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Radio-pathomic estimates of cellular growth kinetics predict survival in recurrent glioblastoma

CNS Oncology 2024年第1期13卷 2415285页

作者： Oshima, Sonoko Yao, Jingwen Bobholz, Samuel Nagaraj, Raksha Raymond, Catalina Teraishi, Ashley Guenther, Anna-Marie Kim, Asher Sanvito, Francesco Cho, Nicholas S C Eldred, Blaine S Connelly, Jennifer M Nghiemphu, Phioanh L Lai, Albert Salamon, Noriko Cloughesy, Timothy F LaViolette, Peter S Ellingson, Benjamin M UCLA Brain Tumor Imaging Laboratory (BTIL) Center for Computer Vision & Imaging Biomarkers University of California Los Angeles Los Angeles 90024 CA United States Department of Radiological Sciences David Geffen School of Medicine University of California Los Angeles Los Angeles 90024 CA United States Department of Bioengineering Henry Samueli School of Engineering & Applied Science University of California Los Angeles Los Angeles 90024 CA United States Department of Radiology Medical College of Wisconsin Milwaukee 53226 WI United States Medical Scientist Training Program David Geffen School of Medicine University of California Los Angeles Los Angeles 90024 CA United States UCLA Neuro-Oncology Program David Geffen School of Medicine University of California Los Angeles Los Angeles 90024 CA United States Department of Neurology Medical College of Wisconsin Milwaukee 53226 WI United States Department of Neurology David Geffen School of Medicine University of California Los Angeles Los Angeles 90024 CA United States Department of Biophysics Medical College of Wisconsin Milwaukee 53226 WI United States Department of Biomedical Engineering Medical College of Wisconsin Milwaukee 53226 WI United States Department of Psychiatry & Biobehavioral Sciences David Geffen School of Medicine University of California Los Angeles Los Angeles 90024 CA United States Department of Neurosurgery David Geffen School of Medicine University of California Los Angeles Los Angeles 90024 CA United States

Aim: A radio-pathomic machine learning (ML) model has been developed to estimate tumor cell density, cytoplasm density (Cyt) and extracellular fluid density (ECF) from multimodal MR images and autopsy pathology. In this multicenter study, we implemented this model to test its ability to predict survival in patients with recurrent glioblastoma (rGBM) treated with chemotherapy. Methods: Pre- and post-contrast T₁-weighted, FLAIR and ADC images were used to generate radio-pathomic maps for 51 patients with longitudinal pre- and post-treatment scans. Univariate and multivariate Cox regression analyses were used to test the influence of contrast-enhancing tumor volume, total cellularity, mean Cyt and mean ECF at baseline, immediately post-treatment and the pre- and post-treatment rate of change in volume and cellularity on overall survival (OS). Results: Smaller Cyt and larger ECF after treatment were significant predictors of OS, independent of tumor volume and other clinical prognostic factors (HR = 3.23 × 10^-6, p < 0.001 and HR = 2.39 × 10⁵, p < 0.001, respectively). Both post-treatment volumetric growth rate and the rate of change in cellularity were significantly correlated with OS (HR = 1.17, p = 0.003 and HR = 1.14, p = 0.01, respectively). Conclusion: Changes in histological characteristics estimated from a radio-pathomic ML model are a promising tool for evaluating treatment response and predicting outcome in rGBM. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： MRI rad-path radiopathomic mapping recurrent glioblastoma survival tumor growth rate

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Airr Community Curation and Standardised Representation for Immunoglobulin and T Cell Receptor Germline Sets

SSRN

引用

SSRN 2022年

作者： Lees, William D. Christley, Scott Peres, Ayelet Kos, Justin T. Corrie, Brian Ralph, Duncan Breden, Felix Cowell, Lindsay G. Yaari, Gur Corcoran, Martin Karlsson Hedestam, Gunilla B. Ohlin, Mats Collins, Andrew M. Watson, Corey T. Busse, Christian E. Institute of Structural and Molecular Biology Birkbeck College London United Kingdom Human-Centered Computing and Information Science Institute for Systems and Computer Engineering Technology and Science Porto Portugal Peter O’Donnell Jr School of Public Health Department of Immunology UT Southwestern Medical Center Texas United States Bioengineering Program Faculty of Engineering Bar-Ilan University Ramat Gan Israel Department of Biochemistry and Molecular Genetics School of Medicine University of Louisville Kentucky United States Department of Biological Sciences Simon Fraser University BurnabyBC Canada Fred Hutchinson Cancer Research Center SeattleWA United States Department of Microbiology Tumor and Cell Biology Karolinska Institute Stockholm Sweden Department of Immunotechnology Lund University Lund Sweden School of Biotechnology and Biomolecular Sciences University of New South Wales SydneyNSW Australia Division of B Cell Immunology German Cancer Research Center Heidelberg Germany

Analysis of an individual’s immunoglobulin or T cell receptor gene repertoire can provide important insights into immune function. High-quality analysis of adaptive immune receptor repertoire sequencing data depends upon accurate and relatively complete germline sets, but current sets are known to be incomplete. Established processes for the review and systematic naming of receptor germline genes and alleles require specific evidence and data types, but the discovery landscape is rapidly changing. To exploit the potential of emerging data, and to provide the field with improved state-of-the-art germline sets, an intermediate approach is needed that will allow the rapid publication of consolidated sets derived from these emerging sources. These sets must use a consistent naming scheme and allow refinement and consolidation into genes as new information emerges. Name changes should be minimised, but, where changes occur, the naming history of a sequence must be traceable. Here we outline the current issues and opportunities for the curation of germline IG/TR genes and present a forward-looking data model for building out more robust germline sets that can dovetail with current established processes and provides transparency based on principles of findability, accessibility, interoperability, and reusability. We describe results obtained by applying the data model and associated principles within the AIRR Community, including supporting software and databases. © 2022, The Authors. All rights reserved.

关键词： Genes

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Magnetic Control of Soft Chiral Phonons in PbTe

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Physical Review Letters 2022年第7期128卷 075901-075901页

作者： Andrey Baydin Felix G. G. Hernandez Martin Rodriguez-Vega Anderson K. Okazaki Fuyang Tay G. Timothy Noe, II Ikufumi Katayama Jun Takeda Hiroyuki Nojiri Paulo H. O. Rappl Eduardo Abramof Gregory A. Fiete Junichiro Kono Department of Electrical and Computer Engineering Rice University Houston Texas 77005 USA Smalley-Curl Institute Rice University Houston Texas 77005 USA Instituto de Física Universidade de São Paulo São Paulo São Paulo 05508-090 Brazil Theoretical Division Los Alamos National Laboratory Los Alamos New Mexico 87545 USA Laboratório Associado de Sensores e Materiais Instituto Nacional de Pesquisas Espaciais São José dos Campos São Paulo 12201-970 Brazil Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston Texas 77005 USA Department of Physics Graduate School of Engineering Science Yokohama National University Yokohama 240-8501 Japan Institute for Materials Research Tohoku University Sendai 980-8577 Japan Department of Physics Northeastern University Boston Massachusetts 02115 USA Department of Physics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Physics and Astronomy Rice University Houston Texas 77005 USA Department of Material Science and NanoEngineering Rice University Houston Texas 77005 USA

PbTe crystals have a soft transverse optical phonon mode in the terahertz frequency range, which is known to efficiently decay into heat-carrying acoustic phonons, resulting in anomalously low thermal conductivity. Here, we studied this phonon via polarization-dependent terahertz spectroscopy. We observed softening of this mode with decreasing temperature, indicative of incipient ferroelectricity, which we explain through a model including strong anharmonicity with a quartic displacement term. In magnetic fields up to 25 T, the phonon mode splits into two modes with opposite handedness, exhibiting circular dichroism. Their frequencies display Zeeman splitting together with an overall diamagnetic shift with increasing magnetic field. Using a group-theoretical approach, we demonstrate that these observations are the result of magnetic field-induced morphic changes in the crystal symmetries through the Lorentz force exerted on the lattice ions. Thus, our Letter reveals a novel process of controlling phonon properties in a soft ionic lattice by a strong magnetic field.

关键词： Chirality Diamagnetism Magneto-dielectric effect Optical phonons Thermal conductivity Zeeman effect Terahertz time-domain spectroscopy

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Identifying and Anticipating Cyberattacks That Could Cause Physical Damage to Industrial Control Systems

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IEEE Power and Energy Technology Systems Journal 2019年第4期6卷 172-182页

作者： Angle, Matthew G. Madnick, Stuart Kirtley, James L. Khan, Shaharyar Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Sloan School of Management School of Engineering Massachusetts Institute of Technology CambridgeMA02139 United States System Design and Management Program Massachusetts Institute of Technology CambridgeMA02139 United States

Physical control systems are increasingly controlled by reconfigurable, network-enabled devices to increase flexibility and ease commissioning and maintenance. Such capability creates vulnerabilities. Devices may be remotely reprogrammed by a malicious actor to act in unintended ways, causing physical damage to mechanical equipment, infrastructure, and life and limb. In this paper, past examples of actual damage to cyber-physical systems are shown, threats posed by software-controlled variable frequency drives (VFDs) are analyzed, and a small-scale version of an attack on ubiquitous VFD equipment is demonstrated. © 2014 IEEE.

关键词： Embedded systems

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Large spin-hall effect in Si at room temperature

arXiv

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arXiv 2020年

作者： Lou, Paul C. Katailiha, Anand Bhardwaj, Ravindra G. Bhowmick, Tonmoy Beyermann, W.P. Lake, Roger K. Kumar, Sandeep Department of Mechanical Engineering University of California RiversideCA92521 United States Department of Electrical Engineering and Computer Science University of California RiversideCA92521 United States Department of Physics and Astronomy University of California RiversideCA92521 United States Materials Science and Engineering Program University of California RiversideCA92521 United States

Silicon’s weak intrinsic spin-orbit coupling and centrosymmetric crystal structure are a critical bottleneck to the development of Si spintronics, because they lead to an insignificant spin-Hall effect (spin current generation) and inverse spin-Hall effect (spin current detection). Here, we undertake current, magnetic field, crystallography dependent magnetoresistance and magneto-thermal transport measurements to study the spin transport behavior in freestanding Si thin films. We observe a large spin-Hall magnetoresistance in both p-Si and n-Si at room temperature and it is an order of magnitude larger than that of Pt. One explanation of the unexpectedly large and efficient spin-Hall effect is spin-phonon coupling instead of spin-orbit coupling. The macroscopic origin of the spin-phonon coupling can be large strain gradients that can exist in the freestanding Si films. This discovery in a light, earth abundant and centrosymmetric material opens a new path of strain engineering to achieve spin dependent properties in technologically highly-developed materials. Copyright © 2020, The Authors. All rights reserved.

关键词： Phonons

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Repositioned Drugs for COVID-19-the Impact on Multiple Organs

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SN comprehensive clinical medicine 2021年第7期3卷 1484-1501页

作者： Christina Chan Sean T Foster Kayla G Chan Matthew J Cacace Shay L Ladd Caleb T Sandum Paul T Wright Brett Volmert Weiyang Yang Aitor Aguirre Wen Li Neil T Wright Department of Chemical Engineering and Materials Sciences Michigan State University 428 S. Shaw Lane Room 2100 EB East Lansing MI 48824 USA. Department of Biochemistry and Molecular Biology Michigan State University East Lansing MI USA. Department of Biomedical Engineering Michigan State University East Lansing MI USA. Institute for Quantitative Health Science and Engineering Michigan State University East Lansing MI USA. Integrative Neuroscience Program Binghamton University Binghamton NY USA. Department of Mechanical Engineering The Pennsylvania State University University Park PA USA. Department of Mechanical Engineering Virginia Polytechnic Institute and State University Blacksburg VA USA. Department of Electrical and Computer Engineering Michigan State University East Lansing MI USA. Department of Mechanical Engineering Michigan State University East Lansing MI USA.

This review summarizes published findings of the beneficial and harmful effects on the heart, lungs, immune system, kidney, liver, and central nervous system of 47 drugs that have been proposed to treat COVID-19. Many of the repurposed drugs were chosen for their benefits to the pulmonary system, as well as immunosuppressive and anti-inflammatory effects. However, these drugs have mixed effects on the heart, liver, kidney, and central nervous system. Drug treatments are critical in the fight against COVID-19, along with vaccines and public health protocols. Drug treatments are particularly needed as variants of the SARS-Cov-2 virus emerge with some mutations that could diminish the efficacy of the vaccines. Patients with comorbidities are more likely to require hospitalization and greater interventions. The combination of treating severe COVID-19 symptoms in the presence of comorbidities underscores the importance of understanding the effects of potential COVID-19 treatments on other organs.

关键词： COVID-19 Central nervous system Drug repositioning Heart Immune system Kidneys Liver Lungs

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Bi_2Se_3/C Nanocomposite as a New Sodium-Ion Battery Anode Material

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Nano-Micro Letters 2018年第3期10卷 135-143页

作者： Lixin Xie Ze Yang Jingying Sun Haiqing Zhou Xiaowei Chi Hailong Chen ANDy X.Li Yan Yao Shuo Chen Department of Physics and TcSUH University of Houston Department of Electrical and Computer Engineering and Materials Science and Engineering Program University of Houston The Woodruff School of Mechanical Engineering Georgia Institute of Technology Clements High School

Bi_2Se_3 was studied as a novel sodium-ion battery anode material because of its high theoretical capacity and high intrinsic conductivity. Integrated with carbon,Bi_2Se_3/C composite shows excellent cyclic performance and rate capability. For instance, the Bi_2Se_3/C anode delivers an initial capacity of 527 mAh g^(-10) at 0.1 A g^(-1) and maintains 89% of this capacity over 100 cycles. The phase change and sodium storage mechanism are also carefully investigated.

关键词： Bi2Se3 Sodium-ion battery High-energy ball milling Sodium storage mechanism

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On sparse identification of complex dynamical systems: a study on discovering influential reactions in chemical reaction networks

arXiv

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arXiv 2020年

作者： Harirchi, Farshad Kim, Doohyun Khalil, Omar Liu, Sijia Elvati, Paolo Baranwal, Mayank Hero, Alfred Violi, Angela Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109–2125 United States Department of Mechanical Engineering University of Michigan Ann ArborMI48109–2125 United States Departments of Chemical Engineering Biomedical Engineering Macromolecular Science and Engineering Biophysics Program University of Michigan Ann ArborMI48109–2125 United States

A wide variety of real life complex networks are prohibitively large for modeling, analysis and control. Understanding the structure and dynamics of such networks entails creating a smaller representative network that preserves its relevant topological and dynamical properties. While modern machine learning methods have enabled identification of governing laws for complex dynamical systems, their inability to produce white-box models with sufficient physical interpretation renders such methods undesirable to domain experts. In this paper, we introduce a hybrid black-box, white-box approach for the sparse identification of the governing laws for complex, highly coupled dynamical systems with particular emphasis on finding the influential reactions in chemical reaction networks for combustion applications, using a data-driven sparse-learning technique. The proposed approach identifies a set of influential reactions using species concentrations and reaction rates, with minimal computational cost without requiring additional data or simulations. The new approach is applied to analyze the combustion chemistry of H2 and C3H8 in a constant-volume homogeneous reactor. The influential reactions determined by the sparse-learning method are consistent with the current kinetics knowledge of chemical mechanisms. Additionally, we show that a reduced version of the parent mechanism can be generated as a combination of the significantly reduced influential reactions identified at different times and conditions and that for both H2 and C3H8 fuel, the reduced mechanisms perform closely to the parent mechanisms as a function of the ignition delay time over a wide range of conditions. Our results demonstrate the potential of the sparse-learning approach as an effective and efficient tool for dynamical system analysis and reduction. The uniqueness of this approach as applied to combustion systems lies in the ability to identify influential reactions in specified conditions and times dur

关键词： Learning systems

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THz Emission from Exchange-Coupled Fe/Ru/Ni Spintronic Emitters

THz Emission from Exchange-Coupled Fe/Ru/Ni Spintronic Emitt...

引用

International Conference on Infrared and Millimeter Waves

作者： R. Adam C. Greb D. E. Bürgler D. Cao S. Heidtfeld F. Wang J. Cheng D. Chakraborty I. Komissarov H. Hardtdegen M. Mikulics M. Büscher C. M. Schneider Roman Sobolewski Research Centre Jülich Peter Grünberg Institute (PGI-6) Jülich Germany Institut für Laser- und Plasmaphysik Heinrich Heine Universität Düsseldorf Düsseldorf Germany College of Physics Center for Marine Observation and Communications Qingdao University Qingdao China Materials Science Graduate Program University of Rochester Rochester New York USA Laboratory for Laser Energetics University of Rochester Rochester New York USA Department of Electrical and Computer Engineering University of Rochester Rochester New York USA Research Centre Jülich Ernst Ruska Centre for Microscopy and Spectroscopy with Electrons Jülich Germany Faculty of Physics University Duisburg-Essen Duisburg Germany Department of Physics University of California Davis Davis California USA

We explored THz emission from $\mathrm{Si}^{2} / \mathrm{SiO}_{2} / / \mathrm{Ta} / \mathrm{Fe} / \mathrm{Ru} /$ $\mathrm{Ni} / \mathrm{Al}_{2} \mathrm{O}_{3}$ spintronic emitters. We tuned magnetization alignment of Fe and Ni layers by varying the interlayer exchange coupling (IEC) strength using a range of Ru layer thickness t. Depending on IEC strength, magnetization hysteresis shows either ferromagnetic $(t=1.1 \mathrm{~nm}, 1.5 \mathrm{~nm})$, antiferromagnetic $(t=1.3 \mathrm{~nm})$ or canted $(t=1.7 \mathrm{~nm}, 1.9 \mathrm{~nm})$ relative alignment. Competition between IEC and an external magnetic field results in a dramatic difference in THz emission from the ferromagnetically (FM) and anti-ferromagnetically (AFM) coupled structures. The resulting THz emission from IEC structures is a result of an interference of THz transiens generated by the individual $\mathrm{Fe} / \mathrm{Ru}$ and $\mathrm{Ru} / \mathrm{Ni}$ emitters.

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Two-dimensional Bose-Hubbard model for helium on graphene

arXiv

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arXiv 2021年

作者： Yu, Jiangyong Lauricella, Ethan Elsayed, Mohamed Shepherd, Kenneth Nichols, Nathan S. Lombardi, Todd Kim, Sang Wook Wexler, Carlos Vanegas, Juan M. Lakoba, Taras Kotov, Valeri N. Del Maestro, Adrian Department of Physics University of Vermont BurlingtonVT05405 United States Materials Science Program University of Vermont BurlingtonVT05405 United States Department of Physics and Astronomy University of Missouri ColumbiaMO65211 United States Department of Mathematics & Statistics University of Vermont BurlingtonVT05405 United States Department of Physics and Astronomy University of Tennessee KnoxvilleTN37996 United States Min H. Kao Department of Electrical Engineering and Computer Science University of Tennessee KnoxvilleTN37996 United States

An exciting development in the field of correlated systems is the possibility of realizing two-dimensional (2D) phases of quantum matter. For a systems of bosons, an example of strong correlations manifesting themselves in a 2D environment is provided by helium adsorbed on graphene. We construct the effective Bose-Hubbard model for this system which involves hard-core bosons (U ≈ ∞), repulsive nearest-neighbor (V > 0) and small attractive (V0 4He adsorbed on graphene deep in the commensurate solid phase with 1/3 of the sites on the dual triangular lattice occupied. Because the parameters of the effective Bose-Hubbard model are very sensitive to the exact lattice structure, this opens up an avenue to tune quantum phase transitions in this solid-state system. Copyright © 2021, The Authors. All rights reserved.

关键词： Hubbard model

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