Intrinsic Adrenal TWIK-Related Acid-Sensitive TASK Channel Dysfunction Produces Spontaneous Calcium Oscillations Sufficient to Drive AngII (Angiotensin II)-Unresponsive Hyperaldosteronism.

BACKGROUND: Ion channel mutations in calcium regulating genes strongly associate with AngII (angiotensin II)-independent aldosterone production. Here, we used an established mouse model of in vivo aldosterone autonomy, Cyp11b2-driven deletion of TWIK-related acid-sensitive potassium channels (TASK-1 and TASK-3, termed zona glomerulosa [zG]-TASK-loss-of-function), and selective pharmacological TASK channel inhibition to determine whether channel dysfunction in native, electrically excitable zG cell rosette-assemblies: (1) produces spontaneous calcium oscillatory activity and (2) is sufficient to drive substantial aldosterone autonomy. METHODS: We imaged calcium activity in adrenal slices expressing a zG-specific calcium reporter (GCaMP3), an in vitro experimental approach that preserves the native rosette assembly and removes potentially confounding extra-adrenal contributions. In parallel experiments, we measured acute aldosterone production from adrenal slice cultures. RESULTS: Absent from untreated WT slices, we find that either adrenal-specific genetic deletion or acute pharmacological TASK channel inhibition produces spontaneous oscillatory bursting behavior and steroidogenic activity (2.4-fold) that are robust, sustained, and equivalent to activities evoked by 3 nM AngII in WT slices. Moreover, spontaneous activity in zG-TASK-loss-of-function slices and inhibitor-evoked activity in WT slices are unresponsive to AngII regulation over a wide range of concentrations (50 pM to 3 µM). CONCLUSIONS: We provide proof of principle that spontaneous activity of zG cells within classic rosette assemblies evoked solely by a change in an intrinsic, dominant resting-state conductance can be a significant source of AngII-independent aldosterone production from native tissue.

PlaqView 2.0: A comprehensive web portal for cardiovascular single-cell genomics.

Single-cell RNA-seq (scRNA-seq) is a powerful genomics technology to interrogate the cellular composition and behaviors of complex systems. While the number of scRNA-seq datasets and available computational analysis tools have grown exponentially, there are limited systematic data sharing strategies to allow rapid exploration and re-analysis of single-cell datasets, particularly in the cardiovascular field. We previously introduced PlaqView, an open-source web portal for the exploration and analysis of published atherosclerosis single-cell datasets. Now, we introduce PlaqView 2.0 (www.plaqview.com), which provides expanded features and functionalities as well as additional cardiovascular single-cell datasets. We showcase improved PlaqView functionality, backend data processing, user-interface, and capacity. PlaqView brings new or improved tools to explore scRNA-seq data, including gene query, metadata browser, cell identity prediction, ad hoc RNA-trajectory analysis, and drug-gene interaction prediction. PlaqView serves as one of the largest central repositories for cardiovascular single-cell datasets, which now includes data from human aortic aneurysm, gene-specific mouse knockouts, and healthy references. PlaqView 2.0 brings advanced tools and high-performance computing directly to users without the need for any programming knowledge. Lastly, we outline steps to generalize and repurpose PlaqView's framework for single-cell datasets from other fields.

Neuroepigenetic impact on mentalizing in childhood.

Mentalizing, or the ability to understand the mental states and intentions of others, is an essential social cognitive function that children learn and continue to cultivate into adolescence. While most typically developing children acquire sufficient mentalizing skills, individual differences in mentalizing persist throughout childhood and are likely influenced by a combination of cognitive functioning, the social environment, and biological factors. DNA methylation of the oxytocin receptor gene (OXTRm) impacts gene expression and is associated with increased brain activity in mentalizing regions during displays of animacy in healthy young adults. The establishment, fine-tuning, and implications of such associations in the context of broader social functioning remain unclear. Using a developmental neuroimaging epigenetic approach, we investigated the contributions of OXTRm to individual variability in brain function during animate motion perception in middle childhood. We find that higher levels of OXTRm are associated with increased neural responses in the left temporo-parietal junction and inferior frontal gyrus. We also find a positive association between neural activity in LTPJ and social skills. These findings provide evidence of epigenetic influence on the developing child brain and demonstrate that variability in neural social perception in childhood is multifaceted with contributions from individual social experience and the endogenous oxytocin system.

Enhanced single-cell RNA-seq workflow reveals coronary artery disease cellular cross-talk and candidate drug targets.

BACKGROUND AND AIMS: The atherosclerotic plaque microenvironment is highly complex, and selective agents that modulate plaque stability are not yet available. We sought to develop a scRNA-seq analysis workflow to investigate this environment and uncover potential therapeutic approaches. We designed a user-friendly, reproducible workflow that will be applicable to other disease-specific scRNA-seq datasets. METHODS: Here we incorporated automated cell labeling, pseudotemporal ordering, ligand-receptor evaluation, and drug-gene interaction analysis into a ready-to-deploy workflow. We applied this pipeline to further investigate a previously published human coronary single-cell dataset by Wirka et al. Notably, we developed an interactive web application to enable further exploration and analysis of this and other cardiovascular single-cell datasets. RESULTS: We revealed distinct derivations of fibroblast-like cells from smooth muscle cells (SMCs), and showed the key changes in gene expression along their de-differentiation path. We highlighted several key ligand-receptor interactions within the atherosclerotic environment through functional expression profiling and revealed several avenues for future pharmacological development for precision medicine. Further, our interactive web application, PlaqView (www.plaqview.com), allows lay scientists to explore this and other datasets and compare scRNA-seq tools without prior coding knowledge. CONCLUSIONS: This publicly available workflow and application will allow for more systematic and user-friendly analysis of scRNA datasets in other disease and developmental systems. Our analysis pipeline provides many hypothesis-generating tools to unravel the etiology of coronary artery disease. We also highlight potential mechanisms for several drugs in the atherosclerotic cellular environment. Future releases of PlaqView will feature more scRNA-seq and scATAC-seq atherosclerosis-related datasets to provide a critical resource for the field, and to promote data harmonization and biological interpretation.

An Image Registration-Based Morphing Technique for Generating Subject-Specific Brain Finite Element Models.

Finite element (FE) models of the brain are crucial for investigating the mechanisms of traumatic brain injury (TBI). However, FE brain models are often limited to a single neuroanatomy because the manual development of subject-specific models is time consuming. The objective of this study was to develop a pipeline to automatically generate subject-specific FE brain models using previously developed nonlinear image registration techniques, preserving both external and internal neuroanatomical characteristics. To verify the morphing-induced mesh distortions did not influence the brain deformation response, strain distributions predicted using the morphed model were compared to those from manually created voxel models of the same subject. Morphed and voxel models were generated for 44 subjects ranging in age, and simulated using head kinematics from a football concussion case. For each subject, brain strain distributions predicted by each model type were consistent, and differences in strain prediction was less than 4% between model type. This automated technique, taking approximately 2 h to generate a subject-specific model, will facilitate interdisciplinary research between the biomechanics and neuroimaging fields and could enable future use of biomechanical models in the clinical setting as a tool for improving diagnosis.

Angiotensin II induces coordinated calcium bursts in aldosterone-producing adrenal rosettes.

Aldosterone-producing zona glomerulosa (zG) cells of the adrenal gland arrange in distinct multi-cellular rosettes that provide a structural framework for adrenal cortex morphogenesis and plasticity. Whether this cyto-architecture also plays functional roles in signaling remains unexplored. To determine if structure informs function, we generated mice with zG-specific expression of GCaMP3 and imaged zG cells within their native rosette structure. Here we demonstrate that within the rosette, angiotensin II evokes periodic Cav3-dependent calcium events that form bursts that are stereotypic in form. Our data reveal a critical role for angiotensin II in regulating burst occurrence, and a multifunctional role for the rosette structure in activity-prolongation and coordination. Combined our data define the calcium burst as the fundamental unit of zG layer activity evoked by angiotensin II and highlight a novel role for the rosette as a facilitator of cell communication.

Accuracy of algorithms to predict injury severity in older adults for trauma triage.

Objective: Older adults make up a rapidly increasing proportion of motor vehicle occupants and previous studies have demonstrated that this population is more susceptible to traumatic injuries. The CDC recommends that patients anticipated to have severe injuries (Injury Severity Score [ISS] ≥ 16) be transported to a trauma center. The recommended target rate for undertriage is ≤ 5% and for overtriage is ≤ 50%. Several regression-based algorithms for injury prediction have been developed in order to predict severe injury in occupants involved in a motor vehicle collision (MVC). The objective of this study to was to determine if the accuracy of regression-based injury severity prediction algorithms decreases for older adults.Methods: Data were obtained from the National Automotive Sampling System - Crashworthiness Data System (NASS-CDS) from the years 2000-2015. Adult occupants involved in non-rollover MVCs were included. Regression-based injury risk models to predict severe injury (ISS ≥ 16) were developed using random split-samples with the following variables: age, delta-V, direction of impact, belt status, and number of impacts. Separate models were trained using data from the following age groups: (1) all adults, (2) 15-54 years, (3) ≥45 years, (4) ≥55 years, and (5) ≥65 years. The models were compared using the mean receiver operating characteristic area under curve (ROC-AUC) after 1,000 iterations of training and testing. The predicted rates of overtriage were then determined for each group in order to achieve an undertriage rate of 5%.Results: There were 24,577 occupants (6,863,306 weighted) included in this analysis. The injury prediction model trained using data from all adults did not perform as well when tested on older adults (ROC-AUC: 15-54 years: 0.874 [95% CI: [0.851-0.895]; 45+ years: 0.837 [95% CI: 0.802-869]; 55+ years: 0.821 [95% CI: 0.775-0.864]; and 65+ years: 0.813 [95% CI: 0.754-0.866]). The accuracy of this model decreased in each decade of life. The performance did not change significantly when age-specific data were used to train the prediction models (ROC-AUC: 18-54 years: 0.874 [95% CI: 0.851-0.896]; 45+ years: 0.836 [95% CI: 0.798-0.871]; 55+ years: 0.822 [95% CI: 0.779-0.864]; and 65+ years: 0.808 [95% CI: 0.748-0.868]). In order to achieve an undertriage rate of 5%, the predicted overtriage rate by these models were 50% for occupants 15-54 years, 61% for occupants ≥ 55 years, 70% for occupants ≥ 55 years, and 71% for occupants ≥ 65 years.Conclusion: The results of this study indicate that it is more difficult to accurately predict severe injury in older adults involved in MVCs, which has the potential to result in significant overtriage. This decreased accuracy is likely due to variations in fragility in older adults. These findings indicate that special care should be taken when using regression-based prediction models to determine the appropriate hospital destination for older occupants.