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2. Profile of Vulnerability Remediations in Dependencies Using Graph Analysis

Author

Vera, Fernando, Pauliuchenka, Palina, Oh, Ethan, Kao, Bai Chien, DiValentin, Louis, and Bader, David A.

Subjects
Computer Science - Software Engineering, Computer Science - Cryptography and Security
Abstract

This research introduces graph analysis methods and a modified Graph Attention Convolutional Neural Network (GAT) to the critical challenge of open source package vulnerability remediation by analyzing control flow graphs to profile breaking changes in applications occurring from dependency upgrades intended to remediate vulnerabilities. Our approach uniquely applies node centrality metrics -- degree, norm, and closeness centrality -- to the GAT model, enabling a detailed examination of package code interactions with a focus on identifying and understanding vulnerable nodes, and when dependency package upgrades will interfere with application workflow. The study's application on a varied dataset reveals an unexpected limited inter-connectivity of vulnerabilities in core code, thus challenging established notions in software security. The results demonstrate the effectiveness of the enhanced GAT model in offering nuanced insights into the relational dynamics of code vulnerabilities, proving its potential in advancing cybersecurity measures. This approach not only aids in the strategic mitigation of vulnerabilities but also lays the groundwork for the development of sophisticated, sustainable monitoring systems for the evaluation of work effort for vulnerability remediation resulting from open source software. The insights gained from this study mark a significant advancement in the field of package vulnerability analysis and cybersecurity.

Published
2024

3. Cover Edge-Based Novel Triangle Counting

Author

Bader, David A., Li, Fuhuan, Du, Zhihui, Pauliuchenka, Palina, Rodriguez, Oliver Alvarado, Gupta, Anant, Minnal, Sai Sri Vastav, Nahata, Valmik, Ganeshan, Anya, Gundogdu, Ahmet, and Lew, Jason

Subjects
Computer Science - Data Structures and Algorithms
Abstract

Listing and counting triangles in graphs is a key algorithmic kernel for network analyses, including community detection, clustering coefficients, k-trusses, and triangle centrality. In this paper, we propose the novel concept of a cover-edge set that can be used to find triangles more efficiently. Leveraging the breadth-first search (BFS) method, we can quickly generate a compact cover-edge set. Novel sequential and parallel triangle counting algorithms that employ cover-edge sets are presented. The novel sequential algorithm performs competitively with the fastest previous approaches on both real and synthetic graphs, such as those from the Graph500 Benchmark and the MIT/Amazon/IEEE Graph Challenge. We implement 22 sequential algorithms for performance evaluation and comparison. At the same time, we employ OpenMP to parallelize 11 sequential algorithms, presenting an in-depth analysis of their parallel performance. Furthermore, we develop a distributed parallel algorithm that can asymptotically reduce communication on massive graphs. In our estimate from massive-scale Graph500 graphs, our distributed parallel algorithm can reduce the communication on a scale~36 graph by 1156x and on a scale~42 graph by 2368x. Comprehensive experiments are conducted on the recently launched Intel Xeon 8480+ processor and shed light on how graph attributes, such as topology, diameter, and degree distribution, can affect the performance of these algorithms.

Published
2024

4. Contour Algorithm for Connectivity

Author

Du, Zhihui, Rodriguez, Oliver Alvarado, Li, Fuhuan, Dindoost, Mohammad, and Bader, David A.

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Data Structures and Algorithms
Abstract

Finding connected components in a graph is a fundamental problem in graph analysis. In this work, we present a novel minimum-mapping based Contour algorithm to efficiently solve the connectivity problem. We prove that the Contour algorithm with two or higher order operators can identify all connected components of an undirected graph within $\mathcal{O}(\log d_{max})$ iterations, with each iteration involving $\mathcal{O}(m)$ work, where $d_{max}$ represents the largest diameter among all components in the given graph, and $m$ is the total number of edges in the graph. Importantly, each iteration is highly parallelizable, making use of the efficient minimum-mapping operator applied to all edges. To further enhance its practical performance, we optimize the Contour algorithm through asynchronous updates, early convergence checking, eliminating atomic operations, and choosing more efficient mapping operators. Our implementation of the Contour algorithm has been integrated into the open-source framework Arachne. Arachne extends Arkouda for large-scale interactive graph analytics, providing a Python API powered by the high-productivity parallel language Chapel. Experimental results on both real-world and synthetic graphs demonstrate the superior performance of our proposed Contour algorithm compared to state-of-the-art large-scale parallel algorithm FastSV and the fastest shared memory algorithm ConnectIt. On average, Contour achieves a speedup of 7.3x and 1.4x compared to FastSV and ConnectIt, respectively. All code for the Contour algorithm and the Arachne framework is publicly available on GitHub ( https://github.com/Bears-R-Us/arkouda-njit ), ensuring transparency and reproducibility of our work., Comment: 30th IEEE International Conference on High Performance Computing, Data, and Analytics, Goa, India, December 2023

Published
2023

5. Property Graphs in Arachne

Author

Rodriguez, Oliver Alvarado, Buschmann, Fernando Vera, Du, Zhihui, and Bader, David A.

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Analyzing large-scale graphs poses challenges due to their increasing size and the demand for interactive and user-friendly analytics tools. These graphs arise from various domains, including cybersecurity, social sciences, health sciences, and network sciences, where networks can represent interactions between humans, neurons in the brain, or malicious flows in a network. Exploring these large graphs is crucial for revealing hidden structures and metrics that are not easily computable without parallel computing. Currently, Python users can leverage the open-source Arkouda framework to efficiently execute Pandas and NumPy-related tasks on thousands of cores. To address large-scale graph analysis, Arachne, an extension to Arkouda, enables easy transformation of Arkouda dataframes into graphs. This paper proposes and evaluates three distributable data structures for property graphs, implemented in Chapel, that are integrated into Arachne. Enriching Arachne with support for property graphs will empower data scientists to extend their analysis to new problem domains. Property graphs present additional complexities, requiring efficient storage for extra information on vertices and edges, such as labels, relationships, and properties., Comment: The 27th Annual IEEE High Performance Extreme Computing Conference (HPEC), Virtual, September 25-29, 2023

Published
2023

6. Parallel Longest Common SubSequence Analysis In Chapel

Author

Vahidi, Soroush, Schieber, Baruch, Du, Zhihui, and Bader, David A.

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

One of the most critical problems in the field of string algorithms is the longest common subsequence problem (LCS). The problem is NP-hard for an arbitrary number of strings but can be solved in polynomial time for a fixed number of strings. In this paper, we select a typical parallel LCS algorithm and integrate it into our large-scale string analysis algorithm library to support different types of large string analysis. Specifically, we take advantage of the high-level parallel language, Chapel, to integrate Lu and Liu's parallel LCS algorithm into Arkouda, an open-source framework. Through Arkouda, data scientists can easily handle large string analytics on the back-end high-performance computing resources from the front-end Python interface. The Chapel-enabled parallel LCS algorithm can identify the longest common subsequences of two strings, and experimental results are given to show how the number of parallel resources and the length of input strings can affect the algorithm's performance., Comment: The 27th Annual IEEE High Performance Extreme Computing Conference (HPEC), Virtual, September 25-29, 2023

Published
2023

7. Fast Triangle Counting

Author

Bader, David A.

Subjects
Computer Science - Data Structures and Algorithms, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Listing and counting triangles in graphs is a key algorithmic kernel for network analyses including community detection, clustering coefficients, k-trusses, and triangle centrality. We design and implement a new serial algorithm for triangle counting that performs competitively with the fastest previous approaches on both real and synthetic graphs, such as those from the Graph500 Benchmark and the MIT/Amazon/IEEE Graph Challenge. The experimental results use the recently-launched Intel Xeon Platinum 8480+ and CPU Max 9480 processors., Comment: The 27th Annual IEEE High Performance Extreme Computing Conference (HPEC), Virtual, September 25-29, 2023. Graph Challenge Innovation Award

Published
2023

8. End-to-end resource analysis for quantum interior point methods and portfolio optimization

Author

Dalzell, Alexander M., Clader, B. David, Salton, Grant, Berta, Mario, Lin, Cedric Yen-Yu, Bader, David A., Stamatopoulos, Nikitas, Schuetz, Martin J. A., Brandão, Fernando G. S. L., Katzgraber, Helmut G., and Zeng, William J.

Subjects
Quantum Physics
Abstract

We study quantum interior point methods (QIPMs) for second-order cone programming (SOCP), guided by the example use case of portfolio optimization (PO). We provide a complete quantum circuit-level description of the algorithm from problem input to problem output, making several improvements to the implementation of the QIPM. We report the number of logical qubits and the quantity/depth of non-Clifford T-gates needed to run the algorithm, including constant factors. The resource counts we find depend on instance-specific parameters, such as the condition number of certain linear systems within the problem. To determine the size of these parameters, we perform numerical simulations of small PO instances, which lead to concrete resource estimates for the PO use case. Our numerical results do not probe large enough instance sizes to make conclusive statements about the asymptotic scaling of the algorithm. However, already at small instance sizes, our analysis suggests that, due primarily to large constant pre-factors, poorly conditioned linear systems, and a fundamental reliance on costly quantum state tomography, fundamental improvements to the QIPM are required for it to lead to practical quantum advantage., Comment: 40 pages, 15 figures. v2: minor corrections and updates to match journal version

Published
2022
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9. Triangle Counting Through Cover-Edges

Author

Bader, David A., Li, Fuhuan, Ganeshan, Anya, Gundogdu, Ahmet, Lew, Jason, Rodriguez, Oliver Alvarado, and Du, Zhihui

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Data Structures and Algorithms, F.2.2
Abstract

Counting and finding triangles in graphs is often used in real-world analytics to characterize cohesiveness and identify communities in graphs. In this paper, we propose the novel concept of a cover-edge set that can be used to find triangles more efficiently. We use a breadth-first search (BFS) to quickly generate a compact cover-edge set. Novel sequential and parallel triangle counting algorithms are presented that employ cover-edge sets. The sequential algorithm avoids unnecessary triangle-checking operations, and the parallel algorithm is communication-efficient. The parallel algorithm can asymptotically reduce communication on massive graphs such as from real social networks and synthetic graphs from the Graph500 Benchmark. In our estimate from massive-scale Graph500 graphs, our new parallel algorithm can reduce the communication on a scale 36 graph by 1156x and on a scale 42 graph by 2368x., Comment: The 27th Annual IEEE High Performance Extreme Computing Conference (HPEC), Virtual, September 25-29, 2023. Graph Challenge Student Innovation Award

Published
2022

10. The fully coupled regionally refined model of E3SM version 2: overview of the atmosphere, land, and river results

Author

Tang, Qi, Golaz, Jean-Christophe, Van Roekel, Luke P, Taylor, Mark A, Lin, Wuyin, Hillman, Benjamin R, Ullrich, Paul A, Bradley, Andrew M, Guba, Oksana, Wolfe, Jonathan D, Zhou, Tian, Zhang, Kai, Zheng, Xue, Zhang, Yunyan, Zhang, Meng, Wu, Mingxuan, Wang, Hailong, Tao, Cheng, Singh, Balwinder, Rhoades, Alan M, Qin, Yi, Li, Hong-Yi, Feng, Yan, Zhang, Yuying, Zhang, Chengzhu, Zender, Charles S, Xie, Shaocheng, Roesler, Erika L, Roberts, Andrew F, Mametjanov, Azamat, Maltrud, Mathew E, Keen, Noel D, Jacob, Robert L, Jablonowski, Christiane, Hughes, Owen K, Forsyth, Ryan M, Di Vittorio, Alan V, Caldwell, Peter M, Bisht, Gautam, McCoy, Renata B, Leung, L Ruby, and Bader, David C

Subjects
Earth Sciences, Oceanography, Atmospheric Sciences, Climate Action, Earth sciences
Abstract

This paper provides an overview of the United States (US) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2 (E3SMv2) fully coupled regionally refined model (RRM) and documents the overall atmosphere, land, and river results from the Coupled Model Intercomparison Project 6 (CMIP6) DECK (Diagnosis, Evaluation, and Characterization of Klima) and historical simulations - a first-of-its-kind set of climate production simulations using RRM. The North American (NA) RRM (NARRM) is developed as the high-resolution configuration of E3SMv2 with the primary goal of more explicitly addressing DOE's mission needs regarding impacts to the US energy sector facing Earth system changes. The NARRM features finer horizontal resolution grids centered over NA, consisting of 25→100¯km atmosphere and land, a 0.125 river-routing model, and 14→60¯km ocean and sea ice. By design, the computational cost of NARRM is 1/43× of the uniform low-resolution (LR) model at 100¯km but only 1/4¯10¯%-20¯% of a globally uniform high-resolution model at 25¯km. A novel hybrid time step strategy for the atmosphere is key for NARRM to achieve improved climate simulation fidelity within the high-resolution patch without sacrificing the overall global performance. The global climate, including climatology, time series, sensitivity, and feedback, is confirmed to be largely identical between NARRM and LR as quantified with typical climate metrics. Over the refined NA area, NARRM is generally superior to LR, including for precipitation and clouds over the contiguous US (CONUS), summertime marine stratocumulus clouds off the coast of California, liquid and ice phase clouds near the North Pole region, extratropical cyclones, and spatial variability in land hydrological processes. The improvements over land are related to the better-resolved topography in NARRM, whereas those over ocean are attributable to the improved air-sea interactions with finer grids for both atmosphere and ocean and sea ice. Some features appear insensitive to the resolution change analyzed here, for instance the diurnal propagation of organized mesoscale convective systems over CONUS and the warm-season land-atmosphere coupling at the southern Great Plains. In summary, our study presents a realistically efficient approach to leverage the fully coupled RRM framework for a standard Earth system model release and high-resolution climate production simulations.

Published
2023

11. Biological and Environmental Research Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Biological and Environmental Research, March 28-31, 2016, Rockville, Maryland

Author

Arkin, Adam, Bader, David C, Coffey, Richard, Antypas, Katie, Bard, Deborah, Dart, Eli, Dosanjh, Sudip, Gerber, Richard, Hack, James, Monga, Inder, Papka, Michael E, Riley, Katherine, Rotman, Lauren, Straatsma, Tjerk, Wells, Jack, Aluru, Srinivas, Andersen, Amity, Aprá, Edoardo, Azad, Ariful, Bates, Susan, Blaby, Ian, Blaby-Haas, Crysten, Bonneau, Rich, Bowen, Ben, Bradford, Mark A, Brodie, Eoin, Brown, James Ben, Buluc, Aydin, Bernholdt, David, Bylaska, Eric, Calvin, Kate, Cannon, Bill, Chen, Xingyuan, Cheng, Xiaolin, Cheung, Margaret, Chowdhary, Kenny, Colella, Phillip, Collins, Bill, Compo, Gil, Crowley, Mike, Debusschere, Bert, D’Imperio, Nicholas, Dror, Ron, Egan, Rob, Evans, Katherine, Friedberg, Iddo, Fyke, Jeremy, Gao, Zheng, Georganas, Evangelos, Giraldo, Frank, Gnanakaran, Gnana, Govind, Niri, Grandy, Stuart, Gustafson, Bill, Hammond, Glenn, Hargrove, William, Heroux, Michael, Hoffman, Forrest, Hofmeyr, Steven, Hunke, Elizabeth, Jackson, Charles, Jacob, Rob, Jacobson, Dan, Jacobson, Matt, Jain, Chirag, Johansen, Hans, Johnson, Jeff, Jones, Andy, Jones, Phil, Kalyanaraman, Ananth, Kang, Senghwa, King, Eric, Koanantakool, Penporn, Kollias, Pavlos, Kopera, Michal, Kotamarthi, Rao, Kowalski, Karol, Kumar, Jitendra, Kyrpides, Nikos, Leung, Ruby, Li, Xiaolin, Lin, Wuyin, Link, Robert, Liu, Yangang, Loew, Leslie, Luke, Edward, Ma, Hsi-Yen, Mahadevan, Radhakrishnan, Maranas, Costas, Martin, Daniel, Maslowski, Wieslaw, McCue, Lee Ann, McInnes, Lois Curfman, Mills, Richard, Molins Rafa, Sergi, Morozov, Dmitriy, Mostafavi, Sara, Moulton, David J, Mourao, Zenaida, and Najm, Habib

Published
2022

12. The rheumatoid arthritis drug auranofin lowers leptin levels and exerts antidiabetic effects in obese mice.

Author

Cox, Aaron, Masschelin, Peter, Saha, Pradip, Felix, Jessica, Sharp, Robert, Lian, Zeqin, Xia, Yan, Chernis, Natasha, Bader, David, Kim, Kang, Li, Xin, Yoshino, Jun, Li, Gang, Sun, Zheng, Wu, Huaizhu, Coarfa, Cristian, Moore, David, Klein, Samuel, Sun, Kai, and Hartig, Sean

Subjects
auranofin, inflammation, insulin sensitivity, leptin reduction, obesity, Animals, Mice, Mice, Obese, Hypoglycemic Agents, Auranofin, Diabetes Mellitus, Type 2, Arthritis, Rheumatoid, Obesity
Abstract

Low-grade, sustained inflammation in white adipose tissue (WAT) characterizes obesity and coincides with type 2 diabetes mellitus (T2DM). However, pharmacological targeting of inflammation lacks durable therapeutic effects in insulin-resistant conditions. Through a computational screen, we discovered that the FDA-approved rheumatoid arthritis drug auranofin improved insulin sensitivity and normalized obesity-associated abnormalities, including hepatic steatosis and hyperinsulinemia in mouse models of T2DM. We also discovered that auranofin accumulation in WAT depleted inflammatory responses to a high-fat diet without altering body composition in obese wild-type mice. Surprisingly, elevated leptin levels and blunted beta-adrenergic receptor activity achieved by leptin receptor deletion abolished the antidiabetic effects of auranofin. These experiments also revealed that the metabolic benefits of leptin reduction were superior to immune impacts of auranofin in WAT. Our studies uncover important metabolic properties of anti-inflammatory treatments and contribute to the notion that leptin reduction in the periphery can be accomplished to treat obesity and T2DM.

Published
2022

13. The DOE E3SM Model Version 2: Overview of the Physical Model and Initial Model Evaluation

Author

Golaz, Jean‐Christophe, Van Roekel, Luke P, Zheng, Xue, Roberts, Andrew F, Wolfe, Jonathan D, Lin, Wuyin, Bradley, Andrew M, Tang, Qi, Maltrud, Mathew E, Forsyth, Ryan M, Zhang, Chengzhu, Zhou, Tian, Zhang, Kai, Zender, Charles S, Wu, Mingxuan, Wang, Hailong, Turner, Adrian K, Singh, Balwinder, Richter, Jadwiga H, Qin, Yi, Petersen, Mark R, Mametjanov, Azamat, Ma, Po‐Lun, Larson, Vincent E, Krishna, Jayesh, Keen, Noel D, Jeffery, Nicole, Hunke, Elizabeth C, Hannah, Walter M, Guba, Oksana, Griffin, Brian M, Feng, Yan, Engwirda, Darren, Di Vittorio, Alan V, Dang, Cheng, Conlon, LeAnn M, Chen, Chih‐Chieh‐Jack, Brunke, Michael A, Bisht, Gautam, Benedict, James J, Asay‐Davis, Xylar S, Zhang, Yuying, Zhang, Meng, Zeng, Xubin, Xie, Shaocheng, Wolfram, Phillip J, Vo, Tom, Veneziani, Milena, Tesfa, Teklu K, Sreepathi, Sarat, Salinger, Andrew G, Eyre, JE Jack Reeves, Prather, Michael J, Mahajan, Salil, Li, Qing, Jones, Philip W, Jacob, Robert L, Huebler, Gunther W, Huang, Xianglei, Hillman, Benjamin R, Harrop, Bryce E, Foucar, James G, Fang, Yilin, Comeau, Darin S, Caldwell, Peter M, Bartoletti, Tony, Balaguru, Karthik, Taylor, Mark A, McCoy, Renata B, Leung, L Ruby, and Bader, David C

Subjects
Climate Action, DOE E3SM, climate modeling, Atmospheric Sciences
Abstract

This work documents version two of the Department of Energy's Energy Exascale Earth System Model (E3SM). E3SMv2 is a significant evolution from its predecessor E3SMv1, resulting in a model that is nearly twice as fast and with a simulated climate that is improved in many metrics. We describe the physical climate model in its lower horizontal resolution configuration consisting of 110 km atmosphere, 165 km land, 0.5° river routing model, and an ocean and sea ice with mesh spacing varying between 60 km in the mid-latitudes and 30 km at the equator and poles. The model performance is evaluated with Coupled Model Intercomparison Project Phase 6 Diagnosis, Evaluation, and Characterization of Klima simulations augmented with historical simulations as well as simulations to evaluate impacts of different forcing agents. The simulated climate has many realistic features of the climate system, with notable improvements in clouds and precipitation compared to E3SMv1. E3SMv1 suffered from an excessively high equilibrium climate sensitivity (ECS) of 5.3 K. In E3SMv2, ECS is reduced to 4.0 K which is now within the plausible range based on a recent World Climate Research Program assessment. However, a number of important biases remain including a weak Atlantic Meridional Overturning Circulation, deficiencies in the characteristics and spectral distribution of tropical atmospheric variability, and a significant underestimation of the observed warming in the second half of the historical period. An analysis of single-forcing simulations indicates that correcting the historical temperature bias would require a substantial reduction in the magnitude of the aerosol-related forcing.

Published
2022

14. LAGraph: Linear Algebra, Network Analysis Libraries, and the Study of Graph Algorithms

Author

Szárnyas, Gábor, Bader, David A., Davis, Timothy A., Kitchen, James, Mattson, Timothy G., McMillan, Scott, and Welch, Erik

Subjects
Computer Science - Mathematical Software, Computer Science - Data Structures and Algorithms
Abstract

Graph algorithms can be expressed in terms of linear algebra. GraphBLAS is a library of low-level building blocks for such algorithms that targets algorithm developers. LAGraph builds on top of the GraphBLAS to target users of graph algorithms with high-level algorithms common in network analysis. In this paper, we describe the first release of the LAGraph library, the design decisions behind the library, and performance using the GAP benchmark suite. LAGraph, however, is much more than a library. It is also a project to document and analyze the full range of algorithms enabled by the GraphBLAS. To that end, we have developed a compact and intuitive notation for describing these algorithms. In this paper, we present that notation with examples from the GAP benchmark suite., Comment: Accepted to GrAPL 2021

Published
2021

15. Parallel Triangles and Squares Count for Multigraphs Using Vertex Covers

Author

Cappelletti, Luca, Fontana, Tommaso, Green, Oded, Bader, David, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Mikyška, Jiří, editor, de Mulatier, Clélia, editor, Paszynski, Maciej, editor, Krzhizhanovskaya, Valeria V., editor, Dongarra, Jack J., editor, and Sloot, Peter M.A., editor

Published
2023
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16. Parallel Suffix Sorting for Large String Analytics

Author

Du, Zhihui, Zhang, Sen, Bader, David A., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Wyrzykowski, Roman, editor, Dongarra, Jack, editor, Deelman, Ewa, editor, and Karczewski, Konrad, editor

Published
2023
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18. Unintended Consequence: Diversity as a Casualty of Eliminating United States Medical Licensing Examination Step 1 Scores

Author

Amin, Sabina, Bader, David, Beckett, Brooke, Carter, Kevin, Chapman, Teresa, Chow, Bernard, Derylo, Amanda, Flaherty, Francis, Fox, Michael, Gould, Jennifer, Groves, Robert, Heitkamp, Darel, Heymann, John, Ho, Christopher, Hughes, Marion, Hull, Nathan, Jafroodifar, Abtin, Jay, Ann, Kamer, Aaron, Kelly, Hillary, Kennedy, Tabassum, Knippa, Emily, Koontz, Nicholas, Marx, Mary, Milburn, James, Mills, Megan, Molina, Marco, Morgan, Desiree, Morgan, Rustain, Omofoye, Toma, Peterson, Ryan, Romanelli, Donald, Schubert, Johanna, Schweitzer, Andrew, Seekins, Jayne, Stanfill, John, Udager, Kara, Vatakencherry, Geogy, Wang, Morlie, Weidenhaft, Mandy, Williamson, Clint, Wojtowycz, Andrij, Zarzour, Jessica, Campos, Felipe M., Grimm, Lars J., and Maxfield, Charles M.

Published
2023
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19. Mitophagy deficiency increases NLRP3 to induce brown fat dysfunction in mice

Author

Ko, Myoung Seok, Yun, Ji Young, Baek, In-Jeoung, Jang, Jung Eun, Hwang, Jung Jin, Lee, Seung Eun, Heo, Seung-Ho, Bader, David A, Lee, Chul-Ho, Han, Jaeseok, Moon, Jong-Seok, Lee, Jae Man, Hong, Eun-Gyoung, Lee, In-Kyu, Kim, Seong Who, Park, Joong Yeol, Hartig, Sean M, Kang, Un Jung, Moore, David D, Koh, Eun Hee, and Lee, Ki-up

Subjects
Biochemistry and Cell Biology, Biological Sciences, Genetics, Nutrition, Obesity, Aetiology, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Underpinning research, Metabolic and endocrine, Cardiovascular, Adipocytes, Adipose Tissue, Brown, Animals, Autophagy, Energy Metabolism, Inflammasomes, Mice, Knockout, Mitochondria, Mitophagy, NLR Family, Pyrin Domain-Containing 3 Protein, Reactive Oxygen Species, Brown adipocyte, inflammasome, pink1, transcriptional activation, white adipocyte, Biochemistry & Molecular Biology, Biochemistry and cell biology
Abstract

Although macroautophagy/autophagy deficiency causes degenerative diseases, the deletion of essential autophagy genes in adipocytes paradoxically reduces body weight. Brown adipose tissue (BAT) plays an important role in body weight regulation and metabolic control. However, the key cellular mechanisms that maintain BAT function remain poorly understood. in this study, we showed that global or brown adipocyte-specific deletion of pink1, a Parkinson disease-related gene involved in selective mitochondrial autophagy (mitophagy), induced BAT dysfunction, and obesity-prone type in mice. Defective mitochondrial function is among the upstream signals that activate the NLRP3 inflammasome. NLRP3 was induced in brown adipocyte precursors (BAPs) from pink1 knockout (KO) mice. Unexpectedly, NLRP3 induction did not induce canonical inflammasome activity. Instead, NLRP3 induction led to the differentiation of pink1 KO BAPs into white-like adipocytes by increasing the expression of white adipocyte-specific genes and repressing the expression of brown adipocyte-specific genes. nlrp3 deletion in pink1 knockout mice reversed BAT dysfunction. Conversely, adipose tissue-specific atg7 KO mice showed significantly lower expression of Nlrp3 in their BAT. Overall, our data suggest that the role of mitophagy is different from general autophagy in regulating adipose tissue and whole-body energy metabolism. Our results uncovered a new mitochondria-NLRP3 pathway that induces BAT dysfunction. The ability of the nlrp3 knockouts to rescue BAT dysfunction suggests the transcriptional function of NLRP3 as an unexpected, but a quite specific therapeutic target for obesity-related metabolic diseases.Abbreviations: ACTB: actin, beta; BAPs: brown adipocyte precursors; BAT: brown adipose tissue; BMDMs: bone marrow-derived macrophages; CASP1: caspase 1; CEBPA: CCAAT/enhancer binding protein (C/EBP), alpha; ChIP: chromatin immunoprecipitation; EE: energy expenditure; HFD: high-fat diet; IL1B: interleukin 1 beta; ITT: insulin tolerance test; KO: knockout; LPS: lipopolysaccharide; NLRP3: NLR family, pyrin domain containing 3; PINK1: PTEN induced putative kinase 1; PRKN: parkin RBR E3 ubiquitin protein ligase; RD: regular diet; ROS: reactive oxygen species; RT: room temperature; UCP1: uncoupling protein 1 (mitochondrial, proton carrier); WT: wild-type.

Published
2021

20. Performance Impact of Memory Channels on Sparse and Irregular Algorithms

Author

Green, Oded, Fox, James, Young, Jeffrey, Shirako, Jun, and Bader, David

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Hardware Architecture, Computer Science - Performance
Abstract

Graph processing is typically considered to be a memory-bound rather than compute-bound problem. One common line of thought is that more available memory bandwidth corresponds to better graph processing performance. However, in this work we demonstrate that the key factor in the utilization of the memory system for graph algorithms is not necessarily the raw bandwidth or even the latency of memory requests. Instead, we show that performance is proportional to the number of memory channels available to handle small data transfers with limited spatial locality. Using several widely used graph frameworks, including Gunrock (on the GPU) and GAPBS \& Ligra (for CPUs), we evaluate key graph analytics kernels using two unique memory hierarchies, DDR-based and HBM/MCDRAM. Our results show that the differences in the peak bandwidths of several Pascal-generation GPU memory subsystems aren't reflected in the performance of various analytics. Furthermore, our experiments on CPU and Xeon Phi systems demonstrate that the number of memory channels utilized can be a decisive factor in performance across several different applications. For CPU systems with smaller thread counts, the memory channels can be underutilized while systems with high thread counts can oversaturate the memory subsystem, which leads to limited performance. Finally, we model the potential performance improvements of adding more memory channels with narrower access widths than are found in current platforms, and we analyze performance trade-offs for the two most prominent types of memory accesses found in graph algorithms, streaming and random accesses.

Published
2019

21. A Simple and Efficient Algorithm for Finding Minimum Spanning Tree Replacement Edges

Author

Bader, David A. and Burkhardt, Paul

Subjects
Computer Science - Data Structures and Algorithms
Abstract

Given an undirected, weighted graph, the minimum spanning tree (MST) is a tree that connects all of the vertices of the graph with minimum sum of edge weights. In real world applications, network designers often seek to quickly find a replacement edge for each edge in the MST. For example, when a traffic accident closes a road in a transportation network, or a line goes down in a communication network, the replacement edge may reconnect the MST at lowest cost. In the paper, we consider the case of finding the lowest cost replacement edge for each edge of the MST. A previous algorithm by Tarjan takes $O(m \alpha(m, n))$ time and space, where $\alpha(m, n)$ is the inverse Ackermann's function. Given the MST and sorted non-tree edges, our algorithm is the first practical algorithm that runs in $O(m+n)$ time and $O(m+n)$ space to find all replacement edges. Additionally, since the most vital edge is the tree edge whose removal causes the highest cost, our algorithm finds it in linear time.

Published
2019
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23. The DOE E3SM Coupled Model Version 1: Description and Results at High Resolution

Author

Caldwell, Peter M, Mametjanov, Azamat, Tang, Qi, Van Roekel, Luke P, Golaz, Jean‐Christophe, Lin, Wuyin, Bader, David C, Keen, Noel D, Feng, Yan, Jacob, Robert, Maltrud, Mathew E, Roberts, Andrew F, Taylor, Mark A, Veneziani, Milena, Wang, Hailong, Wolfe, Jonathan D, Balaguru, Karthik, Cameron‐Smith, Philip, Dong, Lu, Klein, Stephen A, Leung, L Ruby, Li, Hong‐Yi, Li, Qing, Liu, Xiaohong, Neale, Richard B, Pinheiro, Marielle, Qian, Yun, Ullrich, Paul A, Xie, Shaocheng, Yang, Yang, Zhang, Yuying, Zhang, Kai, and Zhou, Tian

Subjects
Earth Sciences, Oceanography, Atmospheric Sciences, Climate Action, Atmospheric sciences, Geoinformatics
Abstract

This study provides an overview of the coupled high-resolution Version 1 of the Energy Exascale Earth System Model (E3SMv1) and documents the characteristics of a 50-year-long high-resolution control simulation with time-invariant 1950 forcings following the HighResMIP protocol. In terms of global root-mean-squared error metrics, this high-resolution simulation is generally superior to results from the low-resolution configuration of E3SMv1 (due to resolution, tuning changes, and possibly initialization procedure) and compares favorably to models in the CMIP5 ensemble. Ocean and sea ice simulation is particularly improved, due to better resolution of bathymetry, the ability to capture more variability and extremes in winds and currents, and the ability to resolve mesoscale ocean eddies. The largest improvement in this regard is an ice-free Labrador Sea, which is a major problem at low resolution. Interestingly, several features found to improve with resolution in previous studies are insensitive to resolution or even degrade in E3SMv1. Most notable in this regard are warm bias and associated stratocumulus deficiency in eastern subtropical oceans and lack of improvement in El Niño. Another major finding of this study is that resolution increase had negligible impact on climate sensitivity (measured by net feedback determined through uniform +4K prescribed sea surface temperature increase) and aerosol sensitivity. Cloud response to resolution increase consisted of very minor decrease at all levels. Large-scale patterns of precipitation bias were also relatively unaffected by grid spacing.

Published
2019

24. Scalable Katz Ranking Computation in Large Static and Dynamic Graphs

Author

van der Grinten, Alexander, Bergamini, Elisabetta, Green, Oded, Bader, David A., and Meyerhenke, Henning

Subjects
Computer Science - Data Structures and Algorithms, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Network analysis defines a number of centrality measures to identify the most central nodes in a network. Fast computation of those measures is a major challenge in algorithmic network analysis. Aside from closeness and betweenness, Katz centrality is one of the established centrality measures. In this paper, we consider the problem of computing rankings for Katz centrality. In particular, we propose upper and lower bounds on the Katz score of a given node. While previous approaches relied on numerical approximation or heuristics to compute Katz centrality rankings, we construct an algorithm that iteratively improves those upper and lower bounds until a correct Katz ranking is obtained. We extend our algorithm to dynamic graphs while maintaining its correctness guarantees. Experiments demonstrate that our static graph algorithm outperforms both numerical approaches and heuristics with speedups between 1.5x and 3.5x, depending on the desired quality guarantees. Our dynamic graph algorithm improves upon the static algorithm for update batches of less than 10000 edges. We provide efficient parallel CPU and GPU implementations of our algorithms that enable near real-time Katz centrality computation for graphs with hundreds of millions of nodes in fractions of seconds., Comment: Published at ESA'18

Published
2018

27. Introduction to GraphBLAS

Author

Kepner, Jeremy, primary, Aaltonen, Peter, additional, Bader, David, additional, Buluc, Aydin, additional, Franchetti, Franz, additional, Gilbert, John, additional, Hutchison, Shana, additional, Kumar, Manoj, additional, Lumsdaine, Andrew, additional, Meyerhenke, Henning, additional, McMillan, Scott, additional, Moreira, Jose, additional, Owens, John D., additional, Yang, Carl, additional, Zalewski, Marcin, additional, and Mattson, Timothy G., additional

Published
2022
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28. The DOE E3SM Coupled Model Version 1: Overview and Evaluation at Standard Resolution

Author

Golaz, Jean‐Christophe, Caldwell, Peter M, Van Roekel, Luke P, Petersen, Mark R, Tang, Qi, Wolfe, Jonathan D, Abeshu, Guta, Anantharaj, Valentine, Asay‐Davis, Xylar S, Bader, David C, Baldwin, Sterling A, Bisht, Gautam, Bogenschutz, Peter A, Branstetter, Marcia, Brunke, Michael A, Brus, Steven R, Burrows, Susannah M, Cameron‐Smith, Philip J, Donahue, Aaron S, Deakin, Michael, Easter, Richard C, Evans, Katherine J, Feng, Yan, Flanner, Mark, Foucar, James G, Fyke, Jeremy G, Griffin, Brian M, Hannay, Cécile, Harrop, Bryce E, Hoffman, Mattthew J, Hunke, Elizabeth C, Jacob, Robert L, Jacobsen, Douglas W, Jeffery, Nicole, Jones, Philip W, Keen, Noel D, Klein, Stephen A, Larson, Vincent E, Leung, L Ruby, Li, Hong‐Yi, Lin, Wuyin, Lipscomb, William H, Ma, Po‐Lun, Mahajan, Salil, Maltrud, Mathew E, Mametjanov, Azamat, McClean, Julie L, McCoy, Renata B, Neale, Richard B, Price, Stephen F, Qian, Yun, Rasch, Philip J, Eyre, JE Jack Reeves, Riley, William J, Ringler, Todd D, Roberts, Andrew F, Roesler, Erika L, Salinger, Andrew G, Shaheen, Zeshawn, Shi, Xiaoying, Singh, Balwinder, Tang, Jinyun, Taylor, Mark A, Thornton, Peter E, Turner, Adrian K, Veneziani, Milena, Wan, Hui, Wang, Hailong, Wang, Shanlin, Williams, Dean N, Wolfram, Phillip J, Worley, Patrick H, Xie, Shaocheng, Yang, Yang, Yoon, Jin‐Ho, Zelinka, Mark D, Zender, Charles S, Zeng, Xubin, Zhang, Chengzhu, Zhang, Kai, Zhang, Yuying, Zheng, Xue, Zhou, Tian, and Zhu, Qing

Subjects
Earth Sciences, Oceanography, Atmospheric Sciences, Climate Action, Atmospheric sciences, Geoinformatics
Abstract

This work documents the first version of the U.S. Department of Energy (DOE) new Energy Exascale Earth System Model (E3SMv1). We focus on the standard resolution of the fully coupled physical model designed to address DOE mission-relevant water cycle questions. Its components include atmosphere and land (110-km grid spacing), ocean and sea ice (60 km in the midlatitudes and 30 km at the equator and poles), and river transport (55 km) models. This base configuration will also serve as a foundation for additional configurations exploring higher horizontal resolution as well as augmented capabilities in the form of biogeochemistry and cryosphere configurations. The performance of E3SMv1 is evaluated by means of a standard set of Coupled Model Intercomparison Project Phase 6 (CMIP6) Diagnosis, Evaluation, and Characterization of Klima simulations consisting of a long preindustrial control, historical simulations (ensembles of fully coupled and prescribed SSTs) as well as idealized CO2 forcing simulations. The model performs well overall with biases typical of other CMIP-class models, although the simulated Atlantic Meridional Overturning Circulation is weaker than many CMIP-class models. While the E3SMv1 historical ensemble captures the bulk of the observed warming between preindustrial (1850) and present day, the trajectory of the warming diverges from observations in the second half of the twentieth century with a period of delayed warming followed by an excessive warming trend. Using a two-layer energy balance model, we attribute this divergence to the model's strong aerosol-related effective radiative forcing (ERFari+aci = −1.65 W/m2) and high equilibrium climate sensitivity (ECS = 5.3 K).

Published
2019

29. Mitochondrial pyruvate import is a metabolic vulnerability in androgen receptor-driven prostate cancer.

Author

Bader, David, Hartig, Sean, Putluri, Vasanta, Foley, Christopher, Hamilton, Mark, Smith, Eric, Saha, Pradip, Panigrahi, Anil, Walker, Christopher, Zong, Lin, Martini-Stoica, Heidi, Chen, Rui, Rajapakshe, Kimal, Coarfa, Cristian, Sreekumar, Arun, Mitsiades, Nicholas, Bankson, James, Ittmann, Michael, OMalley, Bert, Putluri, Nagireddy, and McGuire, Sean

Subjects
Animals, Biological Transport, Cell Line, Tumor, Disease Models, Animal, Gene Expression Regulation, Neoplastic, Glutamine, Humans, Male, Metabolic Networks and Pathways, Mice, Mice, Transgenic, Mitochondria, Mitochondrial Membrane Transport Proteins, Monocarboxylic Acid Transporters, Prostatic Neoplasms, Prostatic Neoplasms, Castration-Resistant, Protein Binding, Pyruvic Acid, Receptors, Androgen, Signal Transduction
Abstract

Specific metabolic underpinnings of androgen receptor (AR)-driven growth in prostate adenocarcinoma (PCa) are largely undefined, hindering the development of strategies to leverage the metabolic dependencies of this disease when hormonal manipulations fail. Here we show that the mitochondrial pyruvate carrier (MPC), a critical metabolic conduit linking cytosolic and mitochondrial metabolism, is transcriptionally regulated by AR. Experimental MPC inhibition restricts proliferation and metabolic outputs of the citric acid cycle (TCA) including lipogenesis and oxidative phosphorylation in AR-driven PCa models. Mechanistically, metabolic disruption resulting from MPC inhibition activates the eIF2α/ATF4 integrated stress response (ISR). ISR signaling prevents cell cycle progression while coordinating salvage efforts, chiefly enhanced glutamine assimilation into the TCA, to regain metabolic homeostasis. We confirm that MPC function is operant in PCa tumors in-vivo using isotopomeric metabolic flux analysis. In turn, we apply a clinically viable small molecule targeting the MPC, MSDC0160, to pre-clinical PCa models and find that MPC inhibition suppresses tumor growth in hormone-responsive and castrate-resistant conditions. Collectively, our findings characterize the MPC as a tractable therapeutic target in AR-driven prostate tumors.

Published
2019

30. miR-30a Remodels Subcutaneous Adipose Tissue Inflammation to Improve Insulin Sensitivity in Obesity

Author

Koh, Eun-Hee, Chernis, Natasha, Saha, Pradip K, Xiao, Liuling, Bader, David A, Zhu, Bokai, Rajapakshe, Kimal, Hamilton, Mark P, Liu, Xia, Perera, Dimuthu, Chen, Xi, York, Brian, Trauner, Michael, Coarfa, Cristian, Bajaj, Mandeep, Moore, David D, Deng, Tuo, McGuire, Sean E, and Hartig, Sean M

Subjects
Biomedical and Clinical Sciences, Diabetes, Obesity, Biotechnology, Nutrition, Genetics, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Oral and gastrointestinal, Cardiovascular, Adipose Tissue, White, Animals, Diabetes Mellitus, Type 2, Diet, High-Fat, Energy Metabolism, Insulin Resistance, Liver, Mice, MicroRNAs, STAT1 Transcription Factor, Subcutaneous Fat, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences
Abstract

Chronic inflammation accompanies obesity and limits subcutaneous white adipose tissue (WAT) expandability, accelerating the development of insulin resistance and type 2 diabetes mellitus. MicroRNAs (miRNAs) influence expression of many metabolic genes in fat cells, but physiological roles in WAT remain poorly characterized. Here, we report that expression of the miRNA miR-30a in subcutaneous WAT corresponds with insulin sensitivity in obese mice and humans. To examine the hypothesis that restoration of miR-30a expression in WAT improves insulin sensitivity, we injected adenovirus (Adv) expressing miR-30a into the subcutaneous fat pad of diabetic mice. Exogenous miR-30a expression in the subcutaneous WAT depot of obese mice coupled improved insulin sensitivity and increased energy expenditure with decreased ectopic fat deposition in the liver and reduced WAT inflammation. High-throughput proteomic profiling and RNA-Seq suggested that miR-30a targets the transcription factor STAT1 to limit the actions of the proinflammatory cytokine interferon-γ (IFN-γ) that would otherwise restrict WAT expansion and decrease insulin sensitivity. We further demonstrated that miR-30a opposes the actions of IFN-γ, suggesting an important role for miR-30a in defending adipocytes against proinflammatory cytokines that reduce peripheral insulin sensitivity. Together, our data identify a critical molecular signaling axis, elements of which are involved in uncoupling obesity from metabolic dysfunction.

Published
2018

31. Exemplar or Matching: Modeling DCJ Problems with Unequal Content Genome Data

Author

Yin, Zhaoming, Tang, Jijun, Schaeffer, Stephen W., and Bader, David A.

Subjects
Computer Science - Data Structures and Algorithms, Computer Science - Computational Engineering, Finance, and Science, Quantitative Biology - Genomics
Abstract

The edit distance under the DCJ model can be computed in linear time for genomes with equal content or with Indels. But it becomes NP-Hard in the presence of duplications, a problem largely unsolved especially when Indels are considered. In this paper, we compare two mainstream methods to deal with duplications and associate them with Indels: one by deletion, namely DCJ-Indel-Exemplar distance; versus the other by gene matching, namely DCJ-Indel-Matching distance. We design branch-and-bound algorithms with set of optimization methods to compute exact distances for both. Furthermore, median problems are discussed in alignment with both of these distance methods, which are to find a median genome that minimizes distances between itself and three given genomes. Lin-Kernighan (LK) heuristic is leveraged and powered up by sub-graph decomposition and search space reduction technologies to handle median computation. A wide range of experiments are conducted on synthetic data sets and real data sets to show pros and cons of these two distance metrics per se, as well as putting them in the median computation scenario., Comment: 17 pages

Published
2017
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32. Envisioning U.S. Climate Predictions and Projections to Meet New Challenges.

Author

Mariotti, Annarita, Bader, David C., Bauer, Susanne E., Danabasoglu, Gokhan, Dunne, John, Gross, Brian, Leung, L. Ruby, Pawson, Steven, Putman, William R., Ramaswamy, Venkatachalam, Schmidt, Gavin A., and Tallapragada, Vijay

Subjects
CLIMATE change, CLIMATOLOGY, ARTIFICIAL intelligence, DATA warehousing, FORECASTING, MACHINE learning, CLOUD storage
Abstract

In the face of a changing climate, the understanding, predictions, and projections of natural and human systems are increasingly crucial to prepare and cope with extremes and cascading hazards, determine unexpected feedbacks and potential tipping points, inform long‐term adaptation strategies, and guide mitigation approaches. Increasingly complex socio‐economic systems require enhanced predictive information to support advanced practices. Such new predictive challenges drive the need to fully capitalize on ambitious scientific and technological opportunities. These include the unrealized potential for very high‐resolution modeling of global‐to‐local Earth system processes across timescales, reduction of model biases, enhanced integration of human systems and the Earth Systems, better quantification of predictability and uncertainties; expedited science‐to‐service pathways, and co‐production of actionable information with stakeholders. Enabling technological opportunities include exascale computing, advanced data storage, novel observations and powerful data analytics, including artificial intelligence and machine learning. Looking to generate community discussions on how to accelerate progress on U.S. climate predictions and projections, representatives of Federally‐funded U.S. modeling groups outline here perspectives on a six‐pillar national approach grounded in climate science that builds on the strengths of the U.S. modeling community and agency goals. This calls for an unprecedented level of coordination to capitalize on transformative opportunities, augmenting and complementing current modeling center capabilities and plans to support agency missions. Tangible outcomes include projections with horizontal spatial resolutions finer than 10 km, representing extremes and associated risks in greater detail, reduced model errors, better predictability estimates, and more customized projections to support next generation climate services. Plain Language Summary: In the face of a changing climate, the understanding, predictions and projections of natural and human systems are increasingly crucial to prepare and cope with extremes and cascading hazards, determine unexpected feedbacks and potential tipping points, inform long‐term adaptation strategies, and guide mitigation approaches. Increasingly complex socio‐economic systems require enhanced predictive information to support advanced practices. Such new predictive challenges drive the need to fully capitalize on ambitious scientific and technological opportunities currently at hand, and working with stakeholders to co‐produce the information that they require. Looking to generate community discussions on how to accelerate progress on U.S. climate predictions and projections, representatives of Federally‐funded U.S. modeling groups outline here perspectives on a six‐pillar national approach grounded in climate science that builds on the strengths of the U.S. modeling community and agency goals. This calls for an unprecedented level of coordination to capitalize on transformative opportunities, augmenting and complementing current modeling center capabilities and plans to support agency missions. Tangible outcomes include projections with horizontal spatial resolutions finer than 10 km, representing extremes and associated risks in greater detail, reduced model errors, better predictability estimates, and more customized projections to support the next generation of climate services. Key Points: Facing the uncharted territory of a changed climate and increasingly complex socio‐economic systems requires the best possible predictionsScientific and technological opportunities are at hand to accelerate progress on U.S. climate predictions and projectionsCapitalizing on the most transformative opportunities calls for an unprecedented level of coordination and resources [ABSTRACT FROM AUTHOR]

Published
2024
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34. QoS-Aware and Fault-Tolerant Replica Placement

Author

Hu, Jingkun, Du, Zhihui, Zhang, Sen, Bader, David A., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, and Qiu, Meikang, editor

Published
2020
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36. End-To-End Resource Analysis for Quantum Interior-Point Methods and Portfolio Optimization

Author

Dalzell, Alexander M., primary, Clader, B. David, additional, Salton, Grant, additional, Berta, Mario, additional, Lin, Cedric Yen-Yu, additional, Bader, David A., additional, Stamatopoulos, Nikitas, additional, Schuetz, Martin J. A., additional, Brandão, Fernando G. S. L., additional, Katzgraber, Helmut G., additional, and Zeng, William J., additional

Published
2023
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37. Envisioning U.S. Climate Predictions and Projections to Meet New Challenges

Author

Mariotti, Annarita, primary, Bader, David Craig, additional, Bauer, Susanne E., additional, Danabasoglu, Gokhan, additional, Dunne, John P. Patrick, additional, Gross, Brian, additional, Leung, L. Ruby, additional, Pawson, Steven, additional, Putman, William M, additional, Ramaswamy, V, additional, Schmidt, Gavin A., additional, and Tallapragada, Vijay, additional

Published
2023
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39. Variations in Neonatal Length of Stay of Babies Born Extremely Preterm: An International Comparison Between iNeo Networks

Author

Lui, Kei, Marshall, Peter, Schmidt, Peter, Dhawan, Anjali, Korostenski, Larissa, Travadi, Javeed Travadi, Sharp, Mary, Gill, Andy, Pillow, Jane, Stack, Jacqueline, Birch, Pita, Nothdurft, Karen, Cooke, Lucy, Casalaz, Dan, Holberton, Jim, Stewart, Alice, Downe, Lyn, Stewart, Michael, Berry, Andrew, Hunt, Rod, Morris, Peter, Paoli, Tony De, Bolisetty, Srinivas, Paradisis, Mary, Greenhalgh, Mark, Koorts, Pieter, Kuschel, Carl, Jacobs, Sue, Doyle, Lex, Craven, John, Numa, Andrew, Carlisle, Hazel, Badawi, Nadia, Popat, Himanshu, Koh, Guan, Davis, Jonathan, Luig, Melissa, Headley, Bevan, Andersen, Chad, Ng, Linda, Chambers, Georgina, Austin, Nicola, Lynn, Adrienne, Darlow, Brian, Edmonds, Liza, Mildenhall, Lindsay, Buksh, Mariam, Battin, Malcolm, Boom, Jutta van den, Richardson, Vaughan, Barker, David, Hammond, Barbara, Rajadurai, Victor Samuel, Lam, Simon, Fung, Genevieve, Shah, Prakesh S., Beltempo, Marc, Kanungo, Jaideep, Ting, Joseph, Cieslak, Zenon, Sherlock, Rebecca, Mehrem, Ayman Abou, Toye, Jennifer, Aziz, Khalid, Fajardo, Carlos, Bodani, Jaya, Strueby, Lannae, Seshia, Mary, Louis, Deepak, Alvaro, Ruben, Mukerji, Amit, Da Silva, Orlando, Adie, Mohammad, Lee, Kyong-Soon, Ng, Eugene, Lemyre, Brigitte, Daboval, Thierry, Khurshid, Faiza, Pelausa, Ermelinda, Barrington, Keith, Lapoint, Anie, Ethier, Guillaume, Drolet, Christine, Piedboeuf, Bruno, Claveau, Martine, St-Hilaire, Marie, Bertelle, Valerie, Masse, Edith, Canning, Roderick, Makary, Hala, Ojah, Cecil, Monterrosa, Luis, Emberley, Julie, Afifi, Jehier, Kajetanowicz, Andrzej, Lee, Shoo K., Metsäranta, Marjo, Lehtonen, Liisa, Tammela, Outi, Sankilampi, Ulla, Saarela, Timo, Morag, Iris, Zangen, Shmuel, Smolkin, Tatyana, Mimouni, Francis, Bader, David, Rothschild, Avi, Strauss, Zipora, Felszer, Clari, Omari, Hussam, Tov-Friedman, Smadar Even, Bar-Oz, Benjamin, Feldman, Michael, Saad, Nizar, Flidel-Rimon, Orna, Weisbrod, Meir, Lubin, Daniel, Litmanovitz, Ita, Kugelman, Amir, Shinwell, Eric, Klinger, Gil, Nijim, Yousif, Bin-Nun, Alona, Golan, Agneta, Mandel, Dror, Fleisher-Sheffer, Vered, Oron, Anat, Bakhrakh, Lev, Hattori, Satoshi, Shirai, Masaru, Ishioka, Toru, Mori, Toshihiko, Amizuka, Takasuke, Huchimukai, Toru, Yoshida, Hiroshi, Sasaki, Ayako, Shimizu, Junichi, Nakamura, Toshihiko, Maruyama, Mami, Matsumoto, Hiroshi, Hosokawa, Shinichi, Taki, Atsuko, Nakagawa, Machiko, Ko, Kyone, Uozumi, Azusa, Nakata, Setsuko, Shimazaki, Akira, Yoda, Tatsuya, Numata, Osamu, Imamura, Hiroaki, Kobayashi, Azusa, Tokuriki, Shuko, Uchida, Yasushi, Arai, Takahiro, Ito, Mitsuhiro, Ieda, Kuniko, Ono, Toshiyuki, Hayashi, Masashi, Maki, Kanemasa, Yamakawa, MieToru, Kawai, Masahiko, Fujii, Noriko, Shiomi, Kozue, Nozaki, Koji, Wada, Hiroshi, Kim, Taho, Tokunaga, Yasuyuki, Takatera, Akihiro, Oshima, Toshio, Sumida, Hiroshi, Michinomae, Yae, Kusumoto, Yoshio, Yoshimoto, Seiji, Morisawa, Takeshi, Ohashi, Tamaki, Takahashi, Yukihiro, Sugimoto, Moriharu, Ono, Noriaki, Miyagawa, Shinichiro, Saijo, Takahiko, Yamagami, Takashi, Koyano, Kosuke, Kobayashi, Shoko, Kanda, Takeshi, Sakemi, Yoshihiro, Aoki, Mikio, Iida, Koichi, Goshi, Mitsushi, Maruyama, Yuko, Avila-Alvarez, Alejandro, Fernandez-Trisac, José Luis, Pico, M<ce:sup loc='post">a</ce:sup> Luz Couce, Fernández Seara, María José, Gutiérrez, Andrés Martínez, Vizcaíno, Carolina, Iglesias, Miriam Salvador, Zaplana, Honorio Sánchez, Colomer, Belén Fernández, García López, José Enrique, Mozo, Rafael García, González Martínez, M. Teresa, Sebastián, M<ce:sup loc='post">a</ce:sup> Dolores Muro, Carbonell, Marta Balart, Barnusell, Joan Badia, Puiggròs, Mònica Domingo, Aloy, Josep Figueras, Mussons, Francesc Botet, Sanz, Israel Anquela, Galiana, Gemma Ginovart, Coroleu, W., Iriondo, Martin, Vilella, Laura Castells, Porta, Roser, Demestre, Xavier, Nadal, Silvia Martínez, de Frutos Martínez, Cristina, López Cuesta, María Jesús, Mora, Dolores Esquivel, Tardío, Joaquín Ortiz, Benavente, Isabel, Alonso, Almudena, Olmos, Ramón Aguilera, García Cabezas, Miguel A., Jiménez, M<ce:sup loc='post">a</ce:sup> Dolores Martínez, Caballero, M<ce:sup loc='post">a</ce:sup> Pilar Jaraba, Díaz, M<ce:sup loc='post">a</ce:sup> Dolores Ordoñez, Fagundo, Alberto Trujillo, Canals, Lluis Mayol, García-Muñoz Rodrigo, Fermín, Martí, Lourdes Urquía, Moreno Galdo, María Fernanda, Suazo, José Antonio Hurtado, López, Eduardo Narbona, Fernández, José Uberos, Cortajarena Altuna, Miguel A., Zuriarrain, Oihana Muga, Navarro, David Mora, Domínguez, María Teresa, Ruiz del Prado, M<ce:sup loc='post">a</ce:sup> Yolanda, Díez, Inés Esteban, Palau Benavides, María Teresa, Lapeña, Santiago, Prada, Teresa, Mir, Eduard Soler, Sánchez, Araceli Corredera, Vega, Enrique Criado, Prado, Náyade del, Fernández, Cristina, Vilaplana, Lucía Cabanillas, Pérez, Irene Cuadrado, Gómez, Luisa López, Comeche, Laura Domingo, Martín, Isabel Llana, Armengod, Carmen González, Labián, Carmen Muñoz, Muñoz, M<ce:sup loc='post">a</ce:sup> José Santos, Bravo, Dorotea Blanco, Pérez, Vicente, Fernández, M<ce:sup loc='post">a</ce:sup> Dolores Elorza, González, Celia Díaz, Segura, Susana Ares, Azorín, Manuela López, Jimenez, Ana Belén, Sánchez-Tamayo, Tomás, Moreno, Elías Tapia, González, María, Sánchez Martínez, José Enrique, Lloreda García, José María, Orayen, Concepción Goñi, González, Javier Vilas, Albo, María Suárez, Colmenero, Eva González, Gutiérrez González, Elena Pilar, Vacas del Arco, Beatriz, Fernández, Josefina Márquez, Gordillo, Laura Acosta, Asensio, Mercedes Granero, Díaz, Carmen Macías, Albújar, Mar, Jorge, Pedro Fuster, Romero, Sabina, Falero, Mónica Rivero, Escobar Izquierdo, Ana Belén, Capell, Javier Estañ, Macián, M<ce:sup loc='post">a</ce:sup> Isabel Izquierdo, Vicente, M<ce:sup loc='post">a</ce:sup> Mar Montejo, Caballero, Raquel Izquierdo, Martínez, M<ce:sup loc='post">a</ce:sup> Mercedes, Euba, Aintzane, Serna, Amaya Rodríguez, López de Heredia Goya, Juan María, Legorburu, Alberto Pérez, Amorós, Ana Gutiérrez, Marugán Isabel, Víctor Manuel, González, Natalio Hernández, Gracia, Segundo Rite, Faci, M<ce:sup loc='post">a</ce:sup> Purificación Ventura, Villagrasa, M<ce:sup loc='post">a</ce:sup> Pilar Samper, Kofron, Jiri, Brodd, Katarina Strand, Odlind, Andreas, Alberg, Lars, Arwehed, Sofia, Hafström, Ola, Kasemo, Anna, Nederman, Karin, Åhman, Lars, Ingemarsson, Fredrik, Petersson, Henrik, Thurn, Pernilla, Albinsson, Eva, Selander, Bo, Abrahamsson, Thomas, Heimdahl, Ingela, Sveinsdottir, Kristbjorg, Wejryd, Erik, Hedlund, Anna, Söderberg, Maria Katarina, Navér, Lars, Brune, Thomas, Bäckström, Jens, Robinson, Johan, Farooqi, Aijaz, Normann, Erik, Fredriksson, Magnus, Palm, Anders, Rosenqvist, Urban, Walde, Bengt, Hagman, Cecilia, Ohlin, Andreas, Florell, Rein, Smedsaas-Löfvenberg, Agneta, Adams, Mark, Meyer, Philipp, Kusche, Rachel, Schulzke, Sven, Nelle, Mathias, Wagner, Bendicht, Riedel, Thomas, Kaczala, Grégoire, Pfister, Riccardo E., Tolsa, Jean-François, Roth, Matthias, Stocker, Martin, Laubscher, Bernhard, Malzacher, Andreas, Micallef, John P., Hegi, Lukas, Bassler, Dirk, Arlettaz, Romaine, Bernet, Vera, Dani, Carlo, Fiorini, Patrizio, Ghirri, Paolo, Tomasini, Barbara, Mittal, Anita, Kefas, Jonathan, Kamalanathan, Anand, Grosdenier, Michael, Dewhurst, Christopher, Bontea, Andreea, Webb, Delyth, Garr, Ross, Hassan, Ahmed, Ambadkar, Priyadarshan, Dyke, Mark, McDevitt, Katharine, Rewitzky, Glynis, D'Amore, Angela, Kamath, P., Settle, Paul, Maddock, Natasha, Edi-Osagie, Ngozi, Zipitis, Christos, Heal, Carrie, Birch, Jacqeline, Hasib, Abdul, Soe, Aung, Abdul-Malik, Bushra, Kisat, Hamudi, Vasu, Vimal, Sivashankar, Savi, Gupta, Richa, Rawlingson, Chris, Wickham, Tim, Theron, Marice, Kendall, Giles, Gupta, Aashish, Aladangady, Narendra, Ali, Imdad, Jain, Neeraj, Mannan, Khalid, Murthy, Vadivelam, Sullivan, Caroline, Chuang, Shu-Ling, Bate, Tristan, Tyszcuzk, Lidia, Lee, Geraint, Obi, Ozioma, Chang, John, Pai, Vinay, Huddy, Charlotte, Yasin, Salim, Nicholl, Richard, Pandey, Poornima, Cusack, Jonathan, Kairamkonda, Venkatesh, Muogbo, Dominic, Harry, Liza, Surana, Pinki, Broggio, Penny, Pillay, Tilly, Deshpande, Sanjeev, Mahadevan, Moore, Alison, Bastani, Porus, Garbash, Mehdi, Lal, Mithilesh, Abu-Harb, Majd, Allwood, Alex, Selter, Michael, Munyard, Paul, Bartle, David, Paul, Siba, Whincup, Graham, Rekha, Sanghavi, Amess, Philip, Obi, Ben, Reynolds, Peter, Misra, Indranil, De Halpert, Peter, Salgia, Sanjay, Sanghavi, Rekha, Paul, Nicola, Deketelaere, Abby, Khashu, Minesh, Johnson, Mark, Groves, Charlotte, Baird, Jim, Brennan, Nick, Vamvakiti, Katia, McIntyre, John, Holman, Jennifer, Jones, Stephen, Pike, Alison, Cairns, Pamela, Eaton, Megan, Schwarz, Karin, Gibson, David, Miall, Lawrence, Krishnamurthy, Dr, Narayanan, Sankara, Seaton, Sarah E., Draper, Elizabeth S., Kusuda, Satoshi, Håkansson, Stellan, Helenius, Kjell, Reichman, Brian, Vento, Maximo, Darlow, Brian A., Rusconi, Franca, Isayama, Tetsuya, Norman, Mikael, Yang, Junmin, and Modi, Neena

Published
2021
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41. Mathematical Foundations of the GraphBLAS

Author

Kepner, Jeremy, Aaltonen, Peter, Bader, David, Buluc, Aydın, Franchetti, Franz, Gilbert, John, Hutchison, Dylan, Kumar, Manoj, Lumsdaine, Andrew, Meyerhenke, Henning, McMillan, Scott, Moreira, Jose, Owens, John D., Yang, Carl, Zalewski, Marcin, and Mattson, Timothy

Subjects
Computer Science - Mathematical Software, Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Data Structures and Algorithms
Abstract

The GraphBLAS standard (GraphBlas.org) is being developed to bring the potential of matrix based graph algorithms to the broadest possible audience. Mathematically the Graph- BLAS defines a core set of matrix-based graph operations that can be used to implement a wide class of graph algorithms in a wide range of programming environments. This paper provides an introduction to the mathematics of the GraphBLAS. Graphs represent connections between vertices with edges. Matrices can represent a wide range of graphs using adjacency matrices or incidence matrices. Adjacency matrices are often easier to analyze while incidence matrices are often better for representing data. Fortunately, the two are easily connected by matrix mul- tiplication. A key feature of matrix mathematics is that a very small number of matrix operations can be used to manipulate a very wide range of graphs. This composability of small number of operations is the foundation of the GraphBLAS. A standard such as the GraphBLAS can only be effective if it has low performance overhead. Performance measurements of prototype GraphBLAS implementations indicate that the overhead is low., Comment: 9 pages; 11 figures; accepted to IEEE High Performance Extreme Computing (HPEC) conference 2016. arXiv admin note: text overlap with arXiv:1504.01039

Published
2016
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42. Spectral Partitioning with Blends of Eigenvectors

Author

Fairbanks, James P., Sanders, Geoffrey D., and Bader, David A.

Subjects
Computer Science - Numerical Analysis
Abstract

Many common methods for data analysis rely on linear algebra. We provide new results connecting data analysis error to numerical accuracy, which leads to the first meaningful stopping criterion for two way spectral partitioning. More generally, we provide pointwise convergence guarantees so that blends (linear combinations) of eigenvectors can be employed to solve data analysis problems with confidence in their accuracy. We demonstrate this theory on an accessible model problem, the Ring of Cliques, by deriving the relevant eigenpairs and comparing the predicted results to numerical solutions. These results bridge the gap between linear algebra based data analysis methods and the convergence theory of iterative approximation methods., Comment: 32 pages, 7 figures, 1 table

Published
2015

43. Bioinformatics

Author

Andreas D. Baxevanis, Gary D. Bader, David S. Wishart, Andreas D. Baxevanis, Gary D. Bader, David S. Wishart and Andreas D. Baxevanis, Gary D. Bader, David S. Wishart, Andreas D. Baxevanis, Gary D. Bader, David S. Wishart

Published
2020

44. Graphs, Matrices, and the GraphBLAS: Seven Good Reasons

Author

Kepner, Jeremy, Bader, David, Buluc, Aydın, Gilbert, John, Mattson, Timothy, and Meyerhenke, Henning

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

The analysis of graphs has become increasingly important to a wide range of applications. Graph analysis presents a number of unique challenges in the areas of (1) software complexity, (2) data complexity, (3) security, (4) mathematical complexity, (5) theoretical analysis, (6) serial performance, and (7) parallel performance. Implementing graph algorithms using matrix-based approaches provides a number of promising solutions to these challenges. The GraphBLAS standard (istc-bigdata.org/GraphBlas) is being developed to bring the potential of matrix based graph algorithms to the broadest possible audience. The GraphBLAS mathematically defines a core set of matrix-based graph operations that can be used to implement a wide class of graph algorithms in a wide range of programming environments. This paper provides an introduction to the GraphBLAS and describes how the GraphBLAS can be used to address many of the challenges associated with analysis of graphs., Comment: 10 pages; International Conference on Computational Science workshop on the Applications of Matrix Computational Methods in the Analysis of Modern Data

Published
2015
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45. Redefining Professional Learning for Museum Education

Author

Tran, Lynn Uyen, Gupta, Preeti, and Bader, David

Abstract

It is through the collective work of museum educators that an organization grows its social capital in its local community and beyond its physical footprint. Given the significant contributions of museum educators to an institution's outcomes, we argue for a shift in mindset on investing in their growth and development. We share our reasoning for this change through our experiences from the "Reflecting on Practice" program. Two leaders in our community offer their reflections on why they took this leap of faith and the outcomes 5-10 years since their first step.

Published
2019
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46. Standards for Graph Algorithm Primitives

Author

Mattson, Tim, Bader, David, Berry, Jon, Buluc, Aydin, Dongarra, Jack, Faloutsos, Christos, Feo, John, Gilbert, John, Gonzalez, Joseph, Hendrickson, Bruce, Kepner, Jeremy, Leiserson, Charles, Lumsdaine, Andrew, Padua, David, Poole, Stephen, Reinhardt, Steve, Stonebraker, Mike, Wallach, Steve, and Yoo, Andrew

Subjects
Computer Science - Mathematical Software, Computer Science - Discrete Mathematics, Computer Science - Data Structures and Algorithms
Abstract

It is our view that the state of the art in constructing a large collection of graph algorithms in terms of linear algebraic operations is mature enough to support the emergence of a standard set of primitive building blocks. This paper is a position paper defining the problem and announcing our intention to launch an open effort to define this standard., Comment: 2 pages, IEEE HPEC 2013

Published
2014
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47. High-Performance Phylogenetic Inference

Author

Bader, David A., Madduri, Kamesh, Crippen, Gordon, Advisory Editor, Dress, Andreas, Editor-in-Chief, Giegerich, Robert, Editorial Board Member, Kelso, Janet, Editorial Board Member, Linial, Michal, Editor-in-Chief, Felsenstein, Joe, Advisory Editor, Troyanskaya, Olga, Editor-in-Chief, Gusfield, Dan, Advisory Editor, Myers, Gene, Editorial Board Member, Istrail, Sorin, Advisory Editor, Pevzner, Pavel, Editorial Board Member, Vingron, Martin, Editor-in-Chief, Lengauer, Thomas, Advisory Editor, McClure, Marcella, Advisory Editor, Nowak, Martin, Advisory Editor, Sankoff, David, Advisory Editor, Shamir, Ron, Advisory Editor, Steel, Mike, Advisory Editor, Stormo, Gary, Advisory Editor, Tavaré, Simon, Advisory Editor, Warnow, Tandy, Advisory Editor, and Welch, Lonnie, Advisory Editor

Published
2019
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48. Prostate Cancer Energetics and Biosynthesis

Author

Lin, Chenchu, Salzillo, Travis C., Bader, David A., Wilkenfeld, Sandi R., Awad, Dominik, Pulliam, Thomas L., Dutta, Prasanta, Pudakalakatti, Shivanand, Titus, Mark, McGuire, Sean E., Bhattacharya, Pratip K., Frigo, Daniel E., Crusio, Wim E., Series Editor, Lambris, John D., Series Editor, Rezaei, Nima, Series Editor, Dehm, Scott M., editor, and Tindall, Donald J., editor

Published
2019
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49. Neonatal Intensive Care Unit-Level Patent Ductus Arteriosus Treatment Rates and Outcomes in Infants Born Extremely Preterm

Author

Harrison, Adele, Synnes, Anne, Ting, Joseph, Cieslak, Zenon, Sherlock, Rebecca, Yee, Wendy, Aziz, Khalid, Toye, Jennifer, Fajardo, Carlos, Kalapesi, Zarin, Sankaran, Koravangattu, Daspal, Sibasis, Seshia, Mary, Alvaro, Ruben, Mukerji, Amit, Da Silva, Orlando, Nwaesei, Chuks, Lee, Kyong-Soon, Dunn, Michael, Lemyre, Brigitte, Dow, Kimberly, Pelausa, Ermelinda, Barrington, Keith, Drolet, Christine, Piedboeuf, Bruno, Claveau, Martine, Beltempo, Marc, Bertelle, Valerie, Masse, Edith, Canning, Roderick, Makary, Hala, Ojah, Cecil, Monterrosa, Luis, Deshpandey, Akhil, Afifi, Jehier, Kajetanowicz, Andrzej, Andersson, Sture, Tammela, Outi, Sankilampi, Ulla, Saarela, Timo, Heymann, Eli, Zangen, Shmuel, Smolkin, Tatyana, Mimouni, Francis, Bader, David, Rothschild, Avi, Strauss, Zipora, Felszer, Clari, Omari, Hussam, Tov-Friedman, Smadar Even, Bar-Oz, Benjamin, Feldman, Michael, Saad, Nizar, Flidel-Rimon, Orna, Weisbrod, Meir, Lubin, Daniel, Litmanovitz, Ita, Kugelman, Amir, Shinwell, Eric, Klinger, Gil, Nijim, Yousif, Bin-Nun, Alona, Golan, Agneta, Mandel, Dror, Fleisher-Sheffer, Vered, Kohelet, David, Bakhrakh, Lev, Hattori, Satoshi, Shirai, Masaru, Ishioka, Toru, Mori, Toshihiko, Amizuka, Takasuke, Huchimukai, Toru, Yoshida, Hiroshi, Sasaki, Ayako, Shimizu, Junichi, Nakamura, Toshihiko, Maruyama, Mami, Matsumoto, Hiroshi, Hosokawa, Shinichi, Taki, Atsuko, Nakagawa, Machiko, Ko, Kyone, Uozumi, Azusa, Nakata, Setsuko, Shimazaki, Akira, Yoda, Tatsuya, Numata, Osamu, Imamura, Hiroaki, Kobayashi, Azusa, Tokuriki, Shuko, Uchida, Yasushi, Arai, Takahiro, Ito, Mitsuhiro, Ieda, Kuniko, Ono, Toshiyuki, Hayashi, Masashi, Maki, Kanemasa, Yamakawa, Mie- Toru, Kawai, Masahiko, Fujii, Noriko, Shiomi, Kozue, Nozaki, Koji, Wada, Hiroshi, Kim, Taho, Tokunaga, Yasuyuki, Takatera, Akihiro, Oshima, Toshio, Sumida, Hiroshi, Michinomae, Yae, Kusumoto, Yoshio, Yoshimoto, Seiji, Morisawa, Takeshi, Ohashi, Tamaki, Takahashi, Yukihiro, Sugimoto, Moriharu, Ono, Noriaki, Miyagawa, Shinichiro, Saijo, Takahiko, Yamagami, Takashi, Koyano, Kosuke, Kobayashi, Shoko, Kanda, Takeshi, Sakemi, Yoshihiro, Aoki, Mikio, Iida, Koichi, Goshi, Mitsushi, Maruyama, Yuko, Kofron, Jiri, Brodd, Katarina Strand, Odlind, Andreas, Alberg, Lars, Arwehed, Sofia, Hafström, Ola, Kasemo, Anna, Nederman, Karin, Åhman, Lars, Ingemarsson, Fredrik, Petersson, Henrik, Thurn, Pernilla, Albinsson, Eva, Selander, Bo, Abrahamsson, Thomas, Heimdahl, Ingela, Sveinsdottir, Kristbjorg, Wejryd, Erik, Hedlund, Anna, Söderberg, Maria Katarina, Navér, Lars, Brune, Thomas, Bäckström, Jens, Robinson, Johan, Farooqi, Aijaz, Normann, Erik, Fredriksson, Magnus, Palm, Anders, Rosenqvist, Urban, Walde, Bengt, Hagman, Cecilia, Ohlin, Andreas, Florell, Rein, Löfvenberg, Agneta Smedsaas, Meyer, Philipp, Kusche, Rachel, Schulzke, Sven, Nelle, Mathias, Wagner, Bendicht, Riedel, Thomas, Kaczala, Grégoire, Pfister, Riccardo E., Tolsa, Jean-François, Roth, Matthias, Stocker, Martin, Laubscher, Bernhard, Malzacher, Andreas, Micallef, John P., Hegi, Lukas, Arlettaz, Romaine, Bernet, Vera, Isayama, Tetsuya, Kusuda, Satoshi, Reichman, Brian, Lee, Shoo K., Lehtonen, Liisa, Norman, Mikael, Adams, Mark, Bassler, Dirk, Helenius, Kjell, Hakansson, Stellan, Yang, Junmin, Jain, Amish, and Shah, Prakesh S.

Published
2020
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50. Inhibition of the hexosamine biosynthetic pathway promotes castration-resistant prostate cancer.

Author

Kaushik, Akash, Shojaie, Ali, Panzitt, Katrin, Sonavane, Rajni, Venghatakrishnan, Harene, Manikkam, Mohan, Zaslavsky, Alexander, Putluri, Vasanta, Vasu, Vihas, Zhang, Yiqing, Khan, Ayesha, Lloyd, Stacy, Szafran, Adam, Dasgupta, Subhamoy, Bader, David, Stossi, Fabio, Li, Hangwen, Samanta, Susmita, Cao, Xuhong, Tsouko, Efrosini, Huang, Shixia, Frigo, Daniel, Chan, Lawrence, Edwards, Dean, Kaipparettu, Benny, Mitsiades, Nicholas, Weigel, Nancy, Mancini, Michael, McGuire, Sean, Mehra, Rohit, Ittmann, Michael, Chinnaiyan, Arul, Putluri, Nagireddy, Palapattu, Ganesh, Michailidis, George, and Sreekumar, Arun

Subjects
Animals, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, Cell Line, Hexosamines, Humans, Male, Mice, Mice, SCID, Phosphatidylinositol 3-Kinases, Prostatic Neoplasms, Castration-Resistant, Proto-Oncogene Proteins c-akt
Abstract

The precise molecular alterations driving castration-resistant prostate cancer (CRPC) are not clearly understood. Using a novel network-based integrative approach, here, we show distinct alterations in the hexosamine biosynthetic pathway (HBP) to be critical for CRPC. Expression of HBP enzyme glucosamine-phosphate N-acetyltransferase 1 (GNPNAT1) is found to be significantly decreased in CRPC compared with localized prostate cancer (PCa). Genetic loss-of-function of GNPNAT1 in CRPC-like cells increases proliferation and aggressiveness, in vitro and in vivo. This is mediated by either activation of the PI3K-AKT pathway in cells expressing full-length androgen receptor (AR) or by specific protein 1 (SP1)-regulated expression of carbohydrate response element-binding protein (ChREBP) in cells containing AR-V7 variant. Strikingly, addition of the HBP metabolite UDP-N-acetylglucosamine (UDP-GlcNAc) to CRPC-like cells significantly decreases cell proliferation, both in-vitro and in animal studies, while also demonstrates additive efficacy when combined with enzalutamide in-vitro. These observations demonstrate the therapeutic value of targeting HBP in CRPC.

Published
2016

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