Computational design of custom therapeutic cells to correct failing human cardiomyocytes

Background: Myocardial delivery of non-excitable cells—namely human mesenchymal stem cells (hMSCs) and c-kit+ cardiac interstitial cells (hCICs)—remains a promising approach for treating the failing heart. Recent empirical studies attempt to improve such therapies by genetically engineering cells to express specific ion channels, or by creating hybrid cells with combined channel expression. This study uses a computational modeling approach to test the hypothesis that custom hypothetical cells can be rationally designed to restore a healthy phenotype when coupled to human heart failure (HF) cardiomyocytes.Methods: Candidate custom cells were simulated with a combination of ion channels from non-excitable cells and healthy human cardiomyocytes (hCMs). Using a genetic algorithm-based optimization approach, candidate cells were accepted if a root mean square error (RMSE) of less than 50% relative to healthy hCM was achieved for both action potential and calcium transient waveforms for the cell-treated HF cardiomyocyte, normalized to the untreated HF cardiomyocyte.Results: Custom cells expressing only non-excitable ion channels were inadequate to restore a healthy cardiac phenotype when coupled to either fibrotic or non-fibrotic HF cardiomyocytes. In contrast, custom cells also expressing cardiac ion channels led to acceptable restoration of a healthy cardiomyocyte phenotype when coupled to fibrotic, but not non-fibrotic, HF cardiomyocytes. Incorporating the cardiomyocyte inward rectifier K+ channel was critical to accomplishing this phenotypic rescue while also improving single-cell action potential metrics associated with arrhythmias, namely resting membrane potential and action potential duration. The computational approach also provided insight into the rescue mechanisms, whereby heterocellular coupling enhanced cardiomyocyte L-type calcium current and promoted calcium-induced calcium release. Finally, as a therapeutically translatable strategy, we simulated delivery of hMSCs and hCICs genetically engineered to express the cardiomyocyte inward rectifier K+ channel, which decreased action potential and calcium transient RMSEs by at least 24% relative to control hMSCs and hCICs, with more favorable single-cell arrhythmia metrics.Conclusion: Computational modeling facilitates exploration of customizable engineered cell therapies. Optimized cells expressing cardiac ion channels restored healthy action potential and calcium handling phenotypes in fibrotic HF cardiomyocytes and improved single-cell arrhythmia metrics, warranting further experimental validation studies of the proposed custom therapeutic cells

Benchmarking mortality risk prediction from electrocardiograms

Several recent high-impact studies leverage large hospital-owned electrocardiographic (ECG) databases to model and predict patient mortality. MIMIC-IV, released September 2023, is the first comparable public dataset and includes 800,000 ECGs from a U.S. hospital system. Previously, the largest public ECG dataset was Code-15, containing 345,000 ECGs collected during routine care in Brazil. These datasets now provide an excellent resource for a broader audience to explore ECG survival modeling. Here, we benchmark survival model performance on Code-15 and MIMIC-IV with two neural network architectures, compare four deep survival modeling approaches to Cox regressions trained on classifier outputs, and evaluate performance at one to ten years. Our results yield AUROC and concordance scores comparable to past work (circa 0.8) and reasonable AUPRC scores (MIMIC-IV: 0.4-0.5, Code-15: 0.05-0.13) considering the fraction of ECG samples linked to a mortality (MIMIC-IV: 27\%, Code-15: 4\%). When evaluating models on the opposite dataset, AUROC and concordance values drop by 0.1-0.15, which may be due to cohort differences. All code and results are made public.Comment: 9 pages plus appendix, 2 figure

Ca2+ Cycling Impairment in Heart Failure Is Exacerbated by Fibrosis: Insights Gained From Mechanistic Simulations

[EN] Heart failure (HF) is characterized by altered Ca2+ cycling, resulting in cardiac contractile dysfunction. Failing myocytes undergo electrophysiological remodeling, which is known to be the main cause of abnormal Ca2+ homeostasis. However, structural remodeling, specifically proliferating fibroblasts coupled to myocytes in the failing heart, could also contribute to Ca2+ cycling impairment. The goal of the present study was to systematically analyze the mechanisms by which myocyte-fibroblast coupling could affect Ca2+ dynamics in normal conditions and in HF. Simulations of healthy and failing human myocytes were performed using established mathematical models, and cells were either isolated or coupled to fibroblasts. Univariate and multivariate sensitivity analyses were performed to quantify effects of ion transport pathways on biomarkers computed from intracellular [Ca2+] waveforms. Variability in ion channels and pumps was imposed and populations of models were analyzed to determine effects on Ca2+ dynamics. Our results suggest that both univariate and multivariate sensitivity analyses are valuable methodologies to shed light into the ionic mechanisms underlying Ca2+ impairment in HF, although differences between the two methodologies are observed at high parameter variability. These can result from either the fact that multivariate analyses take into account ion channels or non-linear effects of ion transport pathways on Ca2+ dynamics. Coupling either healthy or failing myocytes to fibroblasts decreased Ca2+ transients due to an indirect sink effect on action potential and thus on Ca2+ related currents. Simulations that investigated restoration of normal physiology in failing myocytes showed that Ca2+ cycling can be normalized by increasing SERCA and L-type Ca2+ current activity while decreasing Na+-Ca2+ exchange and SR Ca2+ leak. Changes required to normalize action potentials in failing myocytes depended on whether myocytes were coupled to fibroblasts. In conclusion, univariate and multivariate sensitivity analyses are helpful tools to understand how Ca2+ cycling is impaired in heart failure and how this can be exacerbated by coupling of myocytes to fibroblasts. The design of pharmacological actions to restore normal activity should take into account the degree of fibrosis in the failing heart.This work was partially supported by the National Science Foundation (MCB 1615677), the American Heart Association (15GRNT25490006), the "Plan Estatal de Investigacion Cientifica y Tecnica y de Innovacion 2013-2016 from the Ministerio de Economia, Industria y Competitividad of Spain and Fondo Europeo de Desarrollo Regional (FEDER) DPI2016-75799-R (AEI/FEDER, UE)", and the "Programa de Ayudas de Investigacion y Desarrollo (PAID-01-17)" from the Universitat Politecnica de Valencia. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Mora-Fenoll, MT.; Ferrero De Loma-Osorio, JM.; Gómez García, JF.; Sobie, EA.; Trenor Gomis, BA. (2018). Ca2+ Cycling Impairment in Heart Failure Is Exacerbated by Fibrosis: Insights Gained From Mechanistic Simulations. Frontiers in Physiology. 9. https://doi.org/10.3389/fphys.2018.01194S9Aguilar, M., Qi, X. Y., Huang, H., Comtois, P., & Nattel, S. (2014). Fibroblast Electrical Remodeling in Heart Failure and Potential Effects on Atrial Fibrillation. Biophysical Journal, 107(10), 2444-2455. doi:10.1016/j.bpj.2014.10.014R. ALPERT, N., HASENFUSS, G., J. LEAVITT, B., P. ITTLEMAN, F., PIESKE, B., & A. MULIERI, L. (2000). A Mechanistic Analysis of Reduced Mechanical Performance in Human Heart Failure. Japanese Heart Journal, 41(2), 103-116. doi:10.1536/jhj.41.103Bers, D. M. (2000). Calcium Fluxes Involved in Control of Cardiac Myocyte Contraction. Circulation Research, 87(4), 275-281. doi:10.1161/01.res.87.4.275Britton, O. J., Bueno-Orovio, A., Virág, L., Varró, A., & Rodriguez, B. (2017). The Electrogenic Na+/K+ Pump Is a Key Determinant of Repolarization Abnormality Susceptibility in Human Ventricular Cardiomyocytes: A Population-Based Simulation Study. Frontiers in Physiology, 8. doi:10.3389/fphys.2017.00278Brown, T. R., Krogh-Madsen, T., & Christini, D. J. (2016). Illuminating Myocyte-Fibroblast Homotypic and Heterotypic Gap Junction Dynamics Using Dynamic Clamp. Biophysical Journal, 111(4), 785-797. doi:10.1016/j.bpj.2016.06.042Cabo, C., & Boyden, P. A. (2009). Extracellular Space Attenuates the Effect of Gap Junctional Remodeling on Wave Propagation: A Computational Study. Biophysical Journal, 96(8), 3092-3101. doi:10.1016/j.bpj.2009.01.014Cartledge, J. E., Kane, C., Dias, P., Tesfom, M., Clarke, L., Mckee, B., … Terracciano, C. M. (2015). Functional crosstalk between cardiac fibroblasts and adult cardiomyocytes by soluble mediators. Cardiovascular Research, 105(3), 260-270. doi:10.1093/cvr/cvu264Chen, J.-B., Tao, R., Sun, H.-Y., Tse, H.-F., Lau, C.-P., & Li, G.-R. (2009). Multiple Ca2+signaling pathways regulate intracellular Ca2+activity in human cardiac fibroblasts. Journal of Cellular Physiology, n/a-n/a. doi:10.1002/jcp.22010Chilton, L., Giles, W. R., & Smith, G. L. (2007). Evidence of intercellular coupling between co-cultured adult rabbit ventricular myocytes and myofibroblasts. The Journal of Physiology, 583(1), 225-236. doi:10.1113/jphysiol.2007.135038Chilton, L., Ohya, S., Freed, D., George, E., Drobic, V., Shibukawa, Y., … Giles, W. R. (2005). K+ currents regulate the resting membrane potential, proliferation, and contractile responses in ventricular fibroblasts and myofibroblasts. American Journal of Physiology-Heart and Circulatory Physiology, 288(6), H2931-H2939. doi:10.1152/ajpheart.01220.2004Cummins, M. A., Dalal, P. J., Bugana, M., Severi, S., & Sobie, E. A. (2014). Comprehensive Analyses of Ventricular Myocyte Models Identify Targets Exhibiting Favorable Rate Dependence. PLoS Computational Biology, 10(3), e1003543. doi:10.1371/journal.pcbi.1003543Drouin, E., Lande, G., & Charpentier, F. (1998). Amiodarone reduces transmural heterogeneity of repolarization in the human heart. Journal of the American College of Cardiology, 32(4), 1063-1067. doi:10.1016/s0735-1097(98)00330-1Fukuta, H., & Little, W. C. (2007). Contribution of Systolic and Diastolic Abnormalities to Heart Failure With a Normal and a Reduced Ejection Fraction. Progress in Cardiovascular Diseases, 49(4), 229-240. doi:10.1016/j.pcad.2006.08.009Gaudesius, G., Miragoli, M., Thomas, S. P., & Rohr, S. (2003). Coupling of Cardiac Electrical Activity Over Extended Distances by Fibroblasts of Cardiac Origin. Circulation Research, 93(5), 421-428. doi:10.1161/01.res.0000089258.40661.0cGomez, J. F., Cardona, K., Martinez, L., Saiz, J., & Trenor, B. (2014). Electrophysiological and Structural Remodeling in Heart Failure Modulate Arrhythmogenesis. 2D Simulation Study. PLoS ONE, 9(7), e103273. doi:10.1371/journal.pone.0103273Gomez, J. F., Cardona, K., Romero, L., Ferrero, J. M., & Trenor, B. (2014). Electrophysiological and Structural Remodeling in Heart Failure Modulate Arrhythmogenesis. 1D Simulation Study. PLoS ONE, 9(9), e106602. doi:10.1371/journal.pone.0106602Greisas, A., & Zlochiver, S. (2016). The Multi-Domain Fibroblast/Myocyte Coupling in the Cardiac Tissue: A Theoretical Study. Cardiovascular Engineering and Technology, 7(3), 290-304. doi:10.1007/s13239-016-0266-xJacquemet, V., & Henriquez, C. S. (2008). Loading effect of fibroblast-myocyte coupling on resting potential, impulse propagation, and repolarization: insights from a microstructure model. American Journal of Physiology-Heart and Circulatory Physiology, 294(5), H2040-H2052. doi:10.1152/ajpheart.01298.2007Li, Y., Asfour, H., & Bursac, N. (2017). Age-dependent functional crosstalk between cardiac fibroblasts and cardiomyocytes in a 3D engineered cardiac tissue. Acta Biomaterialia, 55, 120-130. doi:10.1016/j.actbio.2017.04.027Lou, Q., Janks, D. L., Holzem, K. M., Lang, D., Onal, B., Ambrosi, C. M., … Efimov, I. R. (2012). Right ventricular arrhythmogenesis in failing human heart: the role of conduction and repolarization remodeling. American Journal of Physiology-Heart and Circulatory Physiology, 303(12), H1426-H1434. doi:10.1152/ajpheart.00457.2012Lyon, A. R., MacLeod, K. T., Zhang, Y., Garcia, E., Kanda, G. K., Lab, M. J., … Gorelik, J. (2009). Loss of T-tubules and other changes to surface topography in ventricular myocytes from failing human and rat heart. Proceedings of the National Academy of Sciences, 106(16), 6854-6859. doi:10.1073/pnas.0809777106Andrew MacCannell, K., Bazzazi, H., Chilton, L., Shibukawa, Y., Clark, R. B., & Giles, W. R. (2007). A Mathematical Model of Electrotonic Interactions between Ventricular Myocytes and Fibroblasts. Biophysical Journal, 92(11), 4121-4132. doi:10.1529/biophysj.106.101410Majumder, R., Nayak, A. R., & Pandit, R. (2012). Nonequilibrium Arrhythmic States and Transitions in a Mathematical Model for Diffuse Fibrosis in Human Cardiac Tissue. PLoS ONE, 7(10), e45040. doi:10.1371/journal.pone.0045040Mayourian, J., Savizky, R. M., Sobie, E. A., & Costa, K. D. (2016). Modeling Electrophysiological Coupling and Fusion between Human Mesenchymal Stem Cells and Cardiomyocytes. PLOS Computational Biology, 12(7), e1005014. doi:10.1371/journal.pcbi.1005014Miragoli, M., Gaudesius, G., & Rohr, S. (2006). Electrotonic Modulation of Cardiac Impulse Conduction by Myofibroblasts. Circulation Research, 98(6), 801-810. doi:10.1161/01.res.0000214537.44195.a3Mora, M. T., Ferrero, J. M., Romero, L., & Trenor, B. (2017). Sensitivity analysis revealing the effect of modulating ionic mechanisms on calcium dynamics in simulated human heart failure. PLOS ONE, 12(11), e0187739. doi:10.1371/journal.pone.0187739Morotti, S., Nieves-Cintrón, M., Nystoriak, M. A., Navedo, M. F., & Grandi, E. (2017). Predominant contribution of L-type Cav1.2 channel stimulation to impaired intracellular calcium and cerebral artery vasoconstriction in diabetic hyperglycemia. Channels, 11(4), 340-346. doi:10.1080/19336950.2017.1293220Muszkiewicz, A., Britton, O. J., Gemmell, P., Passini, E., Sánchez, C., Zhou, X., … Rodriguez, B. (2016). Variability in cardiac electrophysiology: Using experimentally-calibrated populations of models to move beyond the single virtual physiological human paradigm. Progress in Biophysics and Molecular Biology, 120(1-3), 115-127. doi:10.1016/j.pbiomolbio.2015.12.002Nguyen, T. P., Xie, Y., Garfinkel, A., Qu, Z., & Weiss, J. N. (2011). Arrhythmogenic consequences of myofibroblast–myocyte coupling. Cardiovascular Research, 93(2), 242-251. doi:10.1093/cvr/cvr292Nivala, M., Song, Z., Weiss, J. N., & Qu, Z. (2015). T-tubule disruption promotes calcium alternans in failing ventricular myocytes: Mechanistic insights from computational modeling. Journal of Molecular and Cellular Cardiology, 79, 32-41. doi:10.1016/j.yjmcc.2014.10.018O’Hara, T., Virág, L., Varró, A., & Rudy, Y. (2011). Simulation of the Undiseased Human Cardiac Ventricular Action Potential: Model Formulation and Experimental Validation. PLoS Computational Biology, 7(5), e1002061. doi:10.1371/journal.pcbi.1002061Ozdemir, S., Bito, V., Holemans, P., Vinet, L., Mercadier, J.-J., Varro, A., & Sipido, K. R. (2008). Pharmacological Inhibition of Na/Ca Exchange Results in Increased Cellular Ca2+Load Attributable to the Predominance of Forward Mode Block. Circulation Research, 102(11), 1398-1405. doi:10.1161/circresaha.108.173922Péréon, Y., Demolombe, S., Baró, I., Drouin, E., Charpentier, F., & Escande, D. (2000). Differential expression of KvLQT1 isoforms across the human ventricular wall. American Journal of Physiology-Heart and Circulatory Physiology, 278(6), H1908-H1915. doi:10.1152/ajpheart.2000.278.6.h1908Piacentino, V., Weber, C. R., Chen, X., Weisser-Thomas, J., Margulies, K. B., Bers, D. M., & Houser, S. R. (2003). Cellular Basis of Abnormal Calcium Transients of Failing Human Ventricular Myocytes. Circulation Research, 92(6), 651-658. doi:10.1161/01.res.0000062469.83985.9bRocchetti, M., Alemanni, M., Mostacciuolo, G., Barassi, P., Altomare, C., Chisci, R., … Zaza, A. (2008). Modulation of Sarcoplasmic Reticulum Function by PST2744 [Istaroxime; (E,Z)-3-((2-Aminoethoxy)imino) Androstane-6,17-dione Hydrochloride)] in a Pressure-Overload Heart Failure Model. Journal of Pharmacology and Experimental Therapeutics, 326(3), 957-965. doi:10.1124/jpet.108.138701Romero, L., Carbonell, B., Trenor, B., Rodríguez, B., Saiz, J., & Ferrero, J. M. (2011). Systematic characterization of the ionic basis of rabbit cellular electrophysiology using two ventricular models. Progress in Biophysics and Molecular Biology, 107(1), 60-73. doi:10.1016/j.pbiomolbio.2011.06.012Romero, L., Pueyo, E., Fink, M., & Rodríguez, B. (2009). Impact of ionic current variability on human ventricular cellular electrophysiology. American Journal of Physiology-Heart and Circulatory Physiology, 297(4), H1436-H1445. doi:10.1152/ajpheart.00263.2009Rook, M. B., van Ginneken, A. C., de Jonge, B., el Aoumari, A., Gros, D., & Jongsma, H. J. (1992). Differences in gap junction channels between cardiac myocytes, fibroblasts, and heterologous pairs. American Journal of Physiology-Cell Physiology, 263(5), C959-C977. doi:10.1152/ajpcell.1992.263.5.c959Sachse, F. B., Moreno, A. P., Seemann, G., & Abildskov, J. A. (2009). A Model of Electrical Conduction in Cardiac Tissue Including Fibroblasts. Annals of Biomedical Engineering, 37(5), 874-889. doi:10.1007/s10439-009-9667-4Sanchez-Alonso, J. L., Bhargava, A., O’Hara, T., Glukhov, A. V., Schobesberger, S., Bhogal, N., … Gorelik, J. (2016). Microdomain-Specific Modulation of L-Type Calcium Channels Leads to Triggered Ventricular Arrhythmia in Heart Failure. Circulation Research, 119(8), 944-955. doi:10.1161/circresaha.116.308698Savarese, G., & Lund, L. H. (2017). Global Public Health Burden of Heart Failure. Cardiac Failure Review, 03(01), 7. doi:10.15420/cfr.2016:25:2Seidel, T., Salameh, A., & Dhein, S. (2010). A Simulation Study of Cellular Hypertrophy and Connexin Lateralization in Cardiac Tissue. Biophysical Journal, 99(9), 2821-2830. doi:10.1016/j.bpj.2010.09.010Shannon, T. R., Ginsburg, K. S., & Bers, D. M. (2000). Potentiation of Fractional Sarcoplasmic Reticulum Calcium Release by Total and Free Intra-Sarcoplasmic Reticulum Calcium Concentration. Biophysical Journal, 78(1), 334-343. doi:10.1016/s0006-3495(00)76596-9Sobie, E. A. (2009). Parameter Sensitivity Analysis in Electrophysiological Models Using Multivariable Regression. Biophysical Journal, 96(4), 1264-1274. doi:10.1016/j.bpj.2008.10.056Sridhar, S., Vandersickel, N., & Panfilov, A. V. (2017). Effect of myocyte-fibroblast coupling on the onset of pathological dynamics in a model of ventricular tissue. Scientific Reports, 7(1). doi:10.1038/srep40985Tamayo, M., Manzanares, E., Bas, M., Martín-Nunes, L., Val-Blasco, A., Jesús Larriba, M., … Delgado, C. (2017). Calcitriol (1,25-dihydroxyvitamin D3) increases L-type calcium current via protein kinase A signaling and modulates calcium cycling and contractility in isolated mouse ventricular myocytes. Heart Rhythm, 14(3), 432-439. doi:10.1016/j.hrthm.2016.12.013Trayanova, N. A., & Chang, K. C. (2016). How computer simulations of the human heart can improve anti-arrhythmia therapy. The Journal of Physiology, 594(9), 2483-2502. doi:10.1113/jp270532Trenor, B., Cardona, K., Gomez, J. F., Rajamani, S., Ferrero, J. M., Belardinelli, L., & Saiz, J. (2012). Simulation and Mechanistic Investigation of the Arrhythmogenic Role of the Late Sodium Current in Human Heart Failure. PLoS ONE, 7(3), e32659. doi:10.1371/journal.pone.0032659Walmsley, J., Rodriguez, J. F., Mirams, G. R., Burrage, K., Efimov, I. R., & Rodriguez, B. (2013). mRNA Expression Levels in Failing Human Hearts Predict Cellular Electrophysiological Remodeling: A Population-Based Simulation Study. PLoS ONE, 8(2), e56359. doi:10.1371/journal.pone.0056359Xie, Y., Garfinkel, A., Camelliti, P., Kohl, P., Weiss, J. N., & Qu, Z. (2009). Effects of fibroblast-myocyte coupling on cardiac conduction and vulnerability to reentry: A computational study. Heart Rhythm, 6(11), 1641-1649. doi:10.1016/j.hrthm.2009.08.003Xie, Y., Garfinkel, A., Weiss, J. N., & Qu, Z. (2009). Cardiac alternans induced by fibroblast-myocyte coupling: mechanistic insights from computational models. American Journal of Physiology-Heart and Circulatory Physiology, 297(2), H775-H784. doi:10.1152/ajpheart.00341.2009Zhan, H., Xia, L., Shou, G., Zang, Y., Liu, F., & Crozier, S. (2014). Fibroblast proliferation alters cardiac excitation conduction and contraction: a computational study. Journal of Zhejiang University SCIENCE B, 15(3), 225-242. doi:10.1631/jzus.b1300156Zhou, X., Bueno-Orovio, A., Orini, M., Hanson, B., Hayward, M., Taggart, P., … Rodriguez, B. (2016). In Vivo and In Silico Investigation Into Mechanisms of Frequency Dependence of Repolarization Alternans in Human Ventricular Cardiomyocytes. Circulation Research, 118(2), 266-278. doi:10.1161/circresaha.115.307836Zimik, S., & Pandit, R. (2016). Instability of spiral and scroll waves in the presence of a gradient in the fibroblast density: the effects of fibroblast–myocyte coupling. New Journal of Physics, 18(12), 123014. doi:10.1088/1367-2630/18/12/123014Zlochiver, S., Muñoz, V., Vikstrom, K. L., Taffet, S. M., Berenfeld, O., & Jalife, J. (2008). Electrotonic Myofibroblast-to-Myocyte Coupling Increases Propensity to Reentrant Arrhythmias in Two-Dimensional Cardiac Monolayers. Biophysical Journal, 95(9), 4469-4480. doi:10.1529/biophysj.108.136473Zou, J., Salarian, M., Chen, Y., Zhuo, Y., Brown, N. E., Hepler, J. R., & Yang, J. J. (2017). Direct visualization of interaction between calmodulin and connexin45. Biochemical Journal, 474(24), 4035-4051. doi:10.1042/bcj2017042

An Improved Reporter Identifies Ruxolitinib as a Potent and Cardioprotective CaMKII Inhibitor

Ca2+/calmodulin-dependent protein kinase II (CaMKII) hyperactivity causes cardiac arrhythmias, a major source of morbidity and mortality worldwide. Despite proven benefits of CaMKII inhibition in numerous preclinical models of heart disease, translation of CaMKII antagonists into humans has been stymied by low potency, toxicity, and an enduring concern for adverse effects on cognition due to an established role of CaMKII in learning and memory. To address these challenges, we asked whether any clinically approved drugs, developed for other purposes, were potent CaMKII inhibitors. For this, we engineered an improved fluorescent reporter, CaMKAR (CaMKII activity reporter), which features superior sensitivity, kinetics, and tractability for high-throughput screening. Using this tool, we carried out a drug repurposing screen (4475 compounds in clinical use) in human cells expressing constitutively active CaMKII. This yielded five previously unrecognized CaMKII inhibitors with clinically relevant potency: ruxolitinib, baricitinib, silmitasertib, crenolanib, and abemaciclib. We found that ruxolitinib, an orally bioavailable and U.S. Food and Drug Administration–approved medication, inhibited CaMKII in cultured cardiomyocytes and in mice. Ruxolitinib abolished arrhythmogenesis in mouse and patient-derived models of CaMKII-driven arrhythmias. A 10-min pretreatment in vivo was sufficient to prevent catecholaminergic polymorphic ventricular tachycardia, a congenital source of pediatric cardiac arrest, and rescue atrial fibrillation, the most common clinical arrhythmia. At cardioprotective doses, ruxolitinib-treated mice did not show any adverse effects in established cognitive assays. Our results support further clinical investigation of ruxolitinib as a potential treatment for cardiac indications

The Development of an Atlas of the Kinematic Structures of Mechanisms

Based on the restrictions governing the admissible graphs of the kinematic chains of mechanisms, an atlas or listing of 35 graphs has been developed which defines the kinematic structure of a wide class of plane and three-dimensional mechanisms with up to six links. Such an atlas can serve as the basis for the creation of mechanisms in the conceptual stage of mechanical design and permits the partial automation of this process. The same procedure would also be applicable to the development of a similar atlas for mechanisms with more than six links and a greater variety of joints.</jats:p

Energy Efficient Cam-Follower Systems

The energy loss in cam-follower systems due to friction between moving parts can be a significant contributor to the power loss in machinery. Considering the total number of cam-operated machines in manufacturing and other operations, the energy savings obtainable by improving the efficiency of the average cam-follower system by even a small percentage would be significant. In this investigation a new rating factor—an energy-loss coefficient proportional to the energy loss at the cam-follower interface—has been defined and evaluated. The rating factor relates to energy efficiency in a manner analogous to the way in which the well-known rating factors for velocity, acceleration, and shock relate to the kinematic characteristics of the cam-follower system. Two cam-follower configurations have been considered: 1) a follower motion governed by both cam and return spring, and 2) a follower positively driven by the cam. In both cases it was found that cam curves with identical rise and rise times can differ substantially in energy efficiency thereby demonstrating the significance of an energy-optimization strategy in the design of cam-follower systems. The nature of the functional dependence of the energy loss on system parameters has been identified and a minimum energy-loss limit established.</jats:p