A Family of microRNAs Encoded by Myosin Genes Governs Myosin Expression and Muscle Performance

SummaryMyosin is the primary regulator of muscle strength and contractility. Here we show that three myosin genes, Myh6, Myh7, and Myh7b, encode related intronic microRNAs (miRNAs), which, in turn, control muscle myosin content, myofiber identity, and muscle performance. Within the adult heart, the Myh6 gene, encoding a fast myosin, coexpresses miR-208a, which regulates the expression of two slow myosins and their intronic miRNAs, Myh7/miR-208b and Myh7b/miR-499, respectively. miR-208b and miR-499 play redundant roles in the specification of muscle fiber identity by activating slow and repressing fast myofiber gene programs. The actions of these miRNAs are mediated in part by a collection of transcriptional repressors of slow myofiber genes. These findings reveal that myosin genes not only encode the major contractile proteins of muscle, but act more broadly to influence muscle function by encoding a network of intronic miRNAs that control muscle gene expression and performance

A monocyte-TNF-endothelial activation axis in sickle transgenic mice: Therapeutic benefit from TNF blockade

Elaboration of tumor necrosis factor (TNF) is a very early event in development of ischemia/reperfusion injury pathophysiology. Therefore, TNF may be a prominent mediator of endothelial cell and vascular wall dysfunction in sickle cell anemia, a hypothesis we addressed using NY1DD, S+SAntilles, and SS‐BERK sickle transgenic mice. Transfusion experiments revealed participation of abnormally activated blood monocytes exerting an endothelial activating effect, dependent upon Egr‐1 in both vessel wall and blood cells, and upon NFκB(p50) in a blood cell only. Involvement of TNF was identified by beneficial impact from TNF blockers, etanercept and infliximab, with less benefit from an IL‐1 blocker, anakinra. In therapeutic studies, etanercept ameliorated multiple disturbances of the murine sickle condition: monocyte activation, blood biomarkers of inflammation, low platelet count and Hb, vascular stasis triggered by hypoxia/reoxygenation (but not if triggered by hemin infusion), tissue production of neuro‐inflammatory mediators, endothelial activation (monitored by tissue factor and VCAM‐1 expression), histopathologic liver injury, and three surrogate markers of pulmonary hypertension (perivascular inflammatory aggregates, arteriolar muscularization, and right ventricular mean systolic pressure). In aggregate, these studies identify a prominent—and possibly dominant—role for an abnormal monocyte‐TNF‐endothelial activation axis in the sickle context. Its presence, plus the many benefits of etanercept observed here, argue that pilot testing of TNF blockade should be considered for human sickle cell anemia, a challenging but achievable translational research goal

Cardiac Tissue Engineering: Implications for Pediatric Heart Surgery

Children with severe congenital malformations, such as single-ventricle anomalies, have a daunting prognosis. Heart transplantation would be a therapeutic option but is restricted due to a lack of suitable donor organs and, even in case of successful heart transplantation, lifelong immune suppression would frequently be associated with a number of serious side effects. As an alternative to heart transplantation and classical cardiac reconstructive surgery, tissue-engineered myocardium might become available to augment hypomorphic hearts and/or provide new muscle material for complex myocardial reconstruction. These potential applications of tissue engineered myocardium will, however, impose major challenges to cardiac tissue engineers as well as heart surgeons. This review will provide an overview of available cardiac tissue-engineering technologies, discuss limitations, and speculate on a potential application of tissue-engineered heart muscle in pediatric heart surgery

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Integrative and comparative genomic analyses identify clinically relevant pulmonary carcinoid groups and unveil the supra-carcinoids

International audienceThe worldwide incidence of pulmonary carcinoids is increasing, but little is known about their molecular characteristics. Through machine learning and multi-omics factor analysis, we compare and contrast the genomic profiles of 116 pulmonary carcinoids (including 35 atypical), 75 large-cell neuroendocrine carcinomas (LCNEC), and 66 small-cell lung cancers. Here we report that the integrative analyses on 257 lung neuroendocrine neoplasms stratify atypical carcinoids into two prognostic groups with a 10-year overall survival of 88% and 27%, respectively. We identify therapeutically relevant molecular groups of pulmonary car-cinoids, suggesting DLL3 and the immune system as candidate therapeutic targets; we confirm the value of OTP expression levels for the prognosis and diagnosis of these diseases, and we unveil the group of supra-carcinoids. This group comprises samples with carcinoid-like morphology yet the molecular and clinical features of the deadly LCNEC, further supporting the previously proposed molecular link between the low-and high-grade lung neuroendocrine neoplasms

Appendix C. Supplementary tables of the results from the generalized linear mixed models and Piper species sampled.

Supplementary tables of the results from the generalized linear mixed models and Piper species sampled