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- 2019
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Journal article (peer-reviewed)
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- Berger, Ashton C, et al.
(author)
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A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers.
- 2018
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In: Cancer Cell. - : Elsevier BV. - 1535-6108 .- 1878-3686. ; 33:4, s. 690-705.e9
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Journal article (peer-reviewed)abstract
- We analyzed molecular data on 2,579 tumors from The Cancer Genome Atlas (TCGA) of four gynecological types plus breast. Our aims were to identify shared and unique molecular features, clinically significant subtypes, and potential therapeutic targets. We found 61 somatic copy-number alterations (SCNAs) and 46 significantly mutated genes (SMGs). Eleven SCNAs and 11 SMGs had not been identified in previous TCGA studies of the individual tumor types. We found functionally significant estrogen receptor-regulated long non-coding RNAs (lncRNAs) and gene/lncRNA interaction networks. Pathway analysis identified subtypes with high leukocyte infiltration, raising potential implications for immunotherapy. Using 16 key molecular features, we identified five prognostic subtypes and developed a decision tree that classified patients into the subtypes based on just six features that are assessable in clinical laboratories.
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- Kim, Ji Hoon, et al.
(author)
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THE AGORA HIGH-RESOLUTION GALAXY SIMULATIONS COMPARISON PROJECT. II. ISOLATED DISK TEST
- 2016
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In: Astrophysical Journal. - : American Astronomical Society. - 0004-637X .- 1538-4357. ; 833:2
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Journal article (peer-reviewed)abstract
- Using an isolated Milky Way-mass galaxy simulation, we compare results from nine state-of-the-art gravito-hydrodynamics codes widely used in the numerical community. We utilize the infrastructure we have built for the AGORA High-resolution Galaxy Simulations Comparison Project. This includes the common disk initial conditions, common physics models (e.g., radiative cooling and UV background by the standardized package Grackle) and common analysis toolkit yt, all of which are publicly available. Subgrid physics models such as Jeans pressure floor, star formation, supernova feedback energy, and metal production are carefully constrained across code platforms. With numerical accuracy that resolves the disk scale height, we find that the codes overall agree well with one another in many dimensions including: gas and stellar surface densities, rotation curves, velocity dispersions, density and temperature distribution functions, disk vertical heights, stellar clumps, star formation rates, and Kennicutt-Schmidt relations. Quantities such as velocity dispersions are very robust (agreement within a few tens of percent at all radii) while measures like newly formed stellar clump mass functions show more significant variation (difference by up to a factor of ∼3). Systematic differences exist, for example, between mesh-based and particle-based codes in the low-density region, and between more diffusive and less diffusive schemes in the high-density tail of the density distribution. Yet intrinsic code differences are generally small compared to the variations in numerical implementations of the common subgrid physics such as supernova feedback. Our experiment reassures that, if adequately designed in accordance with our proposed common parameters, results of a modern high-resolution galaxy formation simulation are more sensitive to input physics than to intrinsic differences in numerical schemes.
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- Kozhevnikov, Evgeny, et al.
(author)
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A dual-transduction-integrated biosensing system to examine the 3D cell-culture for bone regeneration
- 2019
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In: Biosensors & bioelectronics. - : ELSEVIER ADVANCED TECHNOLOGY. - 0956-5663 .- 1873-4235. ; 141
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Journal article (peer-reviewed)abstract
- Three-dimensional (3D) cell cultures developed with living cells and scaffolds have demonstrated outstanding potential for tissue engineering and regenerative medicine applications. However, no suitable tools are available to monitor dynamically variable cell behavior in such a complex microenvironment. In particular, simultaneously assessing cell behavior, cell secretion, and the general state of a 3D culture system is of a really challenging task. This paper presents our development of a dual-transduction-integrated biosensing system that assesses electrical impedance in conjunction with imaging techniques to simultaneously investigate the 3D cell-culture for bone regeneration. First, we created models to mimic the dynamic deposition of the extracellular matrix (ECM) in 3D culture, which underwent osteogenesis by incorporating different amounts of bone-ECM components (collagen, hydroxyapatite [HAp], and hyaluronic acid [HA]) into alginate-based hydrogels. The formed models were investigated by means of electrical impedance spectroscopy (EIS), with the results showing that the impedances increased linearly with collagen and hyaluronan, but changed in a more complex manner with HAp. Thereafter, we created two models that consisted of primary osteoblast cells (OBs), which expressed the enhanced green fluorescent protein (EGFP), and 4T1 cells, which secreted the EGFP-HA, in the alginate hydrogel. We found the capacitance (associated with impedance and measured by EIS) increased with the increases in initial embedded OBs, and also confirmed the cell proliferation over 3 days with the EGFP signal as monitored by the fluorescent imaging component in our system. Interestingly, the change in capacitance is found to be associated with OB migration following stimulation. Also, we show higher capacitance in 4T1 cells that secret HA when compared to control 4T1 cells after a 3-day culture. Taken together, we demonstrate that our biosensing system is able to investigate the dynamic process of 3D culture in a non-invasive and real-time manner.
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- Krueger, Jacob, et al.
(author)
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Where is my feature and what is it about? A case study on recovering feature facets
- 2019
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In: Journal of Systems and Software. - : Elsevier BV. - 0164-1212. ; 152, s. 239-253
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Journal article (peer-reviewed)abstract
- Developers commonly use features to define, manage, and communicate functionalities of a system. Unfortunately, the locations of features in code and other characteristics (feature facets), relevant for evolution and maintenance, are often poorly documented. Since developers change, and knowledge fades with time, such information often needs to be recovered. Modern projects boast a richness of information sources, such as pull requests, release logs, and otherwise specified domain knowledge. However, it is largely unknown from what sources the features, their locations, and their facets can be recovered. We present an exploratory study on identifying such information in two popular, variant-rich, and long-living systems: The 3D-printer firmware Marlin and the Android application Bitcoin-wallet. Besides the available information sources, we also investigated the projects' communities, communications, and development cultures. Our results show that a multitude of information sources (e.g., commit messages and pull requests) is helpful to recover features, locations, and facets to different extents. Pull requests were the most valuable source to recover facets, followed by commit messages and the issue tracker. As many of the studied information sources are, so far, rarely exploited in techniques for recovering features and their facets, we hope to inspire researchers and tool builders with our results. (C) 2019 Elsevier Inc. All rights reserved.
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- Ling, Yiming, et al.
(author)
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Observations of Kelvin-Helmholtz Waves in the Earth's Magnetotail Near the Lunar Orbit
- 2018
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In: Journal of Geophysical Research - Space Physics. - 2169-9380 .- 2169-9402. ; 123:5, s. 3836-3847
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Journal article (peer-reviewed)abstract
- Kelvin‐Helmholtz waves (KHWs), which have been widely observed at the magnetopause in the region near the Earth, play an essential role in the transport of solar wind plasma and energy into the magnetosphere under dominantly northward interplanetary magnetic field (IMF) conditions. In this study, we present simultaneous observations of KHWs under the northward IMF observed by both the Acceleration, Reconnection, Turbulence, and Electrodynamics of Moon's Interaction with the Sun (ARTEMIS) spacecraft in the Earth's magnetotail around the lunar orbit (at X ~ −50RE, Y ~ 30RE, dusk side) and the Geotail in the near‐Earth space (at X ~ −5RE, Y ~ −10RE, dawn side). The KHWs are quantitatively characterized by their dominant period, phase velocity, and wavelength, utilizing wavelet analysis and an approximation of their center‐of‐mass velocity. Our results suggest that the phase velocity and spatial scale of KHWs may increase as they propagate along the boundary layer toward the tail. Alternatively, the differences between the ARTEMIS and Geotail observations may indicate the possibility of dawn‐dusk asymmetry in the excited KHWs in this study. Our results strongly evidence the existence of the development of KHWs in terms of their wave frequency and scale size in the magnetotail and provide insight to the time evolution of KHWs along the magnetopause.
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- Mansouri, Kamel, et al.
(author)
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CERAPP : Collaborative Estrogen Receptor Activity Prediction Project
- 2016
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In: Journal of Environmental Health Perspectives. - : Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 124:7, s. 1023-1033
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Journal article (peer-reviewed)abstract
- BACKGROUND: Humans are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Most of these chemicals have never been tested for their ability to interact with the estrogen receptor (ER). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program. OBJECTIVES: We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) and demonstrate the efficacy of using predictive computational models trained on high-throughput screening data to evaluate thousands of chemicals for ER-related activity and prioritize them for further testing. METHODS: CERAPP combined multiple models developed in collaboration with 17 groups in the United States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure-activity relationship models and docking approaches were employed, mostly using a common training set of 1,677 chemical structures provided by the U.S. EPA, to build a total of 40 categorical and 8 continuous models for binding, agonist, and antagonist ER activity. All predictions were evaluated on a set of 7,522 chemicals curated from the literature. To overcome the limitations of single models, a consensus was built by weighting models on scores based on their evaluated accuracies. RESULTS: Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. Out of the 32,464 chemicals, the consensus model predicted 4,001 chemicals (12.3%) as high priority actives and 6,742 potential actives (20.8%) to be considered for further testing.CONCLUSION: This project demonstrated the possibility to screen large libraries of chemicals using a consensus of different in silico approaches. This concept will be applied in future projects related to other end points.
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