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.

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.

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.

Prediction of Central Visual Field Measures From Macular OCT Volume Scans With Deep Learning.

Purpose: Predict central 10° global and local visual field (VF) measurements from macular optical coherence tomography (OCT) volume scans with deep learning (DL). Methods: This study included 1121 OCT volume scans and 10-2 VFs from 289 eyes (257 patients). Macular scans were used to estimate 10-2 VF mean deviation (MD), threshold sensitivities (TS), and total deviation (TD) values at 68 locations. A three-dimensional (3D) convolutional neural network based on the 3D DenseNet121 architecture was used for prediction. We compared DL predictions to those from baseline linear models. We carried out 10-fold stratified cross-validation to optimize generalizability. The performance of the DL and baseline models was compared based on correlations between ground truth and predicted VF measures and mean absolute error (MAE; ground truth - predicted values). Results: Average (SD) MD was -9.3 (7.7) dB. Average (SD) correlations between predicted and ground truth MD and MD MAE were 0.74 (0.09) and 3.5 (0.4) dB, respectively. Estimation accuracy deteriorated with worsening MD. Average (SD) Pearson correlations between predicted and ground truth TS and MAEs for DL and baseline model were 0.71 (0.05) and 0.52 (0.05) (P < 0.001) and 6.5 (0.6) and 7.5 (0.5) dB (P < 0.001), respectively. For TD, correlation (SD) and MAE (SD) for DL and baseline models were 0.69 (0.02) and 0.48 (0.05) (P < 0.001) and 6.1 (0.5) and 7.8 (0.5) dB (P < 0.001), respectively. Conclusions: Macular OCT volume scans can be used to predict global central VF parameters with clinically relevant accuracy. Translational Relevance: Macular OCT imaging may be used to confirm and supplement central VF findings using deep learning.

Long-term vaccination strategies to mitigate the impact of SARS-CoV-2 transmission: A modelling study.

BACKGROUND: Vaccines have reduced severe disease and death from Coronavirus Disease 2019 (COVID-19). However, with evidence of waning efficacy coupled with continued evolution of the virus, health programmes need to evaluate the requirement for regular booster doses, considering their impact and cost-effectiveness in the face of ongoing transmission and substantial infection-induced immunity. METHODS AND FINDINGS: We developed a combined immunological-transmission model parameterised with data on transmissibility, severity, and vaccine effectiveness. We simulated Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) transmission and vaccine rollout in characteristic global settings with different population age-structures, contact patterns, health system capacities, prior transmission, and vaccine uptake. We quantified the impact of future vaccine booster dose strategies with both ancestral and variant-adapted vaccine products, while considering the potential future emergence of new variants with modified transmission, immune escape, and severity properties. We found that regular boosting of the oldest age group (75+) is an efficient strategy, although large numbers of hospitalisations and deaths could be averted by extending vaccination to younger age groups. In countries with low vaccine coverage and high infection-derived immunity, boosting older at-risk groups was more effective than continuing primary vaccination into younger ages in our model. Our study is limited by uncertainty in key parameters, including the long-term durability of vaccine and infection-induced immunity as well as uncertainty in the future evolution of the virus. CONCLUSIONS: Our modelling suggests that regular boosting of the high-risk population remains an important tool to reduce morbidity and mortality from current and future SARS-CoV-2 variants. Our results suggest that focusing vaccination in the highest-risk cohorts will be the most efficient (and hence cost-effective) strategy to reduce morbidity and mortality.

Prediction of visual field progression with serial optic disc photographs using deep learning.

AIM: We tested the hypothesis that visual field (VF) progression can be predicted with a deep learning model based on longitudinal pairs of optic disc photographs (ODP) acquired at earlier time points during follow-up. METHODS: 3919 eyes (2259 patients) with ≥2 ODPs at least 2 years apart, and ≥5 24-2 VF exams spanning ≥3 years of follow-up were included. Serial VF mean deviation (MD) rates of change were estimated starting at the fifth visit and subsequently by adding visits until final visit. VF progression was defined as a statistically significant negative slope at two consecutive visits and final visit. We built a twin-neural network with ResNet50-backbone. A pair of ODPs acquired up to a year before the VF progression date or the last VF in non-progressing eyes were included as input. Primary outcome measures were area under the receiver operating characteristic curve (AUC) and model accuracy. RESULTS: The average (SD) follow-up time and baseline VF MD were 8.1 (4.8) years and -3.3 (4.9) dB, respectively. VF progression was identified in 761 eyes (19%). The median (IQR) time to progression in progressing eyes was 7.3 (4.5-11.1) years. The AUC and accuracy for predicting VF progression were 0.862 (0.812-0.913) and 80.0% (73.9%-84.6%). When only fast-progressing eyes were considered (MD rate < -1.0 dB/year), AUC increased to 0.926 (0.857-0.994). CONCLUSIONS: A deep learning model can predict subsequent glaucoma progression from longitudinal ODPs with clinically relevant accuracy. This model may be implemented, after validation, for predicting glaucoma progression in the clinical setting.

Expansions to the MGDrivE suite for simulating the efficacy of novel gene-drive constructs in the control of mosquito-borne diseases.

OBJECTIVE: The MGDrivE (MGDrivE 1 and MGDrivE 2) modeling framework provides a flexible and expansive environment for testing the efficacy of novel gene-drive constructs for the control of mosquito-borne diseases. However, the existing model framework did not previously support several features necessary to simulate some types of intervention strategies. Namely, current MGDrivE versions do not permit modeling of small molecule inducible systems for controlling gene expression in gene drive designs or the inheritance patterns of self-eliminating gene drive mechanisms. RESULTS: Here, we demonstrate a new MGDrivE 2 module that permits the simulation of gene drive strategies incorporating small molecule-inducible systems and self-eliminating gene drive mechanisms. Additionally, we also implemented novel sparsity-aware sampling algorithms for improved computational efficiency in MGDrivE 2 and supplied an analysis and plotting function applicable to the outputs of MGDrivE 1 and MGDrivE 2.

Notch and retinoic acid signals regulate macrophage formation from endocardium downstream of Nkx2-5.

Hematopoietic progenitors are enriched in the endocardial cushion and contribute, in a Nkx2-5-dependent manner, to tissue macrophages required for the remodeling of cardiac valves and septa. However, little is known about the molecular mechanism of endocardial-hematopoietic transition. In the current study, we identified the regulatory network of endocardial hematopoiesis. Signal network analysis from scRNA-seq datasets revealed that genes in Notch and retinoic acid (RA) signaling are significantly downregulated in Nkx2-5-null endocardial cells. In vivo and ex vivo analyses validate that the Nkx2-5-Notch axis is essential for the generation of both hemogenic and cushion endocardial cells, and the suppression of RA signaling via Dhrs3 expression plays important roles in further differentiation into macrophages. Genetic ablation study revealed that these macrophages are essential in cardiac valve remodeling. In summary, the study demonstrates that the Nkx2-5/Notch/RA signaling plays a pivotal role in macrophage differentiation from hematopoietic progenitors.

Harnessing developmental cues for cardiomyocyte production.

Developmental research has attempted to untangle the exact signals that control heart growth and size, with knockout studies in mice identifying pivotal roles for Wnt and Hippo signaling during embryonic and fetal heart growth. Despite this improved understanding, no clinically relevant therapies are yet available to compensate for the loss of functional adult myocardium and the absence of mature cardiomyocyte renewal that underlies cardiomyopathies of multiple origins. It remains of great interest to understand which mechanisms are responsible for the decline in proliferation in adult hearts and to elucidate new strategies for the stimulation of cardiac regeneration. Multiple signaling pathways have been identified that regulate the proliferation of cardiomyocytes in the embryonic heart and appear to be upregulated in postnatal injured hearts. In this Review, we highlight the interaction of signaling pathways in heart development and discuss how this knowledge has been translated into current technologies for cardiomyocyte production.

Rapid model-guided design of organ-scale synthetic vasculature for biomanufacturing.

Our ability to produce human-scale bio-manufactured organs is critically limited by the need for vascularization and perfusion. For tissues of variable size and shape, including arbitrarily complex geometries, designing and printing vasculature capable of adequate perfusion has posed a major hurdle. Here, we introduce a model-driven design pipeline combining accelerated optimization methods for fast synthetic vascular tree generation and computational hemodynamics models. We demonstrate rapid generation, simulation, and 3D printing of synthetic vasculature in complex geometries, from small tissue constructs to organ scale networks. We introduce key algorithmic advances that all together accelerate synthetic vascular generation by more than 230 -fold compared to standard methods and enable their use in arbitrarily complex shapes through localized implicit functions. Furthermore, we provide techniques for joining vascular trees into watertight networks suitable for hemodynamic CFD and 3D fabrication. We demonstrate that organ-scale vascular network models can be generated in silico within minutes and can be used to perfuse engineered and anatomic models including a bioreactor, annulus, bi-ventricular heart, and gyrus. We further show that this flexible pipeline can be applied to two common modes of bioprinting with free-form reversible embedding of suspended hydrogels and writing into soft matter. Our synthetic vascular tree generation pipeline enables rapid, scalable vascular model generation and fluid analysis for bio-manufactured tissues necessary for future scale up and production.

Estimating long-term vaccine effectiveness against SARS-CoV-2 variants: a model-based approach.

With the ongoing evolution of the SARS-CoV-2 virus updated vaccines may be needed. We fitted a model linking immunity levels and protection to vaccine effectiveness data from England for three vaccines (Oxford/AstraZeneca AZD1222, Pfizer-BioNTech BNT162b2, Moderna mRNA-1273) and two variants (Delta, Omicron). Our model reproduces the observed sustained protection against hospitalisation and death from the Omicron variant over the first six months following dose 3 with the ancestral vaccines but projects a gradual waning to moderate protection after 1 year. Switching the fourth dose to a variant-matched vaccine against Omicron BA.1/2 is projected to prevent nearly twice as many hospitalisations and deaths over a 1-year period compared to administering the ancestral vaccine. This result is sensitive to the degree to which immunogenicity data can be used to predict vaccine effectiveness and uncertainty regarding the impact that infection-induced immunity (not captured here) may play in modifying future vaccine effectiveness.

Spatial dynamics of malaria transmission.

The Ross-Macdonald model has exerted enormous influence over the study of malaria transmission dynamics and control, but it lacked features to describe parasite dispersal, travel, and other important aspects of heterogeneous transmission. Here, we present a patch-based differential equation modeling framework that extends the Ross-Macdonald model with sufficient skill and complexity to support planning, monitoring and evaluation for Plasmodium falciparum malaria control. We designed a generic interface for building structured, spatial models of malaria transmission based on a new algorithm for mosquito blood feeding. We developed new algorithms to simulate adult mosquito demography, dispersal, and egg laying in response to resource availability. The core dynamical components describing mosquito ecology and malaria transmission were decomposed, redesigned and reassembled into a modular framework. Structural elements in the framework-human population strata, patches, and aquatic habitats-interact through a flexible design that facilitates construction of ensembles of models with scalable complexity to support robust analytics for malaria policy and adaptive malaria control. We propose updated definitions for the human biting rate and entomological inoculation rates. We present new formulas to describe parasite dispersal and spatial dynamics under steady state conditions, including the human biting rates, parasite dispersal, the "vectorial capacity matrix," a human transmitting capacity distribution matrix, and threshold conditions. An [Formula: see text] package that implements the framework, solves the differential equations, and computes spatial metrics for models developed in this framework has been developed. Development of the model and metrics have focused on malaria, but since the framework is modular, the same ideas and software can be applied to other mosquito-borne pathogen systems.

Multi-scale models reveal hypertrophic cardiomyopathy MYH7 G256E mutation drives hypercontractility and elevated mitochondrial respiration.

Rationale: Over 200 mutations in the sarcomeric protein ß-myosin heavy chain (MYH7) have been linked to hypertrophic cardiomyopathy (HCM). However, different mutations in MYH7 lead to variable penetrance and clinical severity, and alter myosin function to varying degrees, making it difficult to determine genotype-phenotype relationships, especially when caused by rare gene variants such as the G256E mutation. Objective: This study aims to determine the effects of low penetrant MYH7 G256E mutation on myosin function. We hypothesize that the G256E mutation would alter myosin function, precipitating compensatory responses in cellular functions. Methods: We developed a collaborative pipeline to characterize myosin function at multiple scales (protein to myofibril to cell to tissue). We also used our previously published data on other mutations to compare the degree to which myosin function was altered. Results: At the protein level, the G256E mutation disrupts the transducer region of the S1 head and reduces the fraction of myosin in the folded-back state by 50.9%, suggesting more myosins available for contraction. Myofibrils isolated from hiPSC-CMs CRISPR-edited with G256E (MYH7 WT/G256E ) generated greater tension, had faster tension development and slower early phase relaxation, suggesting altered myosin-actin crossbridge cycling kinetics. This hypercontractile phenotype persisted in single-cell hiPSC-CMs and engineered heart tissues. Single-cell transcriptomic and metabolic profiling demonstrated upregulation of mitochondrial genes and increased mitochondrial respiration, suggesting altered bioenergetics as an early feature of HCM. Conclusions: MYH7 G256E mutation causes structural instability in the transducer region, leading to hypercontractility across scales, perhaps from increased myosin recruitment and altered crossbridge cycling. Hypercontractile function of the mutant myosin was accompanied by increased mitochondrial respiration, while cellular hypertrophy was modest in the physiological stiffness environment. We believe that this multi-scale platform will be useful to elucidate genotype-phenotype relationships underlying other genetic cardiovascular diseases.

Combined lineage tracing and scRNA-seq reveals unexpected first heart field predominance of human iPSC differentiation.

During mammalian development, the left and right ventricles arise from early populations of cardiac progenitors known as the first and second heart fields, respectively. While these populations have been extensively studied in non-human model systems, their identification and study in vivo human tissues have been limited due to the ethical and technical limitations of accessing gastrulation-stage human embryos. Human-induced pluripotent stem cells (hiPSCs) present an exciting alternative for modeling early human embryogenesis due to their well-established ability to differentiate into all embryonic germ layers. Here, we describe the development of a TBX5/MYL2 lineage tracing reporter system that allows for the identification of FHF- progenitors and their descendants including left ventricular cardiomyocytes. Furthermore, using single-cell RNA sequencing (scRNA-seq) with oligonucleotide-based sample multiplexing, we extensively profiled differentiating hiPSCs across 12 timepoints in two independent iPSC lines. Surprisingly, our reporter system and scRNA-seq analysis revealed a predominance of FHF differentiation using the small molecule Wnt-based 2D differentiation protocol. We compared this data with existing murine and 3D cardiac organoid scRNA-seq data and confirmed the dominance of left ventricular cardiomyocytes (>90%) in our hiPSC-derived progeny. Together, our work provides the scientific community with a powerful new genetic lineage tracing approach as well as a single-cell transcriptomic atlas of hiPSCs undergoing cardiac differentiation.

Safety and Efficacy of a Novel, Variable-Sequenced, Long-Pulsed, 532-nm and 1,064-nm Laser With Cryogen Spray Cooling for Pigmented and Vascular Lesions.

BACKGROUND: Patients frequently seek treatment for vascular and pigmented lesions. More recently, a novel, variable-sequenced, long-pulsed, 532-nm and 1,064-nm laser with cryogen spray cooling was developed to offer greater flexibility in treatments. OBJECTIVE: A prospective clinical trial evaluated the safety and efficacy of a novel, variable-sequenced, long-pulsed, 532-nm and 1,064-nm laser with cryogen spray cooling (DermaV, Lutronic, South Korea). MATERIALS AND METHODS: Subjects with vascular and/or pigmented lesions were enrolled and underwent laser treatments. RESULTS: Twenty-three subjects were enrolled with vascular lesions (39.1%), pigmented lesions (17.4%), and both (43.5%). Mean age was 53.1 years, and 91.3% were women. Fitzpatrick skin types II-IV were included. All subjects were treated with 532 nm, and 4 were also treated with 1,064 nm. According to 4 blinded physician reviewers, correct before and after photographs were selected in 94.7%, 92.1%, 84.2%, and 76.3% of cases. Overall, 86.8% were responders, meaning that at least 3 of 4 reviewers agreed. For Global Aesthetic Improvement Scale, improvement occurred in 81.6%, 81.6%, 81.6%, and 76.3% of cases. No serious adverse events occurred. Overall, 87.0% of subjects reported being very satisfied or satisfied. CONCLUSION: A novel, variable-sequenced, long-pulsed, 532-nm and 1,064-nm laser with cryogen spray cooling can safely and effectively improve vascular and pigmented lesions.