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Competing Interests: Declaration of competing interest DL, AF – Supported by institutional grants from Amgen and Philips. DD, DSB, PJS – Software royalties from Cedars-Sinai Medical Center. LS – Institutional grants from Amgen and Philips. Site PI for Ocean(a) trial.

A variety of classic psychedelics and MDMA have been shown to enhance fear extinction in rodent models. This has translational significance because a standard treatment for post-traumatic stress disorder (PTSD) is prolonged exposure therapy. However, few studies have investigated psilocybin's potential effect on fear learning paradigms. More specifically, the extents to which dose, timing of administration, and serotonin receptors may influence psilocybin's effect on fear extinction are not understood. In this study, we used a delay fear conditioning paradigm to determine the effects of psilocybin on fear extinction, extinction retention, and fear renewal in male and female mice. Psilocybin robustly enhances fear extinction when given acutely prior to testing for all doses tested. Psilocybin also exerts long-term effects to elevate extinction retention and suppress fear renewal in a novel context, although these changes were sensitive to dose. Analysis of sex differences showed that females may respond to a narrower range of doses than males. Administration of psilocybin prior to fear learning or immediately after extinction yielded no change in behavior, indicating that concurrent extinction experience is necessary for the drug's effects. Cotreatment with a 5-HT 2A receptor antagonist blocked psilocybin's effects for extinction, extinction retention, and fear renewal, whereas 5-HT 1A receptor antagonism attenuated only the effect on fear renewal. Collectively, these results highlight dose, context, and serotonin receptors as crucial factors in psilocybin's ability to facilitate fear extinction. The study provides preclinical evidence to support investigating psilocybin as a pharmacological adjunct for extinction-based therapy for PTSD.

Introduction: Epicardial fat is a metabolically active adipose tissue depot situated between the myocardium and visceral pericardium that covers ∼80% of the heart surface. While epicardial fat has been associated with the development of atherosclerotic coronary artery disease (CAD), less is known about the relationship between epicardial fat and coronary vascular function. Moreover, the relations between excess epicardial fat and cardiac morphology and function remains incompletely understood., Methods and Results: To address these knowledge gaps, we retrospectively analyzed data from 294 individuals from our database of women with suspected ischemia with no obstructive coronary disease (INOCA) who underwent both invasive coronary function testing and cardiac magnetic resonance imaging (cMRI). Epicardial fat area, biventricular morphology, and function, as well as left atrial function, were assessed from cine images, per established protocols. The major novel findings were twofold: First, epicardial fat area was not associated with coronary vascular dysfunction. Second, epicardial fat was associated with increased left ventricular concentricity (β= 0.15, p= 0.01), increased septal thickness (β= 0.17, p= 0.002), and reduced left atrial conduit fraction (β= -0.15, p= 0.02), even after accounting for age, BMI, and history of hypertension., Conclusions: Taken together, these data do not support a measurable relationship between epicardial fat and coronary vascular dysfunction but does suggest that epicardial fat may be related to concentric remodeling and diastolic dysfunction in women with suspected INOCA. Prospective studies are needed to elucidate the long-term impact of epicardial fat in this patient population., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Management and prevention of acute decompensated heart failure remain highly prevalent and challenging medical conditions. Incorporation of Point-of-Care Ultrasound (POCUS) as an adjunctive tool for assessing volume status and treatment response has shown significant promise. POCUS can be used for imaging internal anatomic structures serially and capturing these images for comparison and measurement over time. This protocol describes a scalable and standardized methodology for the serial assessment of the inferior vena cava (IVC). The methodology includes serial image collection, measurement, and presentation in the electronic medical record. A workflow for POCUS-acquired images of the IVC was created to capture the images and measure the diameter in a discrete data field for direct comparison over time and in response to clinical management. The protocol also includes the assessment of the presence or absence of pleural effusion as discrete data in the standardized workflow. By integrating POCUS into heart failure management, clinicians can improve patient outcomes through more precise and timely adjustments in treatment.

Background: Echocardiographic strain measurements require extensive operator experience and have significant intervendor variability. Creating an automated, open-source, vendor-agnostic method to retrospectively measure global longitudinal strain (GLS) from standard echocardiography B-mode images would greatly improve post hoc research applications and may streamline patient analyses., Objectives: This study was seeking to develop an automated deep learning strain (DLS) analysis pipeline and validate its performance across multiple applications and populations., Methods: Interobserver/-vendor variation of traditional GLS, and simulated effects of variation in contour on speckle-tracking measurements were assessed. The DLS pipeline was designed to take semantic segmentation results from EchoNet-Dynamic and derive longitudinal strain by calculating change in the length of the left ventricular endocardial contour. DLS was evaluated for agreement with GLS on a large external dataset and applied across a range of conditions that result in cardiac hypertrophy., Results: In patients scanned by 2 sonographers using 2 vendors, GLS had an intraclass correlation of 0.29 (95% CI: -0.01 to 0.53, P = 0.03) between vendor measurements and 0.63 (95% CI: 0.48-0.74, P < 0.001) between sonographers. With minor changes in initial input contour, step-wise pixel shifts resulted in a mean absolute error of 3.48% and proportional strain difference of 13.52% by a 6-pixel shift. In external validation, DLS maintained moderate agreement with 2-dimensional GLS (intraclass correlation coefficient [ICC]: 0.56, P = 0.002) with a bias of -3.31% (limits of agreement: -11.65% to 5.02%). The DLS method showed differences (P < 0.0001) between populations with cardiac hypertrophy and had moderate agreement in a patient population of advanced cardiac amyloidosis: ICC was 0.64 (95% CI: 0.53-0.72), P < 0.001, with a bias of 0.57%, limits of agreement of -4.87% to 6.01% vs 2-dimensional GLS., Conclusions: The open-source DLS provides lower variation than human measurements and similar quantitative results. The method is rapid, consistent, vendor-agnostic, publicly released, and applicable across a wide range of imaging qualities., Competing Interests: Funding Support and Author Disclosures Dr Kwan has received funding support from the Doris Duke Charitable Foundation Grant 2020059, American Heart Association Career Development Award 23CDA1053659 and National Institutes of Health (NIH) R01HL131532-06 and UL1TR001881. Dr Chang has received funding from National Institutional Health T32HL097129-13. Project no. RRF-2.3.1-21-2022-00004 (MILAB) has been implemented with the support provided by the European Union. This project was also supported by a grant from the National Research, Development, and Innovation Office (NKFIH) of Hungary (FK 142573 to Dr Kovács). Dr Kovács was supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences. Dr. Tokodi was supported by the New National Excellence Program (ÚNKP-23-4-II-SE-39) of the Ministry of Culture and Innovation in Hungary from the National Research, Development, and Innovation Fund. This work was supported in part by NIH K99 HL157421-01 and R00HL157421-04. All other authors have reported that they have no relationships relevant to the contents of this paper to report., (Copyright © 2024 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Purpose: To develop a novel low-rank tensor reconstruction approach leveraging the complete acquired data set to improve precision and repeatability of multiparametric mapping within the cardiovascular MR Multitasking framework., Methods: A novel approach that alternated between estimation of temporal components and spatial components using the entire data set acquired (i.e., including navigator data and imaging data) was developed to improve reconstruction. The precision and repeatability of the proposed approach were evaluated on numerical simulations, 10 healthy subjects, and 10 cardiomyopathy patients at multiple scan times for 2D myocardial T 1 /T 2 mapping with MR Multitasking and were compared with those of the previous navigator-derived fixed-basis approach., Results: In numerical simulations, the proposed approach outperformed the previous fixed-basis approach with lower T 1 and T 2 error against the ground truth at all scan times studied and showed better motion fidelity. In human subjects, the proposed approach showed no significantly different sharpness or T 1 /T 2 measurement and significantly improved T 1 precision by 20%-25%, T 2 precision by 10%-15%, T 1 repeatability by about 30%, and T 2 repeatability by 25%-35% at 90-s and 50-s scan times The proposed approach at the 50-s scan time also showed comparable results with that of the previous fixed-basis approach at the 90-s scan time., Conclusion: The proposed approach improved precision and repeatability for quantitative imaging with MR Multitasking while maintaining comparable motion fidelity, T 1 /T 2 measurement, and septum sharpness and had the potential for further reducing scan time from 90 s to 50 s., (© 2024 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Background and Aims: Diagnosis of tricuspid regurgitation (TR) requires careful expert evaluation. This study developed an automated deep learning pipeline for assessing TR from transthoracic echocardiography., Methods: An automated deep learning workflow was developed using 47,312 studies (2,079,898 videos) from Cedars-Sinai Medical Center (CSMC) between 2011 and 2021. The pipeline was tested on a temporally distinct test set of 2,462 studies (108,138 videos) obtained in 2022 at CSMC and a geographically distinct cohort of 5,549 studies (278,377 videos) from Stanford Healthcare (SHC)., Results: In the CSMC test dataset, the view classifier demonstrated an AUC of 1.000 (0.999 - 1.000) and identified at least one A4C video with colour Doppler across the tricuspid valve in 2,410 of 2,462 studies with a sensitivity of 0.975 (0.968-0.982) and a specificity of 1.000 (1.00-1.000). In the CSMC test cohort, moderate-or-severe TR was detected with an AUC of 0.928 (0.913 - 0.943) and severe TR was detected with an AUC of 0.956 (0.940 - 0.969). In the SHC cohort, the view classifier correctly identified at least one TR colour Doppler video in 5,268 of the 5,549 studies, resulting in an AUC of 0.999 (0.998 - 0.999), a sensitivity of 0.949 (0.944 - 0.955) and specificity of 0.999 (0.999 - 0.999). The AI model detected moderate-or-severe TR with an AUC of 0.951 (0.938 - 0.962) and severe TR with an AUC of 0.980 (0.966 - 0.988)., Conclusions: We developed an automated pipeline to identify clinically significant TR with excellent performance. This approach carries potential for automated TR detection and stratification for surveillance and screening., Key Question: Can an automated deep learning model assess tricuspid regurgitation severity from echocardiography?, Key Finding: We developed and validated an automated tricuspid regurgitation detection algorithm pipeline across two healthcare systems with high volume echocardiography labs. The algorithm correctly identifies apical-4-chamber view videos with colour Doppler across the tricuspid valve and grades clinically significant TR with strong agreement to expert clinical readers., Take Home Message: A deep learning pipeline could automate TR screening, facilitating reproducible accurate assessment of TR severity, allowing rapid triage or re-review and expand access in low-resource or primary care settings.

Importance: Chronic liver disease affects more than 1.5 billion adults worldwide, however the majority of cases are asymptomatic and undiagnosed. Echocardiography is broadly performed and visualizes the liver; but this information is not leveraged., Objective: To develop and evaluate a deep learning algorithm on echocardiography videos to enable opportunistic screening for chronic liver disease., Design: Retrospective observational cohorts., Setting: Two large urban academic medical centers., Participants: Adult patients who received echocardiography and abdominal imaging (either abdominal ultrasound or abdominal magnetic resonance imaging) with ≤30 days between tests, between July 4, 2012, to June 4, 2022., Exposure: Deep learning model predictions from a deep-learning computer vision pipeline that identifies subcostal view echocardiogram videos and detects the presence of cirrhosis or steatotic liver disease (SLD)., Main Outcome and Measures: Clinical diagnosis by paired abdominal ultrasound or magnetic resonance imaging (MRI)., Results: A total of 1,596,640 echocardiogram videos (66,922 studies from 24,276 patients) from Cedars-Sinai Medical Center (CSMC) were used to develop EchoNet-Liver, an automated pipeline that identifies high quality subcostal images from echocardiogram studies and detects the presence of cirrhosis or SLD. In the held-out CSMC test cohort, EchoNet-Liver was able to detect the presence of cirrhosis with an AUC of 0.837 (0.789 - 0.880) and SLD with an AUC of 0.799 (0.758 - 0.837). In a separate test cohort with paired abdominal MRIs, cirrhosis was detected with an AUC of 0.704 (0.689-0.718) and SLD was detected with an AUC of 0.726 (0.659-0.790). In an external test cohort of 106 patients (n = 5,280 videos), the model detected cirrhosis with an AUC of 0.830 (0.738 - 0.909) and SLD with an AUC of 0.768 (0.652 - 0.875)., Conclusions and Relevance: Deep learning assessment of clinical echocardiography enables opportunistic screening of SLD and cirrhosis. Application of this algorithm may identify patients who may benefit from further diagnostic testing and treatment for chronic liver disease.

Objective: To investigate whether the sex disparities in type 2 diabetes-associated cardiovascular disease (CVD) risks may be related to early-onset hypertension that could benefit from intensive blood pressure (BP) control., Research Design and Methods: We analyzed intensive versus standard BP control in relation to incident CVD events in women and men with type 2 diabetes, based on their age of hypertension diagnosis., Results: Among 3,792 adults with type 2 diabetes (49% women), multivariable-adjusted CVD risk was increased per decade earlier age at hypertension diagnosis (hazard ratio 1.11 [1.03-1.21], P = 0.006). Excess risk associated with early-diagnosed hypertension was attenuated in the presence of intensive versus standard antihypertensive therapy in women (P = 0.036) but not men (P = 0.76)., Conclusions: Women with type 2 diabetes and early-onset hypertension may represent a higher-risk subpopulation that not only contributes to the excess in diabetes-related CVD risk for women but may benefit from intensive BP control., (© 2024 by the American Diabetes Association.)

Norepinephrine (NE), a neuromodulator released by locus ceruleus (LC) neurons throughout the cortex, influences arousal and learning through extrasynaptic vesicle exocytosis. While NE within cortical regions has been viewed as a homogenous field, recent studies have demonstrated heterogeneous axonal dynamics and advances in GPCR-based fluorescent sensors permit direct observation of the local dynamics of NE at cellular scale. To investigate how the spatiotemporal dynamics of NE release in the prefrontal cortex (PFC) affect neuronal firing, we employed in vivo two-photon imaging of layer 2/3 of the PFC in order to observe fine-scale neuronal calcium and NE dynamics concurrently. In this proof of principle study, we found that local and global NE fields can decouple from one another, providing a substrate for local NE spatiotemporal activity patterns. Optic flow analysis revealed putative release and reuptake events which can occur at the same location, albeit at different times, indicating the potential to create a heterogeneous NE field. Utilizing generalized linear models, we demonstrated that cellular Ca 2+ fluctuations are influenced by both the local and global NE field. However, during periods of local/global NE field decoupling, the local field drives cell firing dynamics rather than the global field. These findings underscore the significance of localized, phasic NE fluctuations for structuring cell firing, which may provide local neuromodulatory control of cortical activity., (Copyright © 2024 Glaeser-Khan et al.)

Psilocybin, ketamine, and MDMA are psychoactive compounds that exert behavioral effects with distinguishable but also overlapping features. The growing interest in using these compounds as therapeutics necessitates preclinical assays that can accurately screen psychedelics and related analogs. We posit that a promising approach may be to measure drug action on markers of neural plasticity in native brain tissues. We therefore developed a pipeline for drug classification using light sheet fluorescence microscopy of immediate early gene expression at cellular resolution followed by machine learning. We tested male and female mice with a panel of drugs, including psilocybin, ketamine, 5-MeO-DMT, 6-fluoro-DET, MDMA, acute fluoxetine, chronic fluoxetine, and vehicle. In one-versus-rest classification, the exact drug was identified with 67% accuracy, significantly above the chance level of 12.5%. In one-versus-one classifications, psilocybin was discriminated from 5-MeO-DMT, ketamine, MDMA, or acute fluoxetine with >95% accuracy. We used Shapley additive explanation to pinpoint the brain regions driving the machine learning predictions. Our results support a novel approach for screening psychoactive drugs with psychedelic properties., Competing Interests: Competing interests A.C.K. has served as a scientific advisor for Empyrean Neuroscience, Freedom Biosciences, and Psylo. A.C.K. has received research support from Intra-Cellular Therapies. A.P.K has received research support from Transcend Therapeutics and Freedom Biosciences. A.P.K. has a provisional patent application related to psychedelics. The other authors report no financial relationships with commercial interests.

Competing Interests: Funding Support and Author Disclosures Shreel Joshi is an employee of Abbott Laboratories, manufacturer of the mapping tool and system used in this case. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Background: Although physical activity is widely recommended for reducing cardiovascular and all-cause mortality risks, female individuals consistently lag behind male individuals in exercise engagement., Objectives: The goal of this study was to evaluate whether physical activity derived health benefits may differ by sex., Methods: In a prospective study of 412,413 U.S. adults (55% female, age 44 ± 17 years) who provided survey data on leisure-time physical activity, we examined sex-specific multivariable-adjusted associations of physical activity measures (frequency, duration, intensity, type) with all-cause and cardiovascular mortality from 1997 through 2019., Results: During 4,911,178 person-years of follow-up, there were 39,935 all-cause deaths including 11,670 cardiovascular deaths. Regular leisure-time physical activity compared with inactivity was associated with 24% (HR: 0.76; 95% CI: 0.73-0.80) and 15% (HR: 0.85; 95% CI: 0.82-0.89) lower risk of all-cause mortality in women and men, respectively (Wald F = 12.0, sex interaction P < 0.001). Men reached their maximal survival benefit of HR 0.81 from 300 min/wk of moderate-to-vigorous physical activity, whereas women achieved similar benefit at 140 min/wk and then continued to reach a maximum survival benefit of HR 0.76 also at ∼300 min/wk. Sex-specific findings were similar for cardiovascular death (Wald F = 20.1, sex interaction P < 0.001) and consistent across all measures of aerobic activity as well as muscle strengthening activity (Wald F = 6.7, sex interaction P = 0.009)., Conclusions: Women compared with men derived greater gains in all-cause and cardiovascular mortality risk reduction from equivalent doses of leisure-time physical activity. These findings could enhance efforts to close the "gender gap" by motivating especially women to engage in any regular leisure-time physical activity., Competing Interests: Funding Support and Author Disclosures This work was supported in part by National Institutes of Health grants K23HL153888, K23AG058752, R21HL156132, R01HL142983, R01HL151828, R01HL131532, R01HL143227, R01AG072475, U54AG062319, and U54AG065141, and the Erika J. Glazer Family Foundation, National Key R&D Program of China (2022YFC2502800), National Natural Science Foundation of China (82103908), Shandong Provincial Natural Science Foundation (ZR2021QH014), Shuimu Scholar Program of Tsinghua University, and National Postdoctoral Innovative Talent Support Program (BX20230189). The funding sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. The National Center for Health Statistics Disclosure Review Board approves the NHIS. Data analyses for this study were additionally approved by the Cedars-Sinai Medical Center Institutional Review Board. The authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Bias in health care has been well documented and results in disparate and worsened outcomes for at-risk groups. Medical imaging plays a critical role in facilitating patient diagnoses but involves multiple sources of bias including factors related to access to imaging modalities, acquisition of images, and assessment (ie, interpretation) of imaging data. Machine learning (ML) applied to diagnostic imaging has demonstrated the potential to improve the quality of imaging-based diagnosis and the precision of measuring imaging-based traits. Algorithms can leverage subtle information not visible to the human eye to detect underdiagnosed conditions or derive new disease phenotypes by linking imaging features with clinical outcomes, all while mitigating cognitive bias in interpretation. Importantly, however, the application of ML to diagnostic imaging has the potential to either reduce or propagate bias. Understanding the potential gain as well as the potential risks requires an understanding of how and what ML models learn. Common risks of propagating bias can arise from unbalanced training, suboptimal architecture design or selection, and uneven application of models. Notwithstanding these risks, ML may yet be applied to improve gain from imaging across all 3A's (access, acquisition, and assessment) for all patients. In this review, we present a framework for understanding the balance of opportunities and challenges for minimizing bias in medical imaging, how ML may improve current approaches to imaging, and what specific design considerations should be made as part of efforts to maximize the quality of health care for all., Competing Interests: Disclosures Dr Kwan reports consulting fees from InVision and grant support from American Heart Association 23CDA1053659 and the KL2 sub-award from National Institutes of Health (NIH) UL1TR001881. Dr Ouyang reports consulting fees from AstraZeneca, Ultromics, EchoIQ, InVision, and research grants from NIH R00-HL157421 and Alexion Pharmaceuticals. Dr Cheng reports consulting fees from Union Chimique Belge and Viz.ai and research grants from NIH R01-HL131532 and NIH R01-HL142983.

Background: There is an association between coronavirus disease 2019 (COVID-19) mRNA vaccination and the incidence or exacerbation of postural orthostatic tachycardia syndrome (POTS)., Objective: The purpose of this study was to characterize patients reporting new or exacerbated POTS after receiving the mRNA COVID-19 vaccine., Methods: We prospectively collected data from sequential patients in a POTS clinic between July 2021 and June 2022 reporting new or exacerbated POTS symptoms after COVID-19 vaccination. Heart rate variability (HRV) and skin sympathetic nerve activity (SKNA) were compared against those of 24 healthy controls., Results: Ten patients (6 women and 4 men; age 41.5 ± 7.9 years) met inclusion criteria. Four patients had standing norepinephrine levels > 600 pg/mL. All patients had conditions that could raise POTS risk, including previous COVID-19 infection (N = 4), hypermobile Ehlers-Danlos syndrome (N = 6), mast cell activation syndrome (N = 6), and autoimmune (N = 7), cardiac (N = 7), neurological (N = 6), or gastrointestinal conditions (N = 4). HRV analysis indicated a lower ambulatory root mean square of successive differences (46.19 ±24 ms; P = .042) vs control (72.49 ± 40.8 ms). SKNA showed a reduced mean amplitude (0.97 ± 0.052 μV; P = .011) vs control (1.2 ± 0.31 μV) and burst amplitude (1.67 ± 0.16 μV; P = .018) vs control (4. 3 ± 4.3 μV). After 417.2 ± 131.4 days of follow-up, all patients reported improvement with the usual POTS care, although 2 with COVID-19 reinfection and 1 with small fiber neuropathy did have relapses of POTS symptoms., Conclusion: All patients with postvaccination POTS had pre-existing conditions. There was no evidence of myocardial injuries or echocardiographic abnormalities. The decreased HRV suggests a sympathetic dominant state. Although all patients improved with guideline-directed care, there is a risk of relapse., Competing Interests: Disclosures Dr Peng-Sheng Chen is a co-inventor of U.S. Patent No. 10,448,852 awarded to Indiana University. All other authors have no conflicts to disclose., (Copyright © 2023 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

Dysfunction in the gene SCN2A , which encodes the voltage-gated sodium channel Na v 1.2, is strongly associated with neurodevelopmental disorders including autism spectrum disorder and intellectual disability (ASD/ID). This dysfunction typically manifests in these disorders as a haploinsufficiency, where loss of one copy of a gene cannot be compensated for by the other allele. Scn2a haploinsufficiency affects a range of cells and circuits across the brain, including associative neocortical circuits that are important for cognitive flexibility and decision-making behaviors. Here, we tested whether Scn2a haploinsufficiency has any effect on a dynamic foraging task that engages such circuits. Scn2a +/- mice and wild-type (WT) littermates were trained on a choice behavior where the probability of reward between two options varied dynamically across trials and where the location of the high reward underwent uncued reversals. Despite impairments in Scn2a -related neuronal excitability, we found that both male and female Scn2a +/- mice performed these tasks as well as wild-type littermates, with no behavioral difference across genotypes in learning or performance parameters. Varying the number of trials between reversals or probabilities of receiving reward did not result in an observable behavioral difference, either. These data suggest that, despite heterozygous loss of Scn2a , mice can perform relatively complex foraging tasks that make use of higher-order neuronal circuits., Competing Interests: K.J.B. is on the scientific advisory board of Regel Tx and receives funding from BioMarin Pharmaceutical Incorporated. A.C.K. has served as a scientific advisor or consultant for Biohaven Pharmaceuticals, Empyrean Neuroscience, Freedom Biosciences, and Psylo. A.C.K. has also received research support from Intra-Cellular Therapies. These duties had no influence on the content of this article. All other authors declare no competing financial interests., (Copyright © 2023 Schamiloglu et al.)

Generative artificial intelligence can be applied to medical imaging on tasks such as privacy-preserving image generation and superresolution and denoising of existing images. Few prior approaches have used cardiac magnetic resonance imaging (cMRI) as a modality given the complexity of videos (the addition of the temporal dimension) as well as the limited scale of publicly available datasets. We introduce GANcMRI, a generative adversarial network that can synthesize cMRI videos with physiological guidance based on latent space prompting. GANcMRI uses a StyleGAN framework to learn the latent space from individual video frames and leverages the timedependent trajectory between end-systolic and end-diastolic frames in the latent space to predict progression and generate motion over time. We proposed various methods for modeling latent time-dependent trajectories and found that our Frame-to-frame approach generates the best motion and video quality. GANcMRI generated high-quality cMRI image frames that are indistinguishable by cardiologists, however, artifacts in video generation allow cardiologists to still recognize the difference between real and generated videos. The generated cMRI videos can be prompted to apply physiologybased adjustments which produces clinically relevant phenotypes recognizable by cardiologists. GANcMRI has many potential applications such as data augmentation, education, anomaly detection, and preoperative planning.

Serotonergic psychedelics are gaining increasing interest as potential therapeutics for a range of mental illnesses. Compounds with short-lived subjective effects may be clinically useful because dosing time would be reduced, which may improve patient access. One short-acting psychedelic is 5-MeO-DMT, which has been associated with improvement in depression and anxiety symptoms in early phase clinical studies. However, relatively little is known about the behavioral and neural mechanisms of 5-MeO-DMT, particularly the durability of its long-term effects. Here we characterized the effects of 5-MeO-DMT on innate behaviors and dendritic architecture in mice. We showed that 5-MeO-DMT induces a dose-dependent increase in head-twitch response that is shorter in duration than that induced by psilocybin at all doses tested. 5-MeO-DMT also substantially suppresses social ultrasonic vocalizations produced during mating behavior. 5-MeO-DMT produces long-lasting increases in dendritic spine density in the mouse medial frontal cortex that are driven by an elevated rate of spine formation. However, unlike psilocybin, 5-MeO-DMT did not affect the size of dendritic spines. These data provide insights into the behavioral and neural consequences underlying the action of 5-MeO-DMT and highlight similarities and differences with those of psilocybin., (© 2023. The Author(s), under exclusive licence to American College of Neuropsychopharmacology.)

High-dimensional metabolomics analyses may identify convergent and divergent markers, potentially representing aligned or orthogonal disease pathways that underly conditions such as pulmonary arterial hypertension (PAH). Using a comprehensive PAH metabolomics dataset, we applied six different conventional and statistical learning techniques to identify analytes associated with key outcomes and compared the results. We found that certain conventional techniques, such as Bonferroni/FDR correction, prioritized metabolites that tended to be highly intercorrelated. Statistical learning techniques generally agreed with conventional techniques on the top-ranked metabolites, but were also more inclusive of different metabolite groups. In particular, conventional methods prioritized sterol and oxylipin metabolites in relation to idiopathic versus non-idiopathic PAH, whereas statistical learning methods tended to prioritize eicosanoid, bile acid, fatty acid, and fatty acyl ester metabolites. Our findings demonstrate how conventional and statistical learning techniques can offer both concordant or discordant results. In the case of a rare yet morbid condition, such as PAH, convergent metabolites may reflect common pathways to shared disease outcomes whereas divergent metabolites could signal either distinct etiologic mechanisms, different sub-phenotypes, or varying stages of disease progression. Notwithstanding the need to investigate the mechanisms underlying the observed results, our main findings suggest that a multi-method approach to statistical analyses of high-dimensional human metabolomics datasets could effectively broaden the scientific yield from a given study design.

Chronic nicotine results in dependence with withdrawal symptoms on discontinuation of use, through desensitization of nicotinic acetylcholine receptors and altered cholinergic neurotransmission. Nicotine withdrawal is associated with increased whole-brain functional connectivity and decreased network modularity; however, the role of cholinergic neurons in those changes is unknown. To identify the contribution of nicotinic receptors and cholinergic regions to changes in the functional network, we analyzed the contribution of the main cholinergic regions to brain-wide activation of the immediate early-gene Fos during withdrawal in male mice and correlated these changes with the expression of nicotinic receptor mRNA throughout the brain. We show that the main functional connectivity modules included the main long-range cholinergic regions, which were highly synchronized with the rest of the brain. However, despite this hyperconnectivity, they were organized into two anticorrelated networks that were separated into basal forebrain-projecting and brainstem-thalamic-projecting cholinergic regions, validating a long-standing hypothesis of the organization of the brain cholinergic systems. Moreover, baseline (without nicotine) expression of Chrna2 , Chrna3 , Chrna10 , and Chrnd mRNA of each brain region correlated with withdrawal-induced changes in Fos expression. Finally, by mining the Allen Brain mRNA expression database, we were able to identify 1755 gene candidates and three pathways (Sox2-Oct4-Nanog, JAK-STAT, and MeCP2-GABA) that may contribute to nicotine withdrawal-induced Fos expression. These results identify the dual contribution of the basal forebrain and brainstem-thalamic cholinergic systems to whole-brain functional connectivity during withdrawal; and identify nicotinic receptors and novel cellular pathways that may be critical for the transition to nicotine dependence., Competing Interests: The authors declare no competing financial interests., (Copyright © 2023 Carrette et al.)

Traumatic events can lead to lifelong, inflexible adaptations in threat perception and behavior, which characterize posttraumatic stress disorder (PTSD). This process involves associations between sensory cues and internal states of threat and then generalization of the threat responses to previously neutral cues. However, most formulations neglect adaptations to threat that are not specific to those associations. To incorporate nonassociative responses to threat, we propose a computational theory of PTSD based on adaptation to the frequency of traumatic events by using a reinforcement learning momentum model. Recent threat prediction errors generate momentum that influences subsequent threat perception in novel contexts. This model fits primary data acquired from a mouse model of PTSD, in which unpredictable footshocks in one context accelerate threat learning in a novel context. The theory is consistent with epidemiological data that show that PTSD incidence increases with the number of traumatic events, as well as the disproportionate impact of early life trauma. Because the theory proposes that PTSD relates to the average of recent threat prediction errors rather than the strength of a specific association, it makes novel predictions for the treatment of PTSD., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

In a social environment, it is essential for animals to consider the behavior of others when making decisions. To quantitatively assess such social decisions, games offer unique advantages. Games may have competitive and cooperative components, modeling situations with antagonistic and shared objectives between players. Games can be analyzed by mathematical frameworks, including game theory and reinforcement learning, such that an animal's choice behavior can be compared against the optimal strategy. However, so far games have been underappreciated in neuroscience research, particularly for rodent studies. In this review, we survey the varieties of competitive and cooperative games that have been tested, contrasting strategies employed by non-human primates and birds with rodents. We provide examples of how games can be used to uncover neural mechanisms and explore species-specific behavioral differences. We assess critically the limitations of current paradigms and propose improvements. Together, the synthesis of current literature highlights the advantages of using games to probe the neural basis of social decisions for neuroscience studies., Competing Interests: Declaration of Interests Authors report no conflict of interest., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

High-frequency stimulation (HFS) is a promising therapy for patients with depression. However, the mechanisms underlying the HFS-induced antidepressant-like effects on susceptibility and resilience to depressive-like behaviors remain obscure. Given that dopaminergic neurotransmission has been found to be disrupted in depression, we investigated the dopamine(DA)-dependent mechanism of the antidepressant-like effects of HFS of the prelimbic cortex (HFS PrL). We performed HFS PrL in a rat model of mild chronic unpredictable stress (CUS) together with 6-hydroxydopamine lesioning in the dorsal raphe nucleus (DRN) and ventral tegmental area (VTA). Animals were assessed for anxiety, anhedonia, and behavioral despair. We also examined levels of corticosterone, hippocampal neurotransmitters, neuroplasticity-related proteins, and morphological changes in dopaminergic neurons. We found 54.3% of CUS animals exhibited decreased sucrose consumption and were designated as CUS-susceptible, while the others were designated CUS-resilient. HFS PrL in both the CUS-susceptible and CUS-resilient animals significantly increased hedonia, reduced anxiety, decreased forced swim immobility, enhanced hippocampal DA and serotonin levels, and reduced corticosterone levels when compared with the respective sham groups. The hedonic-like effects were abolished in both DRN- and VTA-lesioned groups, suggesting the effects of HFS PrL are DA-dependent. Interestingly, VTA-lesioned sham animals had increased anxiety and forced swim immobility, which was reversed by HFS PrL. The VTA-lesioned HFS PrL animals also had elevated DA levels, and reduced p-p38 MAPK and NF-κB levels when compared to VTA-lesioned sham animals. These findings suggest that HFS PrL in stressed animals leads to profound antidepressant-like responses possibly through both DA-dependent and -independent mechanisms.

Background: Coronary artery calcification (CAC), often assessed by computed tomography (CT), is a powerful marker of coronary artery disease that can guide preventive therapies. Computed tomographies, however, are not always accessible or serially obtainable. It remains unclear whether other widespread tests such as transthoracic echocardiograms (TTEs) can be used to predict CAC., Methods: Using a data set of 2,881 TTE videos paired with coronary calcium CTs, we trained a video-based artificial intelligence convolutional neural network to predict CAC scores from parasternal long-axis views. We evaluated the model's ability to classify patients from a held-out sample as well as an external site sample into zero CAC and high CAC (CAC ≥ 400 Agatston units) groups by receiver operating characteristic and precision-recall curves. We also investigated whether such classifications prognosticated significant differences in 1-year mortality rates by the log-rank test of Kaplan-Meier curves., Results: Transthoracic echocardiogram artificial intelligence models had high discriminatory abilities in predicting zero CAC (receiver operating characteristic area under the curve [AUC] = 0.81 [95% CI, 0.74-0.88], F1 score = 0.95) and high CAC (AUC = 0.74 [0.68-0.8], F1 score = 0.74). This performance was confirmed in an external test data set of 92 TTEs (AUC = 0.75 [0.65-0.85], F1 score = 0.77; and AUC = 0.85 [0.76-0.93], F1 score = 0.59, respectively). Risk stratification by TTE-predicted CAC performed similarly to CT CAC scores in prognosticating significant differences in 1-year survival in high-CAC patients (CT CAC ≥ 400 vs CT CAC < 400, P = .03; TTE-predicted CAC ≥ 400 vs TTE-predicted CAC < 400, P = .02)., Conclusions: A video-based deep learning model successfully used TTE videos to predict zero CAC and high CAC with high accuracy. Transthoracic echocardiography-predicted CAC prognosticated differences in 1-year survival similar to CT CAC. Deep learning of TTEs holds promise for future adjunctive coronary artery disease risk stratification to guide preventive therapies., (Published by Elsevier Inc.)

Background: Quantification of chamber size and systolic function is a fundamental component of cardiac imaging. However, the human heart is a complex structure with significant uncharacterized phenotypic variation beyond traditional metrics of size and function. Examining variation in cardiac shape can add to our ability to understand cardiovascular risk and pathophysiology., Methods: We measured the left ventricle (LV) sphericity index (short axis length/long axis length) using deep learning-enabled image segmentation of cardiac magnetic resonance imaging data from the UK Biobank. Subjects with abnormal LV size or systolic function were excluded. The relationship between LV sphericity and cardiomyopathy was assessed using Cox analyses, genome-wide association studies, and two-sample Mendelian randomization., Findings: In a cohort of 38,897 subjects, we show that a one standard deviation increase in sphericity index is associated with a 47% increased incidence of cardiomyopathy (hazard ratio [HR]: 1.47, 95% confidence interval [CI]: 1.10-1.98, p = 0.01) and a 20% increased incidence of atrial fibrillation (HR: 1.20, 95% CI: 1.11-1.28, p < 0.001), independent of clinical factors and traditional magnetic resonance imaging (MRI) measurements. We identify four loci associated with sphericity at genome-wide significance, and Mendelian randomization supports non-ischemic cardiomyopathy as causal for LV sphericity., Conclusions: Variation in LV sphericity in otherwise normal hearts predicts risk for cardiomyopathy and related outcomes and is caused by non-ischemic cardiomyopathy., Funding: This study was supported by grants K99-HL157421 (D.O.) and KL2TR003143 (S.L.C.) from the National Institutes of Health., Competing Interests: Declaration of interests D.L. has received research funding from Abbott Laboratories., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

The drivers of sexual dimorphism in heart failure phenotypes are currently poorly understood. Divergent phenotypes may result from differences in heritability and genetic versus environmental influences on the interplay of cardiac structure and function. To assess sex-specific heritability and genetic versus environmental contributions to variation and inter-relations between echocardiography traits in a large community-based cohort. We studied Framingham Heart Study participants of Offspring Cohort examination 8 (2005-2008) and Third Generation Cohort examination 1 (2002-2005). Five cardiac traits and six functional traits were measured using standardized echocardiography. Sequential Oligogenic Linkage Analysis Routines (SOLAR) software was used to perform singular and bivariate quantitative trait linkage analysis. In our study of 5674 participants (age 49 ± 15 years; 54% women), heritability for all traits was significant for both men and women. There were no significant differences in traits between men and women. Within inter-trait correlations, there were two genetic, and four environmental trait pairs with sex-based differences. Within both significant genetic trait pairs, men had a positive relation, and women had no significant relation. We observed significant sex-based differences in inter-trait genetic and environmental correlations between cardiac structure and function. These findings highlight potential pathways of sex-based divergent heart failure phenotypes., (© 2023. The Author(s).)

Purpose: To extend the MR MultiTasking-based Multidimensional Assessment of Cardiovascular System (MT-MACS) technique with larger spatial coverage and water-fat separation for comprehensive aortocardiac assessment., Methods: MT-MACS adopts a low-rank tensor image model for 7D imaging, with three spatial dimensions for volumetric imaging, one cardiac motion dimension for cine imaging, one respiratory motion dimension for free-breathing imaging, one T2-prepared inversion recovery time dimension for multi-contrast assessment, and one T2*-decay time dimension for water-fat separation. Nine healthy subjects were recruited for the 3T study. Overall image quality was scored on bright-blood (BB), dark-blood (DB), and gray-blood (GB) contrasts using a 4-point scale (0-poor to 3-excellent) by two independent readers, and their interreader agreement was evaluated. Myocardial wall thickness and left ventricular ejection fraction (LVEF) were quantified on DB and BB contrasts, respectively. The agreement in these metrics between MT-MACS and conventional breath-held, electrocardiography-triggered 2D sequences were evaluated., Results: MT-MACS provides both water-only and fat-only images with excellent image quality (average score = 3.725/3.780/3.835/3.890 for BB/DB/GB/fat-only images) and moderate to high interreader agreement (weighted Cohen's kappa value = 0.727/0.668/1.000/1.000 for BB/DB/GB/fat-only images). There were good to excellent agreements in myocardial wall thickness measurements (intraclass correlation coefficients [ICC] = 0.781/0.929/0.680/0.878 for left atria/left ventricle/right atria/right ventricle) and LVEF quantification (ICC = 0.716) between MT-MACS and 2D references. All measurements were within the literature range of healthy subjects., Conclusion: The refined MT-MACS technique provides multi-contrast, phase-resolved, and water-fat imaging of the aortocardiac systems and allows evaluation of anatomy and function. Clinical validation is warranted., (© 2022 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Artificial intelligence (AI) has been developed for echocardiography 1-3 , although it has not yet been tested with blinding and randomization. Here we designed a blinded, randomized non-inferiority clinical trial (ClinicalTrials.gov ID: NCT05140642; no outside funding) of AI versus sonographer initial assessment of left ventricular ejection fraction (LVEF) to evaluate the impact of AI in the interpretation workflow. The primary end point was the change in the LVEF between initial AI or sonographer assessment and final cardiologist assessment, evaluated by the proportion of studies with substantial change (more than 5% change). From 3,769 echocardiographic studies screened, 274 studies were excluded owing to poor image quality. The proportion of studies substantially changed was 16.8% in the AI group and 27.2% in the sonographer group (difference of -10.4%, 95% confidence interval: -13.2% to -7.7%, P < 0.001 for non-inferiority, P < 0.001 for superiority). The mean absolute difference between final cardiologist assessment and independent previous cardiologist assessment was 6.29% in the AI group and 7.23% in the sonographer group (difference of -0.96%, 95% confidence interval: -1.34% to -0.54%, P < 0.001 for superiority). The AI-guided workflow saved time for both sonographers and cardiologists, and cardiologists were not able to distinguish between the initial assessments by AI versus the sonographer (blinding index of 0.088). For patients undergoing echocardiographic quantification of cardiac function, initial assessment of LVEF by AI was non-inferior to assessment by sonographers., (© 2023. The Author(s).)

Background: Individuals with post-acute sequelae of COVID (PASC) may have a persistence in immune activation that differentiates them from individuals who have recovered from COVID without clinical sequelae. To investigate how humoral immune activation may vary in this regard, we compared patterns of vaccine-provoked serological response in patients with PASC compared to individuals recovered from prior COVID without PASC., Methods: We prospectively studied 245 adults clinically diagnosed with PASC and 86 adults successfully recovered from prior COVID. All participants had measures of humoral immunity to SARS-CoV-2 assayed before or after receiving their first-ever administration of COVID vaccination (either single-dose or two-dose regimen), including anti-spike (IgG-S and IgM-S) and anti-nucleocapsid (IgG-N) antibodies as well as IgG-S angiotensin-converting enzyme 2 (ACE2) binding levels. We used unadjusted and multivariable-adjusted regression analyses to examine the association of PASC compared to COVID-recovered status with post-vaccination measures of humoral immunity., Results: Individuals with PASC mounted consistently higher post-vaccination IgG-S antibody levels when compared to COVID-recovered (median log IgG-S 3.98 versus 3.74, P < 0.001), with similar results seen for ACE2 binding levels (median 99.1 versus 98.2, P = 0.044). The post-vaccination IgM-S response in PASC was attenuated but persistently unchanged over time (P = 0.33), compared to in COVID recovery wherein the IgM-S response expectedly decreased over time (P = 0.002). Findings remained consistent when accounting for demographic and clinical variables including indices of index infection severity and comorbidity burden., Conclusion: We found evidence of aberrant immune response distinguishing PASC from recovered COVID. This aberrancy is marked by excess IgG-S activation and ACE2 binding along with findings consistent with a delayed or dysfunctional immunoglobulin class switching, all of which is unmasked by vaccine provocation. These results suggest that measures of aberrant immune response may offer promise as tools for diagnosing and distinguishing PASC from non-PASC phenotypes, in addition to serving as potential targets for intervention., (© 2023. The Author(s).)

Psilocybin is a psychedelic with therapeutic potential. While there is growing evidence that psilocybin exerts its beneficial effects through enhancing neural plasticity, the exact brain regions involved are not completely understood. Determining the impact of psilocybin on plasticity-related gene expression throughout the brain can broaden our understanding of the neural circuits involved in psychedelic-evoked neural plasticity. In this study, whole-brain serial two-photon microscopy and light sheet microscopy were employed to map the expression of the immediate early gene, c-Fos, in male and female mice. The drug-induced c-Fos expression following psilocybin administration was compared to that of subanesthetic ketamine and saline control. Psilocybin and ketamine produced acutely comparable elevations in c-Fos expression in numerous brain regions, including anterior cingulate cortex, locus coeruleus, primary visual cortex, central and basolateral amygdala, medial and lateral habenula, and claustrum. Select regions exhibited drug-preferential differences, such as dorsal raphe and insular cortex for psilocybin and the CA1 subfield of hippocampus for ketamine. To gain insights into the contributions of receptors and cell types, the c-Fos expression maps were related to brain-wide in situ hybridization data. The transcript analyses showed that the endogenous levels of Grin2a and Grin2b predict whether a cortical region is sensitive to drug-evoked neural plasticity for both ketamine and psilocybin. Collectively, the systematic mapping approach produced an unbiased list of brain regions impacted by psilocybin and ketamine. The data are a resource that highlights previously underappreciated regions for future investigations. Furthermore, the robust relationships between drug-evoked c-Fos expression and endogenous transcript distributions suggest glutamatergic receptors as a potential convergent target for how psilocybin and ketamine produce their rapid-acting and long-lasting therapeutic effects.

Background: Coronary microvascular dysfunction (CMD) has differences in prevalence and presentation between women and men; however, we have limited understanding about underlying contributors to sex differences in CMD. Myocardial perfusion reserve index (MPRI), as semi-quantitative measure of myocardial perfusion derived from cardiac magnetic resonance (CMR) imaging has been validated as a measure of CMD. We sought to understand the sex differences in the relations between the MPRI and traditional measures of cardiovascular disease by CMR., Methods: A retrospective analysis of a single-center cohort of patients receiving clinical stress CMR from 2015 to 2022 was performed. Patients with calculated MPRI and no visible perfusion defects consistent with obstructive epicardial coronary disease were included. We compared associations between MPRI versus traditional cardiovascular risk factors and markers of cardiac structure/function in sex-stratified populations using univariable and multivariable regression models., Results: A total of 229 patients [193 female, 36 male, median age 57 (47-67) years] were included in the analysis. In the female population, no traditional cardiovascular risk factors were associated with MPRI, whereas in the male population, diabetes (β: -0.80, p = 0.03) and hyperlipidemia (β: -0.76, p = 0.006) were both associated with reduced MPRI in multivariable models. Multivariable models revealed significant associations between reduced MPRI and increased ascending aortic diameter (β: -0.42, p = 0.005) and T1 times (β: -0.0056, p = 0.03) in the male population, and increased T1 times (β: -0.0037, p = 0.006) and LVMI (β: -0.022, p = 0.0003) in the female population., Conclusion: The findings suggest different underlying pathophysiology of CMD in men versus women, with lower MPRI in male patients fitting a more "traditional" atherosclerotic profile., Competing Interests: JW served on an advisory board for Abbott Vascular, paid to institution. CM serves as Board of Director for iRhythm and Advisory Board member for SHL Telemedicine. DB serves as a consultant with Bayer Pharmaceuticals. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Kwan, Wei, Ouyang, Ebinger, Merz, Berman and Cheng.)

Postural orthostatic tachycardia syndrome (POTS) has been previously described after SARS-CoV-2 infection; however, limited data is available on the relation of POTS with COVID-19 vaccination. Here we show in a cohort of 284,592 COVID-19 vaccinated individuals using a sequence-symmetry analysis, that the odds of POTS are higher 90 days after vaccine exposure than 90 days prior to exposure, and that the odds for POTS are higher than referent conventional primary care diagnoses, but lower than the odds of new POTS diagnosis after SARS-CoV-2 infection. Our results identify a possible association between COVID-19 vaccination and incidence of POTS. Notwithstanding the probable low incidence of POTS after COVID-19 vaccination, particularly when compared to SARS-Cov-2 post-infection odds which were five times higher, our results suggest that further studies, are needed to investigate the incidence and etiology of POTS occurring after COVID-19 vaccination., Competing Interests: COMPETING INTERESTS The authors declare no competing interests.

Psychedelic drugs have reemerged as tools to treat several brain disorders. Cultural attitudes toward them are changing, and scientists are once again investigating the neural mechanisms through which these drugs impact brain function. The significance of this research direction is reflected by recent work, including work presented by these authors at the 2022 meeting of the Society for Neuroscience. As of 2022, there were hundreds of clinical trials recruiting participants for testing the therapeutic effects of psychedelics. Emerging evidence suggests that psychedelic drugs may exert some of their long-lasting therapeutic effects by inducing structural and functional neural plasticity. Herein, basic and clinical research attempting to elucidate the mechanisms of these compounds is showcased. Topics covered include psychedelic receptor binding sites, effects of psychedelics on gene expression, and on dendrites, and psychedelic effects on microcircuitry and brain-wide circuits. We describe unmet clinical needs and the current state of translation to the clinic for psychedelics, as well as other unanswered basic neuroscience questions addressable with future studies., (Copyright © 2022 the authors.)

Psychedelics are serotonin 2A receptor agonists that can lead to profound changes in perception, cognition and mood. In this review, we focus on the basic neurobiology underlying the action of psychedelic drugs. We first discuss chemistry, highlighting the diversity of psychoactive molecules and the principles that govern their potency and pharmacokinetics. We describe the roles of serotonin receptors and their downstream molecular signaling pathways, emphasizing key elements for drug discovery. We consider the impact of psychedelics on neuronal spiking dynamics in several cortical and subcortical regions, along with transcriptional changes and sustained effects on structural plasticity. Finally, we summarize neuroimaging results that pinpoint effects on association cortices and thalamocortical functional connectivity, which inform current theories of psychedelic action. By synthesizing knowledge across the chemical, molecular, neuronal, and network levels, we hope to provide an integrative perspective on the neural mechanisms responsible for the acute and enduring effects of psychedelics on behavior., (© 2022. Springer Nature America, Inc.)

Dopamine signaling from the ventral tegmental area (VTA) plays critical roles in reward-related behaviors, but less is known about the functions of neighboring VTA GABAergic neurons. We show here that a primary target of VTA GABA projection neurons is the ventral pallidum (VP). Activity of VTA-to-VP-projecting GABA neurons correlates consistently with size and palatability of the reward and does not change following cue learning, providing a direct measure of reward value. Chemogenetic stimulation of this GABA projection increased activity of a subset of VP neurons that were active while mice were seeking reward. Optogenetic stimulation of this pathway improved performance in a cue-reward task and maintained motivation to work for reward over days. This VTA GABA projection provides information about reward value directly to the VP, likely distinct from the prediction error signal carried by VTA dopamine neurons.

Background: Hepatic disease is linked to cardiovascular events but the independent association between hepatic and cardiovascular disease remains unclear, given shared risk factors., Methods: This was a retrospective study of consecutive patients with a clinical cardiac MRI (CMR) and a serological marker of hepatic fibrosis, the FIB-4 score, within one year of clinical imaging. We assessed the relations between FIB-4 scores grouped based on prior literature: low (< 1.3), moderate (1.3-3.25), and high (>3.25), and abnormalities detected by comprehensive CMR grouped into 4 domains: cardiac structure (end diastolic volumes, atrial dimensions, wall thickness); cardiac function (ejection fractions, wall motion abnormalities, cardiac output); vascular structure (ascending aortic and pulmonary arterial sizes); and cardiac composition (late gadolinium enhancement, T1 and T2 times). We used Poisson regression to examine the association between the conventionally defined FIB-4 category (low <1.3, moderate 1.3-3.25, and high >3.25) and any CMR abnormality while adjusting for demographics and traditional cardiovascular risk factors., Results: Of the 1668 patients studied (mean age: 55.971 ± 7.28, 901 [54%] male), 85.9% had ≥1 cardiac abnormality with increasing prevalence seen within the low (82.0%) to moderate (88.8%) to high (92.3%) FIB-4 categories. Multivariable analyses demonstrated the presence of any cardiac abnormality was significantly associated with having a high-range FIB-4 (prevalence ratio 1.07, 95% CI: 1.01-1.13); notably, the presence of functional cardiac abnormalities were associated with being in the high FIB-4 range (1.41, 1.21-1.65) and any vascular abnormalities with being in the moderate FIB-4 range (1.22, 1.01-1.47)., Conclusions: Elevated FIB-4 was associated with cardiac functional and vascular abnormalities even after adjustment for shared risk factors in a cohort of patients with clinically referred CMR. These CMR findings indicate that cardiovascular abnormalities exist in the presence of subclinical hepatic fibrosis, irrespective of shared risk factors, underscoring the need for further studies of the heart-liver axis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Kwan, Sun, Driver, Botting, Navarrette, Ouyang, Hussain, Noureddin, Li, Ebinger, Berman and Cheng.)

Purpose: To develop a free-breathing, non-electrocardiogram technique for simultaneous myocardial T 1 , T 2 , T 2 *, and fat-fraction (FF) mapping in a single scan., Methods: The MR Multitasking framework is adapted to quantify T 1 , T 2 , T 2 *, and FF simultaneously. A variable TR scheme is developed to preserve temporal resolution and imaging efficiency. The underlying high-dimensional image is modeled as a low-rank tensor, which allows accelerated acquisition and efficient reconstruction. The accuracy and/or repeatability of the technique were evaluated on static and motion phantoms, 12 healthy volunteers, and 3 patients by comparing to the reference techniques., Results: In static and motion phantoms, T 1 /T 2 /T 2 */FF measurements showed substantial consistency (R > 0.98) and excellent agreement (intraclass correlation coefficient > 0.93) with reference measurements. In human subjects, the proposed technique yielded repeatable T 1 , T 2 , T 2 *, and FF measurements that agreed with those from references., Conclusions: The proposed free-breathing, non-electrocardiogram, motion-resolved Multitasking technique allows simultaneous quantification of myocardial T 1 , T 2 , T 2 *, and FF in a single 2.5-min scan., (© 2022 International Society for Magnetic Resonance in Medicine.)

BACKGROUND Myocarditis is an inflammatory process that can present as acute or chronic with either focal or diffuse involvement of the myocardium. Its incidence is approximately 1.5 million cases per year worldwide. In the United States, viral infection is the most common cause of myocarditis. Most of the reported cases are singular and self-limiting in nature. We present the case of severe recurrent myocarditis in a young adult who was transferred to the Intensive Care Unit. CASE REPORT An 18-year-old man presented with chest pressure and troponin I 33 ng/mL. He had presented to another hospital with similar symptoms 3 months prior and was diagnosed with myocarditis that had resolved with colchicine. As part of his workup during this admission, coronary angiogram was normal and biopsy obtained without evidence of an inflammatory process; however, cardiac magnetic resonance imaging (MRI) was consistent with myocarditis and Coxsackie B titers indicated prior infection, leading to a diagnosis of clinically suspected recurrent viral myocarditis. He was treated with intravenous immunoglobulin (IV Ig) and a steroid taper, with rapid improvement in symptoms over the ensuing weeks without evidence of further recurrence or sequelae. CONCLUSIONS We present a case of recurrent Coxsackie B myocarditis based on presentation and imaging. Myocarditis is an important diagnosis to consider when a young, healthy individual presents with chest pain mimicking acute coronary syndrome, especially during the COVID pandemic. If there is evidence of myocarditis on MRI or endomyocardial biopsy, immunosuppressive therapy should be considered in patients with recurrent and severe presentations.