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2,602 results on '"J. Kowalski"'

1. OpenFOAM-avalanche 2312: depth-integrated models beyond dense-flow avalanches

Author

M. Rauter and J. Kowalski

Subjects
Geology, QE1-996.5
Abstract

Numerical simulations have become an important tool for the estimation and mitigation of gravitational mass flows, such as avalanches, landslides, pyroclastic flows, and turbidity currents. Depth integration stands as a pivotal concept in rendering numerical models applicable to real-world scenarios, as it provides the required efficiency and a streamlined workflow for geographic information systems. In recent years, a large number of flow models were developed following the idea of depth integration, thereby enlarging the applicability and reliability of this family of process models substantially. It has been previously shown that the finite area method of OpenFOAM® can be utilized to express and solve the basic depth-integrated models representing incompressible dense flows. In this article, previous work (Rauter et al., 2018) is extended beyond the dense-flow regime to account for suspended particle flows, such as turbidity currents and powder snow avalanches. A novel coupling mechanism is introduced to enhance the simulation capabilities for mixed-snow avalanches. Further, we will give an updated description of the revised computational framework, its integration into OpenFOAM, and interfaces to geographic information systems. This work aims to provide practitioners and scientists with an open-source tool that facilitates transparency and reproducibility and that can be easily applied to real-world scenarios. The tool can be used as a baseline for further developments and in particular allows for modular integration of customized process models.

Published
2024
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2. Global, high-resolution mapping of tropospheric ozone – explainable machine learning and impact of uncertainties

Author

C. Betancourt, T. T. Stomberg, A.-K. Edrich, A. Patnala, M. G. Schultz, R. Roscher, J. Kowalski, and S. Stadtler

Subjects
Geology, QE1-996.5
Abstract

Tropospheric ozone is a toxic greenhouse gas with a highly variable spatial distribution which is challenging to map on a global scale. Here, we present a data-driven ozone-mapping workflow generating a transparent and reliable product. We map the global distribution of tropospheric ozone from sparse, irregularly placed measurement stations to a high-resolution regular grid using machine learning methods. The produced map contains the average tropospheric ozone concentration of the years 2010–2014 with a resolution of 0.1∘ × 0.1∘. The machine learning model is trained on AQ-Bench (“air quality benchmark dataset”), a pre-compiled benchmark dataset consisting of multi-year ground-based ozone measurements combined with an abundance of high-resolution geospatial data. Going beyond standard mapping methods, this work focuses on two key aspects to increase the integrity of the produced map. Using explainable machine learning methods, we ensure that the trained machine learning model is consistent with commonly accepted knowledge about tropospheric ozone. To assess the impact of data and model uncertainties on our ozone map, we show that the machine learning model is robust against typical fluctuations in ozone values and geospatial data. By inspecting the input features, we ensure that the model is only applied in regions where it is reliable. We provide a rationale for the tools we use to conduct a thorough global analysis. The methods presented here can thus be easily transferred to other mapping applications to ensure the transparency and reliability of the maps produced.

Published
2022
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3. Elements of future snowpack modeling – Part 1: A physical instability arising from the nonlinear coupling of transport and phase changes

Author

K. Schürholt, J. Kowalski, and H. Löwe

Subjects
Environmental sciences, GE1-350, Geology, QE1-996.5
Abstract

The incorporation of vapor transport has become a key demand for snowpack modeling in which accompanied phase changes give rise to a new, nonlinear coupling in the heat and mass equations. This coupling has an impact on choosing efficient numerical schemes for 1D snowpack models which are naturally not designed to cope with mathematical particularities of arbitrary, nonlinear partial differential equations (PDEs). To explore this coupling we have implemented a stand-alone finite element solution of the coupled heat and mass equations in snow using the computing platform FEniCS. We focus on the nonlinear feedback of the ice phase exchanging mass with a diffusing vapor phase with concurrent heat transport in the absence of settling. We demonstrate that existing continuum-mechanical models derived through homogenization or mixture theory yield similar results for homogeneous snowpacks of constant density. When snow density varies significantly with depth, we show that phase changes in the presence of temperature gradients give rise to nonlinear advection of the ice phase amplifying existing density variations. Eventually, this advection triggers a wave instability in the continuity equations. This is traced back to the density dependence of the effective transport coefficients as revealed by a linear stability analysis of the nonlinear PDE system. The instability is an inherent feature of existing continuum models and predicts, as a side product, the formation of a low-density (mechanical) weak layer on the sublimating side of an ice crust. The wave instability constitutes a key challenge for a faithful treatment of solid–vapor mass conservation between layers, which is discussed in view of the underlying homogenization schemes and their numerical solutions.

Published
2022
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4. Elements of future snowpack modeling – Part 2: A modular and extendable Eulerian–Lagrangian numerical scheme for coupled transport, phase changes and settling processes

Author

A. Simson, H. Löwe, and J. Kowalski

Subjects
Environmental sciences, GE1-350, Geology, QE1-996.5
Abstract

A coupled treatment of transport processes, phase changes and mechanical settling is the core of any detailed snowpack model. A key concept underlying the majority of these models is the notion of layers as deforming material elements that carry the information on their physical state. Thereby an explicit numerical solution of the ice mass continuity equation can be circumvented, although with the downside of virtual no flexibility in implementing different coupling schemes for densification, phase changes and transport. As a remedy we consistently recast the numerical core of a snowpack model into an extendable Eulerian–Lagrangian framework for solving the coupled non-linear processes. In the proposed scheme, we explicitly solve the most general form of the ice mass balance using the method of characteristics, a Lagrangian method. The underlying coordinate transformation is employed to state a finite-difference formulation for the superimposed (vapor and heat) transport equations which are treated in their Eulerian form on a moving, spatially non-uniform grid that includes the snow surface as a free upper boundary. This formulation allows us to unify the different existing viewpoints of densification in snow or firn models in a flexible way and yields a stable coupling of the advection-dominated mechanical settling with the remaining equations. The flexibility of the scheme is demonstrated within several numerical experiments using a modular solver strategy. We focus on emerging heterogeneities in (two-layer) snowpacks, the coupling of (solid–vapor) phase changes with settling at layer interfaces and the impact of switching to a non-linear mechanical constitutive law. Lastly, we discuss the potential of the scheme for extensions like a dynamical equation for the surface mass balance or the coupling to liquid water flow.

Published
2021
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5. Topographic uncertainty quantification for flow-like landslide models via stochastic simulations

Author

H. Zhao and J. Kowalski

Subjects
Environmental technology. Sanitary engineering, TD1-1066, Geography. Anthropology. Recreation, Environmental sciences, GE1-350, Geology, QE1-996.5
Abstract

Digital elevation models (DEMs) representing topography are an essential input for computational models capable of simulating the run-out of flow-like landslides. Yet, DEMs are often subject to error, a fact that is mostly overlooked in landslide modeling. We address this research gap and investigate the impact of topographic uncertainty on landslide run-out models. In particular, we will describe two different approaches to account for DEM uncertainty, namely unconditional and conditional stochastic simulation methods. We investigate and discuss their feasibility, as well as whether DEM uncertainty represented by stochastic simulations critically affects landslide run-out simulations. Based upon a historic flow-like landslide event in Hong Kong, we present a series of computational scenarios to compare both methods using our modular Python-based workflow. Our results show that DEM uncertainty can significantly affect simulation-based landslide run-out analyses, depending on how well the underlying flow path is captured by the DEM, as well as on further topographic characteristics and the DEM error's variability. We further find that, in the absence of systematic bias in the DEM, a performant root-mean-square-error-based unconditional stochastic simulation yields similar results to a computationally intensive conditional stochastic simulation that takes actual DEM error values at reference locations into account. In all other cases the unconditional stochastic simulation overestimates the variability in the DEM error, which leads to an increase in the potential hazard area as well as extreme values of dynamic flow properties.

Published
2020
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6. Galactic Cosmic Radiation Induces Persistent Epigenome Alterations Relevant to Human Lung Cancer

Author

E. M. Kennedy, D. R. Powell, Z. Li, J. S. K. Bell, B. G. Barwick, H. Feng, M. R. McCrary, B. Dwivedi, J. Kowalski, W. S. Dynan, K. N. Conneely, and P. M. Vertino

Subjects
Medicine, Science
Abstract

Abstract Human deep space and planetary travel is limited by uncertainties regarding the health risks associated with exposure to galactic cosmic radiation (GCR), and in particular the high linear energy transfer (LET), heavy ion component. Here we assessed the impact of two high-LET ions 56Fe and 28Si, and low-LET X rays on genome-wide methylation patterns in human bronchial epithelial cells. We found that all three radiation types induced rapid and stable changes in DNA methylation but at distinct subsets of CpG sites affecting different chromatin compartments. The 56Fe ions induced mostly hypermethylation, and primarily affected sites in open chromatin regions including enhancers, promoters and the edges (“shores”) of CpG islands. The 28Si ion-exposure had mixed effects, inducing both hyper and hypomethylation and affecting sites in more repressed heterochromatic environments, whereas X rays induced mostly hypomethylation, primarily at sites in gene bodies and intergenic regions. Significantly, the methylation status of 56Fe ion sensitive sites, but not those affected by X ray or 28Si ions, discriminated tumor from normal tissue for human lung adenocarcinomas and squamous cell carcinomas. Thus, high-LET radiation exposure leaves a lasting imprint on the epigenome, and affects sites relevant to human lung cancer. These methylation signatures may prove useful in monitoring the cumulative biological impact and associated cancer risks encountered by astronauts in deep space.

Published
2018
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7. Image-guided genomics of phenotypically heterogeneous populations reveals vascular signalling during symbiotic collective cancer invasion

Author

J. Konen, E. Summerbell, B. Dwivedi, K. Galior, Y. Hou, L. Rusnak, A. Chen, J. Saltz, W. Zhou, L. H. Boise, P. Vertino, L. Cooper, K. Salaita, J. Kowalski, and A. I. Marcus

Subjects
Science
Abstract

The mechanisms linking phenotypic heterogeneity to collective cancer invasion are unclear. Here the authors develop an image-guided genomic technique to select and amplify leader and follower cells fromin vitroinvading cell packs and find a cooperative symbiotic relationship between these two cell populations.

Published
2017
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8. Quantum ergosphere and brick wall entropy

Author

M. Arzano, L. Brocki, J. Kowalski-Glikman, M. Letizia, and J. Unger

Subjects
Physics, QC1-999
Abstract

We revisit the “brick wall” model for black hole entropy taking into account backreaction effects on the horizon structure. We do so by adopting an evaporating metric in the quasi-static approximation in which departures from the standard Schwarzschild metric are governed by a small luminosity factor. One of the effects of the backreaction is to create an ergosphere-like region which naturally tames the usual divergence in the calculation of the partition function of the field. The black hole luminosity sets the width of such ‘quantum ergosphere’. We find a finite horizon contribution to the entropy which, for the luminosity associated to the Hawking flux, reproduces remarkably well the Bekenstein-Hawking entropy-area law.

Published
2019
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9. Rozkład naprężeń mechanicznych w łyżce o szerokości 500 mm, przeznaczonej do koparki podsiębiernej

Author

A. Lesnau and J. Kowalski

Subjects
analiza MES, łyżka koparki podsiębiernej, konstrukcja, wytrzymałość, naprężenia, Naval architecture. Shipbuilding. Marine engineering, VM1-989, Technology
Abstract

W artykule zaprezentowano optymalizację kształtu łyżki koparki przed­siębiernej z wykorzystaniem analizy wytrzymałościowej. Analizę oparto na trójwymiarowym modelu konstrukcji łyżki z zastosowaniem metody elementów skończonych (MES). Opracowanie wspomnianej metody pozwoliło na modyfikację konstrukcji łyżki, która dała w efekcie obniżenie naprężeń złożonych w newralgicznych obszarach konstrukcji łyżki. Przedstawiona analiza okazała się prostym i relatywnie tanim sposobem optymalizacji konstrukcji mechanicznych o złożonych kształtach już na etapie projektowania.

Published
2018
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11. Diseño optimo multiobjetivo de procesos de maquinado

Author

J. Kowalski and C. Díaz P.

Subjects
Mechanical engineering and machinery, TJ1-1570
Abstract

En el presente artículo se muestra la implementación del análisis de tendencia, como tecnología predictiva, a través de laestadística matemática y su utilización en mediciones de parámetros de diagnóstico tanto espectral como de nivel total. Elempleo de esta tecnología resulta de gran importancia debido a que permite pronosticar el momento de fallo, según elcomportamiento de los niveles de los parámetros medidos, lo cual facilita la gestión del mantenimiento.Palabras claves: Diseño optimo, optimización multiobjetivo, procesos de maquinado.

Published
2000

13. Internetowy Atlas Polski Niepodległej – metodyka opracowania bazy miejscowości i granic administracyjnych oraz analizy pochodne

Author

Andrzej Głażewski and Paweł J. Kowalski

Subjects
Modeling and Simulation
Abstract

Artykuł przedstawia przykłady wykorzystania zasobu historycznych danych przestrzennych, zgromadzonego w ramach Internetowego Atlasu Polski Niepodległej, opublikowanego w 2021 r. jako efekt projektu Instytutu Historii PAN i Wydziału Geodezji i Kartografii Politechniki Warszawskiej. Zasadniczym celem artykułu jest ukazanie możliwości badania struktury sieci osadniczej z wykorzystaniem analiz przestrzennych oraz propozycja sposobów odtwarzania metodami kartograficznymi struktur przestrzennych: grup obiektów osadniczych czy jednostek administracyjnych.

Published
2023

14. The Impact of Covid-19 Pandemic on Value Migration Processes in the Real Estate Sector

Author

Michał J. Kowalski, Tong Wang, and Jan K. Kazak

Subjects
real estate market, value migration, COVID-19
Abstract

The COVID-19 pandemic period brings huge uncertainty, especially for the real estate sector. On the one hand, restrictions on the mobility of a population, decline in travel demands, popularization of remote work and education models caused doubts among investors questioning the future of the sector and the functions of real estate. On the other hand, the large supply of cash after the first waves of the pandemic and the upcoming increase in inflation resulted in many investors boldly investing cash in real estate, considering them as assets of stable value. This research aims to analyze the processes of value migration among real estate companies listed on the Warsaw Stock Exchange during this turbulent process. We analyzed the changes in the main drivers of value and the migration rates of the real estate sector based on data for 2018, 2019, 2020 and Q3 2021. The first period of the pandemic is the time of the collapse of the main profitability factors, sales and profitability of sales decline in the entire sector. However, the financial pillars of the analyzed companies are stable and we are not seeing signs of liquidity problems or a significant increase in debt. The second year of the pandemic is a significant reflection of most of the drivers of value, often to levels higher than those observed before the pandemic. Investors seem to remain insensitive to turbulent changes in accounting measures of effectiveness. We observe the relative stability of market measures. The processes of the migration of values from and to the sector do not show significant changes when comparing the periods before and during the pandemic. We observe various intensities of the studied phenomena in various groups of the real estate segment.

Published
2023

18. Black Hole Solution of Quantum Gravity

Author

Glikman, J. Kowalski

Subjects
General Relativity and Quantum Cosmology
Abstract

We present a spherically symmetric and static exact solution of Quantum Einstein Equations. This solution is asymptotically (for large $r$) identical with the black hole solution on the anti--De Sitter background and, for some range of values of the mass possesses two horizons. We investigate thermodynamical properties of this solution., Comment: Plain Latex, 10 pages

Published
1998
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19. Quantum Potential and Quantum Gravity

Author

Glikman, J. Kowalski

Subjects
General Relativity and Quantum Cosmology
Abstract

The quantum potential approach makes it possible to construct a complementary picture of quantum mechanical evolution which reminds classical equation of motion. The only difference as compared to equations of motion for the underlying classical system is the presence of an additional potential term being a functional of the real part of the wavefunction. In the present paper this approach is applied to the quantum theory of gravity based on Wheeler -- De Witt equation. We describe the derivation of the `quantum Einstein equation' and discuss the new features of their solutions., Comment: 12 pages LaTeX, to appear in From Field Theory to Quantum Groups. Birthday volume dedicated to Jerzy Lukierski, World Scientific

Published
1995
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20. Supplemental Figure 9 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Figure S9

Published
2023

21. Data from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Mechanisms driving resistance to cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) in hormone receptor–positive (HR+) breast cancer have not been clearly defined. Whole-exome sequencing of 59 tumors with CDK4/6i exposure revealed multiple candidate resistance mechanisms including RB1 loss, activating alterations in AKT1, RAS, AURKA, CCNE2, ERBB2, and FGFR2, and loss of estrogen receptor expression. In vitro experiments confirmed that these alterations conferred CDK4/6i resistance. Cancer cells cultured to resistance with CDK4/6i also acquired RB1, KRAS, AURKA, or CCNE2 alterations, which conferred sensitivity to AURKA, ERK, or CHEK1 inhibition. Three of these activating alterations—in AKT1, RAS, and AURKA—have not, to our knowledge, been previously demonstrated as mechanisms of resistance to CDK4/6i in breast cancer preclinically or in patient samples. Together, these eight mechanisms were present in 66% of resistant tumors profiled and may define therapeutic opportunities in patients.Significance:We identified eight distinct mechanisms of resistance to CDK4/6i present in 66% of resistant tumors profiled. Most of these have a therapeutic strategy to overcome or prevent resistance in these tumors. Taken together, these findings have critical implications related to the potential utility of precision-based approaches to overcome resistance in many patients with HR+ metastatic breast cancer.This article is highlighted in the In This Issue feature, p. 1079

Published
2023

22. Supplemental Figure 8 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Figure S8

Published
2023

23. Supplemental Figure 5 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Figure S5

Published
2023

24. Supplemental Figure 4 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Figure S4

Published
2023

25. Supplemental Table 1 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Supplemental Table 1

Published
2023

26. Supplemental Figure 7 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Figure S7

Published
2023

27. Supplemental Table 2 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Supplemental Table 2

Published
2023

28. Supplemental Figure 10 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Figure S10

Published
2023

29. Supplemental Table 5 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Supplemental Table 5

Published
2023

30. Supplemental Table 7 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Supplemental Table 7

Published
2023

31. Supplemental Table 4 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Supplemental Table 4

Published
2023

32. Supplemental Figure 3 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Figure S3

Published
2023

33. Supplemental Figure 2 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Figure S2

Published
2023

34. Supplementary Data from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Supplementary material

Published
2023

35. Supplemental Figure 6 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Figure S6

Published
2023

36. Supplemental Table 8 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Supplemental Table 8

Published
2023

37. Supplemental Table 3 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Supplemental Table 3

Published
2023

38. Supplemental Table 6 from The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Author

Nikhil Wagle, Sean G. Buchanan, Nancy U. Lin, Sara M. Tolaney, Eric P. Winer, Levi A. Garraway, Jill D. Kremer, Melissa E. Hughes, Gerald Batist, Quincy S. Chu, Gerard J. Oakley, Patricia S. Smith, John R. Stille, Valerie M. Jansen, Chunping Yu, Xiang S. Ye, Lacey M. Litchfield, Ricardo Martinez, Stephen H. Parsons, Adrienne G. Waks, Utthara Nayar, Kailey J. Kowalski, Karla Helvie, Pingping Mao, Flora Luo, Dewey Kim, Maxwell R. Lloyd, Jorge E. Buendia-Buendia, Gabriela N. Johnson, Xueqian Gong, Ofir Cohen, and Seth A. Wander

Abstract

Supplemental Table 6

Published
2023

39. Supplemental Table 9 from Acquired FGFR and FGF Alterations Confer Resistance to Estrogen Receptor (ER) Targeted Therapy in ER+ Metastatic Breast Cancer

Author

Nikhil Wagle, Nancy U. Lin, Eric P. Winer, Aviv Regev, David E. Root, Federica Piccioni, Vincent A. Miller, Orit Rozenblatt-Rosen, Samuel Freeman, Jon Chung, Utthara Nayar, Adrienne G. Waks, Seth A. Wander, Pedro Exman, Michael S. Cuoco, Jorge E. Buendia-Buendia, Justin G. Kusiel, Kailey J. Kowalski, Ofir Cohen, and Pingping Mao

Abstract

RNA-seq experiment conditions and QC stats

Published
2023

40. Supplemental Table 12 from Acquired FGFR and FGF Alterations Confer Resistance to Estrogen Receptor (ER) Targeted Therapy in ER+ Metastatic Breast Cancer

Author

Nikhil Wagle, Nancy U. Lin, Eric P. Winer, Aviv Regev, David E. Root, Federica Piccioni, Vincent A. Miller, Orit Rozenblatt-Rosen, Samuel Freeman, Jon Chung, Utthara Nayar, Adrienne G. Waks, Seth A. Wander, Pedro Exman, Michael S. Cuoco, Jorge E. Buendia-Buendia, Justin G. Kusiel, Kailey J. Kowalski, Ofir Cohen, and Pingping Mao

Abstract

Gene sets enrichment and associations

Published
2023

41. Supplemental Table 6 from Acquired FGFR and FGF Alterations Confer Resistance to Estrogen Receptor (ER) Targeted Therapy in ER+ Metastatic Breast Cancer

Author

Nikhil Wagle, Nancy U. Lin, Eric P. Winer, Aviv Regev, David E. Root, Federica Piccioni, Vincent A. Miller, Orit Rozenblatt-Rosen, Samuel Freeman, Jon Chung, Utthara Nayar, Adrienne G. Waks, Seth A. Wander, Pedro Exman, Michael S. Cuoco, Jorge E. Buendia-Buendia, Justin G. Kusiel, Kailey J. Kowalski, Ofir Cohen, and Pingping Mao

Abstract

Evolutionary status data

Published
2023

42. Supplemental Table 8 from Acquired FGFR and FGF Alterations Confer Resistance to Estrogen Receptor (ER) Targeted Therapy in ER+ Metastatic Breast Cancer

Author

Nikhil Wagle, Nancy U. Lin, Eric P. Winer, Aviv Regev, David E. Root, Federica Piccioni, Vincent A. Miller, Orit Rozenblatt-Rosen, Samuel Freeman, Jon Chung, Utthara Nayar, Adrienne G. Waks, Seth A. Wander, Pedro Exman, Michael S. Cuoco, Jorge E. Buendia-Buendia, Justin G. Kusiel, Kailey J. Kowalski, Ofir Cohen, and Pingping Mao

Abstract

Foundation Medicine cohort

Published
2023

43. Supplemental Table 2 from Acquired FGFR and FGF Alterations Confer Resistance to Estrogen Receptor (ER) Targeted Therapy in ER+ Metastatic Breast Cancer

Author

Nikhil Wagle, Nancy U. Lin, Eric P. Winer, Aviv Regev, David E. Root, Federica Piccioni, Vincent A. Miller, Orit Rozenblatt-Rosen, Samuel Freeman, Jon Chung, Utthara Nayar, Adrienne G. Waks, Seth A. Wander, Pedro Exman, Michael S. Cuoco, Jorge E. Buendia-Buendia, Justin G. Kusiel, Kailey J. Kowalski, Ofir Cohen, and Pingping Mao

Abstract

GSEA list

Published
2023

44. Supplemental Table 3 from Acquired FGFR and FGF Alterations Confer Resistance to Estrogen Receptor (ER) Targeted Therapy in ER+ Metastatic Breast Cancer

Author

Nikhil Wagle, Nancy U. Lin, Eric P. Winer, Aviv Regev, David E. Root, Federica Piccioni, Vincent A. Miller, Orit Rozenblatt-Rosen, Samuel Freeman, Jon Chung, Utthara Nayar, Adrienne G. Waks, Seth A. Wander, Pedro Exman, Michael S. Cuoco, Jorge E. Buendia-Buendia, Justin G. Kusiel, Kailey J. Kowalski, Ofir Cohen, and Pingping Mao

Abstract

FGFR alterations in different cohorts

Published
2023

45. Supplementary Data from Acquired FGFR and FGF Alterations Confer Resistance to Estrogen Receptor (ER) Targeted Therapy in ER+ Metastatic Breast Cancer

Author

Nikhil Wagle, Nancy U. Lin, Eric P. Winer, Aviv Regev, David E. Root, Federica Piccioni, Vincent A. Miller, Orit Rozenblatt-Rosen, Samuel Freeman, Jon Chung, Utthara Nayar, Adrienne G. Waks, Seth A. Wander, Pedro Exman, Michael S. Cuoco, Jorge E. Buendia-Buendia, Justin G. Kusiel, Kailey J. Kowalski, Ofir Cohen, and Pingping Mao

Abstract

Supplementary Data from Acquired FGFR and FGF Alterations Confer Resistance to Estrogen Receptor (ER) Targeted Therapy in ER+ Metastatic Breast Cancer

Published
2023

46. Supplemental Table 7 from Acquired FGFR and FGF Alterations Confer Resistance to Estrogen Receptor (ER) Targeted Therapy in ER+ Metastatic Breast Cancer

Author

Nikhil Wagle, Nancy U. Lin, Eric P. Winer, Aviv Regev, David E. Root, Federica Piccioni, Vincent A. Miller, Orit Rozenblatt-Rosen, Samuel Freeman, Jon Chung, Utthara Nayar, Adrienne G. Waks, Seth A. Wander, Pedro Exman, Michael S. Cuoco, Jorge E. Buendia-Buendia, Justin G. Kusiel, Kailey J. Kowalski, Ofir Cohen, and Pingping Mao

Abstract

clinicopathologic info

Published
2023

47. Supplemental Table 5 from Acquired FGFR and FGF Alterations Confer Resistance to Estrogen Receptor (ER) Targeted Therapy in ER+ Metastatic Breast Cancer

Author

Nikhil Wagle, Nancy U. Lin, Eric P. Winer, Aviv Regev, David E. Root, Federica Piccioni, Vincent A. Miller, Orit Rozenblatt-Rosen, Samuel Freeman, Jon Chung, Utthara Nayar, Adrienne G. Waks, Seth A. Wander, Pedro Exman, Michael S. Cuoco, Jorge E. Buendia-Buendia, Justin G. Kusiel, Kailey J. Kowalski, Ofir Cohen, and Pingping Mao

Abstract

Complete exome data

Published
2023

48. Supplemental Table 4 from Acquired FGFR and FGF Alterations Confer Resistance to Estrogen Receptor (ER) Targeted Therapy in ER+ Metastatic Breast Cancer

Author

Nikhil Wagle, Nancy U. Lin, Eric P. Winer, Aviv Regev, David E. Root, Federica Piccioni, Vincent A. Miller, Orit Rozenblatt-Rosen, Samuel Freeman, Jon Chung, Utthara Nayar, Adrienne G. Waks, Seth A. Wander, Pedro Exman, Michael S. Cuoco, Jorge E. Buendia-Buendia, Justin G. Kusiel, Kailey J. Kowalski, Ofir Cohen, and Pingping Mao

Abstract

Biopsy purity and ploidy

Published
2023

49. Ageing Evaluation of Foamed Polymer Modified Bitumen with Bio-Flux Additive

Author

Piotr Radziszewski, Adam Liphardt, Michał Sarnowski, Karol J. Kowalski, Piotr Pokorski, Katarzyna Konieczna, Jan B. Król, Marek Iwański, Anna Chomicz-Kowalska, Krzysztof Maciejewski, Mateusz M. Iwański, and Maciej Michalec

Subjects
General Materials Science, foamed bitumen, fluxing additive, highly modified asphalt binder, ageing, DSR
Abstract

This paper presents the results of an analysis of the changes in the stiffness of asphalt binders modified with a bio-flux additive and subjected to the processes of foaming and short-term ageing. The purpose of the analyses was to determine changes in the rheological properties of asphalt binder as a result of technological processes characteristic of hot and warm mix asphalt technology. Three asphalt binders with similar penetration but varying degrees of polymer modification were tested: 50/70, 45/80–55 polymer-modified bitumen, and 45/80–80 highly modified bitumen. Tests were carried out on four groups of binders: original binders, foamed binders after 14 days of storage, non-foamed binders after Rolling Thin Film Oven Test (RTFOT) ageing, and foamed binders after 14 days of storage subjected to RTFOT ageing. The master curves of the complex shear modulus G* were analysed, and three indexes of binder stiffening were determined, characterising the investigated effects. The tests showed that some of the stiffening indices significantly depended on the degree of polymer modification and the content of the bio-flux additive. Moreover, it was found that the foaming process in the case of paving-grade bitumen and polymer-modified bitumen did not contribute to the additional stiffening of the binders.

Published
2023
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