, robust microglial activation, and cytotoxic edema in the cerebral cortex, thalamus, and hippocampus in the absence of blood–brain barrier disruption. A key conceptual advance in the field was identification of sulfonylurea receptor 1 (SUR1), a member of the adenosine triphosphate (ATP)-binding cassette protein superfamily, that associates with the transient receptor potential melastatin 4 (TRPM4) cation channel to play a crucial role in cerebral edema development. Therefore, we hypothesized that knockout (KO) of Abcc8 (Sur1 gene) is associated with a decrease in microglial activation, cerebral edema, and improved neurobehavioral outcomes in a murine cecal ligation and puncture (CLP) model of sepsis. Sepsis was induced in 4–6-week-old Abcc8 KO and wild-type (WT) littermate control male mice by CLP. We used immunohistochemistry to define neuropathology and microglial activation along with parallel studies using magnetic resonance imaging, focusing on cerebral edema on days 1 and 4 after CLP. Abcc8 KO mice exhibited a decrease in axonal injury and cytotoxic edema vs. WT on day 1. Abcc8 KO mice also had decreased microglial activation in the cerebral cortex vs. WT. These findings were associated with improved spatial memory on days 7–8 after CLP. Our study challenges a key concept in sepsis and suggests that brain injury may not occur merely as an extension of systemic inflammation. We advance the field further and demonstrate that deletion of the SUR1 gene ameliorates CNS pathobiology in sepsis including edema, axonal injury, neuroinflammation, and behavioral deficits. Benefits conferred by Abcc8 KO in the murine CLP model warrant studies of pharmacological Abcc8 inhibition as a new potential therapeutic strategy for SABI

Modeling normal mouse uterine contraction and placental perfusion with non-invasive longitudinal dynamic contrast enhancement MRI

Background: The placenta is a transient organ critical for fetal development. Disruptions of normal placental functions can impact health throughout an individual’s entire life. Although being recognized by the NIH Human Placenta Project as an important organ, the placenta remains understudied, partly because of a lack of non-invasive tools for longitudinally evaluation for key aspects of placental functionalities. Objective: Our goal is to create a non-invasive preclinical imaging pipeline that can longitudinally probe murine placental health in vivo. We use advanced imaging processing schemes to establish functional biomarkers for non-invasive longitudinal evaluation of placental development. Methodology: We implement dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) and analysis pipeline to quantify uterine contraction and placental perfusion dynamics. We use optic flow and time-frequency analysis to quantify and characterize contraction-related placental motion. Our novel imaging and analysis pipeline uses subcutaneous administration of gadolinium for steepest slope-based perfusion evaluation, enabling non-invasive longitudinal monitoring. Results: We demonstrate that the placenta exhibits spatially asymmetric contractile motion that develops from E14.5 to E17.5. Additionally, we see that placental perfusion, perfusion delivery rate, and substrate delivery all increase from E14.5 to E17.5, with the High Perfusion Chamber (HPC) leading the placental changes that occur from E14.5 to E17.5 Discussion: We advance the placental perfusion chamber paradigm with a novel, physiologically based threshold model for chamber localization and demonstrate spatially varying placental chambers using multiple functional metrics that assess mouse placental development and remodeling throughout gestation. Conclusion: Our pipeline enables the non-invasive, longitudinal assessment of multiple placenta functions from a single imaging session. Our pipeline serves as a key toolbox for advancing research in mouse models of placental disease and disorder