Cardiac Development at a Single-Cell Resolution.

Mammalian cardiac development is a complex, multistage process. Though traditional lineage tracing studies have characterized the broad trajectories of cardiac progenitors, the advent and rapid optimization of single-cell RNA sequencing methods have yielded an ever-expanding toolkit for characterizing heterogeneous cell populations in the developing heart. Importantly, they have allowed for a robust profiling of the spatiotemporal transcriptomic landscape of the human and mouse heart, revealing the diversity of cardiac cells-myocyte and non-myocyte-over the course of development. These studies have yielded insights into novel cardiac progenitor populations, chamber-specific developmental signatures, the gene regulatory networks governing cardiac development, and, thus, the etiologies of congenital heart diseases. Furthermore, single-cell RNA sequencing has allowed for the exquisite characterization of distinct cardiac populations such as the hard-to-capture cardiac conduction system and the intracardiac immune population. Therefore, single-cell profiling has also resulted in new insights into the regulation of cardiac regeneration and injury repair. Single-cell multiomics approaches combining transcriptomics, genomics, and epigenomics may uncover an even more comprehensive atlas of human cardiac biology. Single-cell analyses of the developing and adult mammalian heart offer an unprecedented look into the fundamental mechanisms of cardiac development and the complex diseases that may arise from it.

Incomplete-penetrant hypertrophic cardiomyopathy MYH7 G256E mutation causes hypercontractility and elevated mitochondrial respiration.

Determining the pathogenicity of hypertrophic cardiomyopathy-associated mutations in the ß-myosin heavy chain (MYH7) can be challenging due to its variable penetrance and clinical severity. This study investigates the early pathogenic effects of the incomplete-penetrant MYH7 G256E mutation on myosin function that may trigger pathogenic adaptations and hypertrophy. We hypothesized that the G256E mutation would alter myosin biomechanical function, leading to changes in cellular functions. We developed a collaborative pipeline to characterize myosin function across protein, myofibril, cell, and tissue levels to determine the multiscale effects on structure-function of the contractile apparatus and its implications for gene regulation and metabolic state. The G256E mutation disrupts the transducer region of the S1 head and reduces the fraction of myosin in the folded-back state by 33%, resulting in more myosin heads available for contraction. Myofibrils from gene-edited MYH7WT/G256E human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) exhibited greater and faster tension development. This hypercontractile phenotype persisted in single-cell hiPSC-CMs and engineered heart tissues. We demonstrated consistent hypercontractile myosin function as a primary consequence of the MYH7 G256E mutation across scales, highlighting the pathogenicity of this gene variant. Single-cell transcriptomic and metabolic profiling demonstrated upregulated mitochondrial genes and increased mitochondrial respiration, indicating early bioenergetic alterations. This work highlights the benefit of our multiscale platform to systematically evaluate the pathogenicity of gene variants at the protein and contractile organelle level and their early consequences on cellular and tissue function. We believe this platform can help elucidate the genotype-phenotype relationships underlying other genetic cardiovascular diseases.

The cardiac conduction system: History, development, and disease.

The heart is the first organ to form during embryonic development, establishing the circulatory infrastructure necessary to sustain life and enable downstream organogenesis. Critical to the heart's function is its ability to initiate and propagate electrical impulses that allow for the coordinated contraction and relaxation of its chambers, and thus, the movement of blood and nutrients. Several specialized structures within the heart, collectively known as the cardiac conduction system (CCS), are responsible for this phenomenon. In this review, we discuss the discovery and scientific history of the mammalian cardiac conduction system as well as the key genes and transcription factors implicated in the formation of its major structures. We also describe known human diseases related to CCS development and explore existing challenges in the clinical context.

Laser-assisted see-through technology for locating sound sources inside a structure.

A laser-assisted see-through technology is developed to locate sound sources inside a structure and to analyze the interior sound field. Six lasers were employed to measure simultaneously the normal velocities on the exterior surface. These input data were used to locate sound sources inside a solid structure using a passive sonic detection and ranging algorithm, and then to reconstruct the interior sound field using the Helmholtz equation least squares method, and finally to observe the changes of the interior sound field over time through computer tomography. If signals are time invariant, all these can be accomplished with two lasers, one being fixed and another moving around to measure the normal surface velocity sequentially to establish transfer function with respect to the stationary laser. Once the transfer functions are established, they can be multiplied by any segment of time-domain signals measured by the fixed laser to acquire multiple normal surface velocities, as if they were measured simultaneously. This laser-assisted see-through technology has been validated experimentally and employed to observe the aerodynamically-induced sound field generated by a blower inside a projector. This development is important as it signifies a significant advancement in sound source localization, and opens the door to a class of applications presently unattainable.

Prediction of Visual Field Progression with Baseline and Longitudinal Structural Measurements Using Deep Learning.

PURPOSE: Identifying glaucoma patients at high risk of progression based on widely available structural data is an unmet task in clinical practice. We test the hypothesis that baseline or serial structural measures can predict visual field (VF) progression with deep learning (DL). DESIGN: Development of a DL algorithm to predict VF progression. METHODS: 3,079 eyes (1,765 patients) with various types of glaucoma and ≥5 VFs, and ≥3 years of follow-up from a tertiary academic center were included. Serial VF mean deviation (MD) rates of change were estimated with linear-regression. VF progression was defined as negative MD slope with p<0.05. A Siamese Neural Network with ResNet-152 backbone pre-trained on ImageNet was designed to predict VF progression using serial optic-disc photographs (ODP), and baseline retinal nerve fiber layer (RNFL) thickness. We tested the model on a separate dataset (427 eyes) with RNFL data from different OCT. The Main Outcome Measure was Area under ROC curve (AUC). RESULTS: Baseline average (SD) MD was 3.4 (4.9)dB. VF progression was detected in 900 eyes (29%). AUC (95% CI) for model incorporating baseline ODP and RNFL thickness was 0.813 (0.757-0.869). After adding the second and third ODPs, AUC increased to 0.860 and 0.894, respectively (p<0.027). This model also had highest AUC (0.911) for predicting fast progression (MD rate <1.0 dB/year). Model's performance was similar when applied to second dataset using RNFL data from another OCT device (AUC=0.893; 0.837-0.948). CONCLUSIONS: DL model predicted VF progression with clinically relevant accuracy using baseline RNFL thickness and serial ODPs and can be implemented as a clinical tool after further validation.

THE IMPACT OF ROUTINE CARDIAC TROPONIN I-BASED CARDIOTOXICITY SCREENING ON CLINICAL OUTCOMES IN PATIENTS ON CANCER IMMUNOTHERAPY.

Purpose: Immune checkpoint inhibitors (ICI) used as cancer therapy have been associated with a range of cardiac immune-related adverse events (irAEs), including fulminant myocarditis with a high case fatality rate. Early detection through cardiotoxicity screening by biomarker monitoring can lead to prompt intervention and improved patient outcomes. In this study, we investigate the association between cardiotoxicity screening with routine serial troponin I monitoring in asymptomatic patients receiving ICI, cardiovascular adverse event (CV AE) detection, and overall survival (OS). Methods: We instituted a standardized troponin I screening protocol at baseline and with each ICI dose (every 2-4 weeks) in all patients receiving ICI at our center starting Jan 2019. We subsequently collected data in 825 patients receiving ICI at our institution from January 2018 to October 2021. Of these patients, 428 underwent cardiotoxicity screening with serial troponin I monitoring during ICI administration (Jan 2019-Oct 2021) and 397 patients were unmonitored (Jan 2018-Dec 2018). We followed patients for nine months following their first dose of ICI and compared outcomes of CV AEs and OS between monitored and unmonitored patients. Additionally, we investigated rates of CV AEs, all-cause mortality, and oncologic time-to-treatment failure (TTF) between patients with an elevated troponin I value during the monitoring period versus patients without elevated troponin I. Results: We found a lower rate of severe (grades 4-5) CV AEs, resulting in critical illness or death, in patients who underwent troponin monitoring (0.5%) compared to patients who did not undergo monitoring (1.8%), (HR 0.17, 95% CI 0.02-0.79, p = 0.04). There was no difference in overall CV AEs (grades 3-5) or OS between monitored and unmonitored patients. In the entire cohort, patients with at least one elevated troponin I during the follow up period, during routine monitoring or unmonitored, had a higher risk of overall CV AEs (HR 10.96, 95% CI 4.65-25.85, p<0.001) as well as overall mortality (HR 2.67, 95% CI 1.69 - 4.10, p<0.001) compared to those without elevated troponin. Oncologic time-to-treatment failure (TTF) was not significantly different in a sub-cohort of monitored vs. unmonitored patients. Conclusions: Patients undergoing cardiotoxicity screening with troponin I monitoring during ICI therapy had a lower rate of severe (grade 4-5) CV AEs compared patients who were not screened. Troponin I elevation in screened and unscreened patients was significantly associated with increased CV AEs as well as increased mortality. Troponin I monitoring did not impact oncologic time-to-treatment-failure in a sub-cohort analysis of patients treated with ICI. These results provide preliminary evidence for clinical utility of cardiotoxicity screening with troponin I monitoring in patients receiving ICI therapy.