Functional Differences in Engineered Myocardium from Embryonic Stem Cell-Derived versus Neonatal Cardiomyocytes

Stem cell-derived cardiomyocytes represent unique tools for cell- and tissue-based regenerative therapies, drug discovery and safety, and studies of fundamental heart-failure mechanisms. However, the degree to which stem cell-derived cardiomyocytes compare to mature cardiomyocytes is often debated. We reasoned that physiological metrics of engineered cardiac tissues offer a means of comparison. We built laminar myocardium engineered from cardiomyocytes that were differentiated from mouse embryonic stem cell-derived cardiac progenitors or harvested directly from neonatal mouse ventricles, and compared their anatomy and physiology in vitro. Tissues assembled from progenitor-derived myocytes and neonate myocytes demonstrated similar cytoskeletal architectures but different gap junction organization and electromechanical properties. Progenitor-derived myocardium had significantly less contractile stress and slower longitudinal conduction velocity than neonate-derived myocardium, indicating that the developmental state of the cardiomyocytes affects the electromechanical function of the resultant engineered tissue. These data suggest a need to establish performance metrics for future stem cell applications

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.Comment: 58 pages (19 main and 39 supplement pages), 4 main figures, 9 supplement figure

Gain-of-function mutation in ubiquitin ligase KLHL24 causes desmin degradation and dilatation in hiPSC-derived engineered heart tissues

The start codon c.1A>G mutation in KLHL24, encoding ubiquitin ligase KLHL24, results in the loss of 28 N-terminal amino acids (KLHL24-ΔN28) by skipping the initial start codon. In skin, KLHL24-ΔN28 leads to gain of function, excessively targeting intermediate filament keratin-14 for proteasomal degradation and ultimately causing epidermolysis bullosa simplex (EBS). The majority of patients with EBS are also diagnosed with dilated cardiomyopathy (DCM), but the pathological mechanism in the heart is unknown. As desmin is the cardiac homolog of keratin-14, we hypothesized that KLHL24-ΔN28 leads to excessive degradation of desmin, resulting in DCM. Dynamically loaded engineered heart tissues (dyn-EHTs) were generated from human-induced pluripotent stem cell–derived (hiPSC-derived) cardiomyocytes from 2 patients and 3 nonfamilial controls. Ten-fold lower desmin protein levels were observed in patient-derived dyn-EHTs, in line with diminished desmin levels detected in patients’ explanted heart. This was accompanied by tissue dilatation, impaired mitochondrial function, decreased force values, and increased cardiomyocyte stress. HEK293 transfection studies confirmed KLHL24-mediated desmin degradation. KLHL24 RNA interference or direct desmin overexpression recovered desmin protein levels, restoring morphology and function in patient-derived dyn-EHTs. To conclude, presence of KLHL24-ΔN28 in cardiomyocytes leads to excessive degradation of desmin, affecting tissue morphology and function, which can be prevented by restoring desmin protein levels

A tissue-engineered jellyfish with biomimetic propulsion

Reverse engineering of biological form and function requires hierarchical design over several orders of space and time. Recent advances in the mechanistic understanding of biosynthetic compound materials, computer-aided design approaches in molecular synthetic biology and traditional soft robotics, and increasing aptitude in generating structural and chemical microenvironments that promote cellular self-organization have enhanced the ability to recapitulate such hierarchical architecture in engineered biological systems. Here we combined these capabilities in a systematic design strategy to reverse engineer a muscular pump. We report the construction of a freely swimming jellyfish from chemically dissociated rat tissue and silicone polymer as a proof of concept. The constructs, termed 'medusoids', were designed with computer simulations and experiments to match key determinants of jellyfish propulsion and feeding performance by quantitatively mimicking structural design, stroke kinematics and animal-fluid interactions. The combination of the engineering design algorithm with quantitative benchmarks of physiological performance suggests that our strategy is broadly applicable to reverse engineering of muscular organs or simple life forms that pump to survive

Dynamic loading of human engineered heart tissue enhances contractile function and drives a desmosome-linked disease phenotype

The role that mechanical forces play in shaping the structure and function of the heart is critical to understanding heart formation and the etiology of disease but is challenging to study in patients. Engineered heart tissues (EHTs) incorporating human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes have the potential to provide insight into these adaptive and maladaptive changes. However, most EHT systems cannot model both preload (stretch during chamber filling) and afterload (pressure the heart must work against to eject blood). Here, we have developed a new dynamic EHT (dyn-EHT) model that enables us to tune preload and have unconstrained contractile shortening of >10%. To do this, three-dimensional (3D) EHTs were integrated with an elastic polydimethylsiloxane strip providing mechanical preload and afterload in addition to enabling contractile force measurements based on strip bending. Our results demonstrated that dynamic loading improves the function of wild-type EHTs on the basis of the magnitude of the applied force, leading to improved alignment, conduction velocity, and contractility. For disease modeling, we used hiPSC-derived cardiomyocytes from a patient with arrhythmogenic cardiomyopathy due to mutations in the desmoplakin gene. We demonstrated that manifestation of this desmosome-linked disease state required dyn-EHT conditioning and that it could not be induced using 2D or standard 3D EHT approaches. Thus, a dynamic loading strategy is necessary to provoke the disease phenotype of diastolic lengthening, reduction of desmosome counts, and reduced contractility, which are related to primary end points of clinical disease, such as chamber thinning and reduced cardiac output

Threshold analyses and Lorentz violation

In the context of threshold investigations of Lorentz violation, we discuss the fundamental principle of coordinate invariance, the role of an effective dynamical framework, and the conditions of positivity and causality. Our analysis excludes a variety of previously considered Lorentz-breaking parameters and opens an avenue for viable dispersion-relation investigations of Lorentz violation.Comment: 9 page

Heavy quarkonium: progress, puzzles, and opportunities

A golden age for heavy quarkonium physics dawned a decade ago, initiated by the confluence of exciting advances in quantum chromodynamics (QCD) and an explosion of related experimental activity. The early years of this period were chronicled in the Quarkonium Working Group (QWG) CERN Yellow Report (YR) in 2004, which presented a comprehensive review of the status of the field at that time and provided specific recommendations for further progress. However, the broad spectrum of subsequent breakthroughs, surprises, and continuing puzzles could only be partially anticipated. Since the release of the YR, the BESII program concluded only to give birth to BESIII; the $B$-factories and CLEO-c flourished; quarkonium production and polarization measurements at HERA and the Tevatron matured; and heavy-ion collisions at RHIC have opened a window on the deconfinement regime. All these experiments leave legacies of quality, precision, and unsolved mysteries for quarkonium physics, and therefore beg for continuing investigations. The plethora of newly-found quarkonium-like states unleashed a flood of theoretical investigations into new forms of matter such as quark-gluon hybrids, mesonic molecules, and tetraquarks. Measurements of the spectroscopy, decays, production, and in-medium behavior of c\bar{c}, b\bar{b}, and b\bar{c} bound states have been shown to validate some theoretical approaches to QCD and highlight lack of quantitative success for others. The intriguing details of quarkonium suppression in heavy-ion collisions that have emerged from RHIC have elevated the importance of separating hot- and cold-nuclear-matter effects in quark-gluon plasma studies. This review systematically addresses all these matters and concludes by prioritizing directions for ongoing and future efforts.Comment: 182 pages, 112 figures. Editors: N. Brambilla, S. Eidelman, B. K. Heltsley, R. Vogt. Section Coordinators: G. T. Bodwin, E. Eichten, A. D. Frawley, A. B. Meyer, R. E. Mitchell, V. Papadimitriou, P. Petreczky, A. A. Petrov, P. Robbe, A. Vair

Tumor Transcriptome Sequencing Reveals Allelic Expression Imbalances Associated with Copy Number Alterations

Due to growing throughput and shrinking cost, massively parallel sequencing is rapidly becoming an attractive alternative to microarrays for the genome-wide study of gene expression and copy number alterations in primary tumors. The sequencing of transcripts (RNA-Seq) should offer several advantages over microarray-based methods, including the ability to detect somatic mutations and accurately measure allele-specific expression. To investigate these advantages we have applied a novel, strand-specific RNA-Seq method to tumors and matched normal tissue from three patients with oral squamous cell carcinomas. Additionally, to better understand the genomic determinants of the gene expression changes observed, we have sequenced the tumor and normal genomes of one of these patients. We demonstrate here that our RNA-Seq method accurately measures allelic imbalance and that measurement on the genome-wide scale yields novel insights into cancer etiology. As expected, the set of genes differentially expressed in the tumors is enriched for cell adhesion and differentiation functions, but, unexpectedly, the set of allelically imbalanced genes is also enriched for these same cancer-related functions. By comparing the transcriptomic perturbations observed in one patient to his underlying normal and tumor genomes, we find that allelic imbalance in the tumor is associated with copy number mutations and that copy number mutations are, in turn, strongly associated with changes in transcript abundance. These results support a model in which allele-specific deletions and duplications drive allele-specific changes in gene expression in the developing tumor

Many Labs 5:Testing pre-data collection peer review as an intervention to increase replicability

Replication studies in psychological science sometimes fail to reproduce prior findings. If these studies use methods that are unfaithful to the original study or ineffective in eliciting the phenomenon of interest, then a failure to replicate may be a failure of the protocol rather than a challenge to the original finding. Formal pre-data-collection peer review by experts may address shortcomings and increase replicability rates. We selected 10 replication studies from the Reproducibility Project: Psychology (RP:P; Open Science Collaboration, 2015) for which the original authors had expressed concerns about the replication designs before data collection; only one of these studies had yielded a statistically significant effect (p < .05). Commenters suggested that lack of adherence to expert review and low-powered tests were the reasons that most of these RP:P studies failed to replicate the original effects. We revised the replication protocols and received formal peer review prior to conducting new replication studies. We administered the RP:P and revised protocols in multiple laboratories (median number of laboratories per original study = 6.5, range = 3?9; median total sample = 1,279.5, range = 276?3,512) for high-powered tests of each original finding with both protocols. Overall, following the preregistered analysis plan, we found that the revised protocols produced effect sizes similar to those of the RP:P protocols (?r = .002 or .014, depending on analytic approach). The median effect size for the revised protocols (r = .05) was similar to that of the RP:P protocols (r = .04) and the original RP:P replications (r = .11), and smaller than that of the original studies (r = .37). Analysis of the cumulative evidence across the original studies and the corresponding three replication attempts provided very precise estimates of the 10 tested effects and indicated that their effect sizes (median r = .07, range = .00?.15) were 78% smaller, on average, than the original effect sizes (median r = .37, range = .19?.50)

Dijet production in √s = 7 TeV pp collisions with large rapidity gaps at the ATLAS experiment

A 6.8 nb−¹ sample of pp collision data collected under low-luminosity conditions at √s = 7 TeV by the ATLAS detector at the Large Hadron Collider is used to study diffractive dijet production. Events containing at least two jets with pT > 20 GeV are selected and analysed in terms of variables which discriminate between diffractive and non-diffractive processes. Cross sections are measured differentially in ΔηF, the size of the observable forward region of pseudorapidity which is devoid of hadronic activity, and in an estimator, ξ˜, of the fractional momentum loss of the proton assuming single diffractive dissociation (pp → p X). Model comparisons indicate a dominant non-diffractive contribution up to moderately large ηF and small ξ˜, with a diffractive contribution which is significant at the highest ΔηF and the lowest ξ˜. The rapidity-gap survival probability is estimated from comparisons of the data in this latter region with predictions based on diffractive parton distribution functions