High Performance Computing for DNA Sequence Alignment and Assembly

Recent advances in DNA sequencing technology have dramatically increased the scale and scope of DNA sequencing. These data are used for a wide variety of important biological analyzes, including genome sequencing, comparative genomics, transcriptome analysis, and personalized medicine but are complicated by the volume and complexity of the data involved. Given the massive size of these datasets, computational biology must draw on the advances of high performance computing. Two fundamental computations in computational biology are read alignment and genome assembly. Read alignment maps short DNA sequences to a reference genome to discover conserved and polymorphic regions of the genome. Genome assembly computes the sequence of a genome from many short DNA sequences. Both computations benefit from recent advances in high performance computing to efficiently process the huge datasets involved, including using highly parallel graphics processing units (GPUs) as high performance desktop processors, and using the MapReduce framework coupled with cloud computing to parallelize computation to large compute grids. This dissertation demonstrates how these technologies can be used to accelerate these computations by orders of magnitude, and have the potential to make otherwise infeasible computations practical

Observing a Dynamical Skeleton of Turbulence in Taylor-Couette Flow Experiments

Recent work suggests unstable recurrent solutions of the equations governing fluid flow can play an important role in structuring the dynamics of turbulence. Here we present a method for detecting intervals of time where turbulence "shadows" (spatially and temporally mimics) recurrent solutions. We find that shadowing occurs frequently and repeatedly in both numerical and experimental observations of counter-rotating Taylor-Couette flow, despite the relatively small number of known recurrent solutions in this system. Our results set the stage for experimentally-grounded dynamical descriptions of turbulence in a variety of wall-bounded shear flows, enabling applications to forecasting and control

Hubble Space Telescope Near-Ultraviolet Spectroscopy of Bright CEMP-s Stars

We present an elemental-abundance analysis, in the near-ultraviolet (NUV) spectral range, for the bright carbon-enhanced metal-poor (CEMP) stars HD196944 (V = 8.40, [Fe/H] = -2.41) and HD201626 (V = 8.16, [Fe/H] = -1.51), based on data acquired with the Space Telescope Imaging Spectrograph (STIS) on the Hubble Space Telescope. Both of these stars belong to the sub-class CEMP-s, and exhibit clear over-abundances of heavy elements associated with production by the slow neutron-capture process. HD196944 has been well-studied in the optical region, but we are able to add abundance results for six species (Ge, Nb, Mo, Lu, Pt, and Au) that are only accessible in the NUV. In addition, we provide the first determination of its orbital period, P=1325 days. HD201626 has only a limited number of abundance results based on previous optical work -- here we add five new species from the NUV, including Pb. We compare these results with models of binary-system evolution and s-process element production in stars on the asymptotic giant branch, aiming to explain their origin and evolution. Our best-fitting models for HD 196944 (M1,i = 0.9Mo, M2,i = 0.86Mo, for [Fe/H]=-2.2), and HD 201626 (M1,i = 0.9Mo , M2,i = 0.76Mo , for [Fe/H]=-2.2; M1,i = 1.6Mo , M2,i = 0.59Mo, for [Fe/H]=-1.5) are consistent with the current accepted scenario for the formation of CEMP-s stars.Comment: 25 pages, 13 figures; accepted for publication in Ap

Molecular Threading: Mechanical Extraction, Stretching and Placement of DNA Molecules from a Liquid-Air Interface

We present “molecular threading”, a surface independent tip-based method for stretching and depositing single and double-stranded DNA molecules. DNA is stretched into air at a liquid-air interface, and can be subsequently deposited onto a dry substrate isolated from solution. The design of an apparatus used for molecular threading is presented, and fluorescence and electron microscopies are used to characterize the angular distribution, straightness, and reproducibility of stretched DNA deposited in arrays onto elastomeric surfaces and thin membranes. Molecular threading demonstrates high straightness and uniformity over length scales from nanometers to micrometers, and represents an alternative to existing DNA deposition and linearization methods. These results point towards scalable and high-throughput precision manipulation of single-molecule polymers

Comparative genomics of mutualistic viruses of Glyptapanteles parasitic wasps

Comparative genome analysis of two endosymbiotic polydnaviruses from Glyptapanteles parasitic wasps reveals new insights into the evolutionary arms race between host and parasite

Interleukin‐1 Blockade Inhibits the Acute Inflammatory Response in Patients With ST‐Segment–Elevation Myocardial Infarction

Background ST‐segment–elevation myocardial infarction is associated with an intense acute inflammatory response and risk of heart failure. We tested whether interleukin‐1 blockade with anakinra significantly reduced the area under the curve for hsCRP (high sensitivity C‐reactive protein) levels during the first 14 days in patients with ST‐segment–elevation myocardial infarction (VCUART3 [Virginia Commonwealth University Anakinra Remodeling Trial 3]). Methods and Results We conducted a randomized, placebo‐controlled, double‐blind, clinical trial in 99 patients with ST‐segment–elevation myocardial infarction in which patients were assigned to 2 weeks treatment with anakinra once daily (N=33), anakinra twice daily (N=31), or placebo (N=35). hsCRP area under the curve was significantly lower in patients receiving anakinra versus placebo (median, 67 [interquartile range, 39–120] versus 214 [interquartile range, 131–394] mg·day/L; P\u3c0.001), without significant differences between the anakinra arms. No significant differences were found between anakinra and placebo groups in the interval changes in left ventricular end‐systolic volume (median, 1.4 [interquartile range, −9.8 to 9.8] versus −3.9 [interquartile range, −15.4 to 1.4] mL; P=0.21) or left ventricular ejection fraction (median, 3.9% [interquartile range, −1.6% to 10.2%] versus 2.7% [interquartile range, −1.8% to 9.3%]; P=0.61) at 12 months. The incidence of death or new‐onset heart failure or of death and hospitalization for heart failure was significantly lower with anakinra versus placebo (9.4% versus 25.7% [P=0.046] and 0% versus 11.4% [P=0.011], respectively), without difference between the anakinra arms. The incidence of serious infection was not different between anakinra and placebo groups (14% versus 14%; P=0.98). Injection site reactions occurred more frequently in patients receiving anakinra (22%) versus placebo (3%; P=0.016). Conclusions In patients presenting with ST‐segment–elevation myocardial infarction, interleukin‐1 blockade with anakinra significantly reduces the systemic inflammatory response compared with placebo. Clinical Trial Registration URL: https://www.clinicaltrials.gov/. Unique identifier: NCT01950299

Artificial Intelligence and Cardiovascular Genetics

Polygenic diseases, which are genetic disorders caused by the combined action of multiple genes, pose unique and significant challenges for the diagnosis and management of affected patients. A major goal of cardiovascular medicine has been to understand how genetic variation leads to the clinical heterogeneity seen in polygenic cardiovascular diseases (CVDs). Recent advances and emerging technologies in artificial intelligence (AI), coupled with the ever-increasing availability of next generation sequencing (NGS) technologies, now provide researchers with unprecedented possibilities for dynamic and complex biological genomic analyses. Combining these technologies may lead to a deeper understanding of heterogeneous polygenic CVDs, better prognostic guidance, and, ultimately, greater personalized medicine. Advances will likely be achieved through increasingly frequent and robust genomic characterization of patients, as well the integration of genomic data with other clinical data, such as cardiac imaging, coronary angiography, and clinical biomarkers. This review discusses the current opportunities and limitations of genomics; provides a brief overview of AI; and identifies the current applications, limitations, and future directions of AI in genomics.</jats:p

Clonal Hematopoiesis Before, During, and After Human Spaceflight.

Clonal hematopoiesis (CH) occurs when blood cells harboring an advantageous mutation propagate faster than others. These mutations confer a risk for hematological cancers and cardiovascular disease. Here, we analyze CH in blood samples from a pair of twin astronauts over 4 years in bulk and fractionated cell populations using a targeted CH panel, linked-read whole-genome sequencing, and deep RNA sequencing. We show CH with distinct mutational profiles and increasing allelic fraction that includes a high-risk, TET2 clone in one subject and two DNMT3A mutations on distinct alleles in the other twin. These astronauts exhibit CH almost two decades prior to the mean age at which it is typically detected and show larger shifts in clone size than age-matched controls or radiotherapy patients, based on a longitudinal cohort of 157 cancer patients. As such, longitudinal monitoring of CH may serve as an important metric for overall cancer and cardiovascular risk in astronauts

Catching Element Formation In The Act

Gamma-ray astronomy explores the most energetic photons in nature to address some of the most pressing puzzles in contemporary astrophysics. It encompasses a wide range of objects and phenomena: stars, supernovae, novae, neutron stars, stellar-mass black holes, nucleosynthesis, the interstellar medium, cosmic rays and relativistic-particle acceleration, and the evolution of galaxies. MeV gamma-rays provide a unique probe of nuclear processes in astronomy, directly measuring radioactive decay, nuclear de-excitation, and positron annihilation. The substantial information carried by gamma-ray photons allows us to see deeper into these objects, the bulk of the power is often emitted at gamma-ray energies, and radioactivity provides a natural physical clock that adds unique information. New science will be driven by time-domain population studies at gamma-ray energies. This science is enabled by next-generation gamma-ray instruments with one to two orders of magnitude better sensitivity, larger sky coverage, and faster cadence than all previous gamma-ray instruments. This transformative capability permits: (a) the accurate identification of the gamma-ray emitting objects and correlations with observations taken at other wavelengths and with other messengers; (b) construction of new gamma-ray maps of the Milky Way and other nearby galaxies where extended regions are distinguished from point sources; and (c) considerable serendipitous science of scarce events -- nearby neutron star mergers, for example. Advances in technology push the performance of new gamma-ray instruments to address a wide set of astrophysical questions.Comment: 14 pages including 3 figure

Consensus Recommendations for the Use of Automated Insulin Delivery (AID) Technologies in Clinical Practice

International audienceThe significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past six years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials and real-world studies have shown that the use of AID systems is safe and effective in helping PwD achieve their long-term glycemic goals while reducing hypoglycemia risk. Thus, AID systems have recently become an integral part of diabetes management. However, recommendations for using AID systems in clinical settings have been lacking. Such guided recommendations are critical for AID success and acceptance. All clinicians working with PwD need to become familiar with the available systems in order to eliminate disparities in diabetes quality of care. This report provides much-needed guidance for clinicians who are interested in utilizing AIDs and presents a comprehensive listing of the evidence payers should consider when determining eligibility criteria for AID insurance coverage