3,003 research outputs found

    Vol. 20, No. 4 (2000)

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    RMRP Is a Non-Coding RNA Essential for Early Murine Development

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    RMRP is a non-coding RNA that is ubiquitously expressed in both humans and mice. RMRP mutations that lead to decreased RMRP levels are found in the pleiotropic syndrome Cartilage Hair Hypoplasia. To assess the effects of deleting RMRP, we engineered a targeting vector that contains loxP sequences flanking RMRP and created hemizygous mice harboring this engineered allele (RMRP conditional). We found that insertion of this cassette suppressed RMRP expression, and we failed to obtain viable mice homozygous for the RMRP conditional allele. Furthermore, we were unable to obtain viable homozygous RMRP null mice, indicating that RMRP is essential for early embryonic development

    Genome-scale analysis identifies paralog lethality as a vulnerability of chromosome 1p loss in cancer.

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    Functional redundancy shared by paralog genes may afford protection against genetic perturbations, but it can also result in genetic vulnerabilities due to mutual interdependency1-5. Here, we surveyed genome-scale short hairpin RNA and CRISPR screening data on hundreds of cancer cell lines and identified MAGOH and MAGOHB, core members of the splicing-dependent exon junction complex, as top-ranked paralog dependencies6-8. MAGOHB is the top gene dependency in cells with hemizygous MAGOH deletion, a pervasive genetic event that frequently occurs due to chromosome 1p loss. Inhibition of MAGOHB in a MAGOH-deleted context compromises viability by globally perturbing alternative splicing and RNA surveillance. Dependency on IPO13, an importin-β receptor that mediates nuclear import of the MAGOH/B-Y14 heterodimer9, is highly correlated with dependency on both MAGOH and MAGOHB. Both MAGOHB and IPO13 represent dependencies in murine xenografts with hemizygous MAGOH deletion. Our results identify MAGOH and MAGOHB as reciprocal paralog dependencies across cancer types and suggest a rationale for targeting the MAGOHB-IPO13 axis in cancers with chromosome 1p deletion

    Parametrization of nonlinear and chaotic oscillations in driven beam-plasma diodes

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    Nonlinear phenomena in a driven plasma diode are studied using a fluid code and the particle-in-cell simulation code XPDPI. When a uniform electron beam is injected to a bounded diode filled with uniform ion background, the beam is destabilized by the Pierce instability and a perturbation grows to exhibit nonlinear oscillations including chaos. Two standard routes to chaos, period doubling and quasiperiodicity, are observed. Mode lockings of various winding numbers are observed in an ac driven system. A new diagnostic quantity is used to parametrize various nonlinear oscillations.open10

    Control of Cyclin D1 and Breast Tumorigenesis by the EglN2 Prolyl Hydroxylase

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    Summary2-Oxoglutarate-dependent dioxygenases, including the EglN prolyl hydroxylases that regulate HIF, can be inhibited with drug-like molecules. EglN2 is estrogen inducible in breast carcinoma cells and the lone Drosophila EglN interacts genetically with Cyclin D1. Although EglN2 is a nonessential gene, we found that EglN2 inactivation decreases Cyclin D1 levels and suppresses mammary gland proliferation in vivo. Regulation of Cyclin D1 is a specific attribute of EglN2 among the EglN proteins and is HIF independent. Loss of EglN2 catalytic activity inhibits estrogen-dependent breast cancer tumorigenesis and can be rescued by exogenous Cyclin D1. EglN2 depletion also impairs the fitness of lung, brain, and hematopoietic cancer lines. These findings support the exploration of EglN2 inhibitors as therapeutics for estrogen-dependent breast cancer and other malignancies

    Software engineering to sustain a high-performance computing scientific application: QMCPACK

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    We provide an overview of the software engineering efforts and their impact in QMCPACK, a production-level ab-initio Quantum Monte Carlo open-source code targeting high-performance computing (HPC) systems. Aspects included are: (i) strategic expansion of continuous integration (CI) targeting CPUs, using GitHub Actions runners, and NVIDIA and AMD GPUs in pre-exascale systems, using self-hosted hardware; (ii) incremental reduction of memory leaks using sanitizers, (iii) incorporation of Docker containers for CI and reproducibility, and (iv) refactoring efforts to improve maintainability, testing coverage, and memory lifetime management. We quantify the value of these improvements by providing metrics to illustrate the shift towards a predictive, rather than reactive, sustainable maintenance approach. Our goal, in documenting the impact of these efforts on QMCPACK, is to contribute to the body of knowledge on the importance of research software engineering (RSE) for the sustainability of community HPC codes and scientific discovery at scale.Comment: Accepted at the first US-RSE Conference, USRSE2023, https://us-rse.org/usrse23/, 8 pages, 3 figures, 4 table
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