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Highlights of Medical Physics (GMED) Talks @ APS 2024 March Meeting

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American Physics Society (APS) March meeting is one of the largest physics meetings in the world. To help the community quickly catch up on the work presented in this conference, Paper Digest Team processed all accepted work, and generated one highlight sentence (typically the main topic) for each. Readers are encouraged to read these machine generated highlights to quickly get the main idea of each piece of work.

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TABLE 1: Highlights of Medical Physics (GMED) Talks @ APS 2024 March Meeting

Paper Author(s)
1 Micromagnetic Neural Stimulation and Spintronic Neural Sensing
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Highlight: In this talk, I will report our team’s magnetic biomedical brain related research: 1) micromagnetic neural stimulation (μMS) [1]; 2) spintronic neural sensing [2].		 Jian-Ping Wang;
2 Sensitive Diamond-based Magnetometry Toward Magnetoencephalography of A Living Animal
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Highlight: We develop a sensitive diamond quantum magnetometer with a dc sensitivity below 10 pT Hz -1/2 toward MEG of a living rat.		 Naota Sekiguchi ; Motofumi Fushimi ; Atsumi Yoshimura ; Chikara Shinei ; Masashi Miyakawa ; Takashi Taniguchi ; Tokuyuki Teraji ; Hiroshi Abe ; Shinobu Onoda ; Takeshi Ohshima ; Mutsuko Hatano ; Masaki Sekino ; Takayuki Iwasaki;
3 Co₉₀P₁₀ Sensing Elements Based on The Giant Magnetoimpedance Effect for Biomedical Applications
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Highlight: We characterized the composition, surface quality, and electrical and magnetic properties using Energy-dispersive spectroscopy (EDS), Impedance Analyzer, and VSM techniques.		 Rafael Licarião ; Emanoel Tavares França ; José Marques de Lima ; Carlos de Moraes Iglesias ; Eduardo Padrón Hernández ; Fernando de Araujo Machado ; Gilvania Da Silva Vilela;
4 Ultra-Sensitive Embedded AC Magnetic Tracers Through Nano-Scale Ordering
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Abstract: In magnetic nanoparticle (MNP) systems, inter-particle interactions as affected by the spatial MNP arrangement will strongly govern the macroscopic magnetic properties. Tuning …		 Frank Abel ; Eduardo de Lima Correa ; Thinh Bui ; Adam Biacchi ; Michael Donahue ; Solomon Woods ; Angela Hight Walker ; Cindi Dennis;
5 FMR Detection of Magnetic Nanowires (MNW) for Tagging and Sensing Applications
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Highlight: Detection occurs by setting a specific applied AC Frequency, along with the position and magnitude of an applied DC magnetic field. In this work, such detection is performed for MNWs of ferromagnetic materials and their alloys.		 Allison Harpel ; Md Toaha Anas ; Alex Wege ; Rhonda Franklin ; Bethanie Stadler;
6 Utilizing 13C NMR to Track The Biochemical Effect of Dichloroacetate on Glycolysis in Cultured Colorectal Cancer Cells
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Highlight: While it has primarily been under investigation in clinical trials for cancer treatment, DCA has displayed promise in addressing diabetes, as well as issues related to lipid and lipoprotein regulation. This particular study examines how DCA affects the metabolic processes of glucose in cultured colorectal cancer cells using 13C nuclear magnetic resonance (NMR) spectroscopy.		 Emmanuel Ameh ; Lloyd Lumata;
7 13C NMR Spectroscopic Studies of Liver Cancer Cells and Spheroids
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Highlight: The project focused on two hepatocellular carcinoma liver cancer cell lines HepG2 and HuH-7.		 Desiree DeHart ; Lloyd Lumata;
8 3D Imaging of Extracellular Matrix Analogues Via Fluorescence Correlation Spectroscopy Super-Resolution Optical Fluctuation Imaging (fcsSOFI)
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Highlight: In this work, we have taken a step further to extend this approach, employing fcsSOFI in conjunction with light sheet microscopy to reconstruct the three-dimensional structure of the matrix in various specific extracellular matrix analogues.		 Stephanie Kramer ; Benjamin Wellnitz ; Jeanpun Antarasen ; Surajit Chatterjee ; Albert Kim ; Lydia Kisley;
9 Hyperspectral Imaging of Head and Neck Tumors
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Highlight: A clinical study involving human patients with BCC, SCC, and benign skin lesions in the head and neck region will be presented.		 Matija Milanic ; Aljosa Krt ; Črt Keber ; Tadej Tomanic ; Jost Stergar ; Bostjan Markelc ; Ales Groselj ; Gregor Sersa;
10 Robustness of Machine Learning Techniques for CT26 Colon Carcinoma Classification Based on Hyperspectral Images
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Highlight: In this study, we utilized hyperspectral imaging (HSI) to monitor CT26 colon carcinoma tumors subcutaneously grown on the back of BALB/c mice.		 Tadej Tomanic ; Jost Stergar ; Tim Bozic ; Bostjan Markelc ; Simona Kranjc Brezar ; Gregor Sersa ; Matija Milanic;
11 Quantum Photonic Micro/Nanolaser for Rapidly Assessing Overall Health of Cells and Organelles
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Abstract: Healthy respiration of cells and organelles requires a stable proton pump in the inner mitochondrial membrane to regulate the membrane potential and internal biomolecular …		 Paul Gourley;
12 Theoretical Explorations of Quantum Neurosurgery
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Highlight: Thus, the ambition here is to undertake a rigorous theoretical exploration into the potential possibilities of implementing quantum theory into a Neurosurgical setting.		 Juan Diego Garcia;
13 Ultrasound Luminescence Chemical Imaging for Implant Infection
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Highlight: We present a hybrid ultrasound luminescent chemical imaging (ULCI) technique to probe the chemical environment on an implant surface.		 Sriparna Bhattacharya ; Gretchen Schober ; Unaiza Uzair ; Morgan Reel ; Vigjna Abbaraju ; Herbert Behlow ; Apparao Rao ; Jeffrey Anker;
14 Enhancing The Photodeactivation Efficiency of Pathogens in Prosthetic Joint Infection with Methylene Blue and Silver Nanoparticles Through Efflux Pump Inhibition
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Highlight: This research adopts a synergistic approach, combining the efflux pump inhibitor (EPI) , reserpine, with silver nanoparticles (Ag NPs) and methylene blue (MB) to enhance PDT efficiency.		 Yaran Allamyradov ; Justice ben Yosef ; Inomjon Majidov ; Zikrulloh Khuzhakulov ; Simran Banga ; Mahmood Ateyeh ; Alper Er ; Ali Oguz Er ; Salizhan Kylychbekov;
15 Hydroxyapatite Coatings on Ti6Al4V and Si(100) Surfaces By Pulsed Laser Deposition
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Highlight: In this research, the effect of substrate temperature and ablation mechanism on the properties of hydroxyapatite (HA) coatings were investigated.		 Ali Er ; Salizhan Kylychbekov ; Yaran Allamyradov ; Justice ben Yosef ; Liviu Duta ; Inomjon Majidov ; Zikrulloh Khuzhakulov ; Simran Banga;
16 Deep Dive Into Optical Properties of SiliGlass Tissue Phantoms
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Highlight: In this contribution, we present a detailed study of a polymer-based, stable, and affordable phantom, based on the SiliGlass polymer, black pigment, and glass microspheres.		 Jost Stergar ; Matija Milanic;
17 Restoring Cerebrospinal Fluid Drainage Following Traumatic Brain Injury: Insights from Computational Modeling
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Highlight: To delve deeper into the relation of vessel contractility and CSF drainage, we use a lumped parameter model to simulate the CSF efflux from the brain to CLVs.		 Daehyun Kim;
18 Longitudinal Analysis of Brain Images for The Study of Cognitive Decline and Alzheimer’s Disease Response Assessment
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Highlight: The goal of this work was to establish quantitative, longitudinal patterns of cognitive decline in both AD and normal aging using neuroimaging.		 Alison Deatsch ; Mauro Namías ; Matej Perovnik ; Robert Jeraj;
19 Astrocytes Mediate Hyperexcitability in Normal Neuronal Function During Tauopathy Disease Progression
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Highlight: We present our recent experimental results showing how astrocytes mediate extracellular spread of tau and supporting hyperexcitability in neuronal networks.		 Michael Gramlich ; Miranda Reed ; Paxton Wilson;
20 Detangling Neuronal Networks in Epilepsy for Better Interventions
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Highlight: By using modern techniques, including on-demand optogenetics, closed-loop optimization strategies, and in vivo imaging methods, we work to disentangle neuronal networks and their relationship to seizures to identify much needed novel therapeutic approaches.		 Esther Krook-Magnuson;
21 A Gas Sensor Array for The Selective Detection of Cancer Related Volatile Organic Compounds
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Highlight: We have addressed this challenge by developing a new nanostructured material and engineering it to be sensitive to low concentration VOCs. In this presentation, we showcase the performance of a four-sensor array developed using this material in detecting VOC biomarkers for cancer detection.		 David Waligo ; Oomman K. Varghese ; Bigyan Kandel ; Lilly Schaffer ; Maggie Paulose;
22 Positron Emission Tomography with Liquid Argon Detection
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Highlight: This presentation will describe our efforts to construct a prototype LArTPC featuring a pixelated anode and VUV light sensors and expose it to a radioactive source (Na-22), allowing the response of the detector to 511 keV gammas to be studied.		 Mitch Soderberg ; Corinne Motl;
23 Brain Synchronization As A Predictive Factor in Depression Treatment Given EEG-synchronized RTMS
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Highlight: Since recent evidence emphasizes the crucial role of alpha oscillations in network connectivity, especially in mediating top-down influences within the human brain, including responses to neurostimulation methods like rTMS, in response to the challenge, we introduce an innovative approach—a closed-loop, phase-locked repetitive TMS (rTMS) treatment.		 Xiaoxiao Sun ; Jayce Doose ; Josef Faller ; James McIntosh ; Golbarg Saber ; Sarah Huffman ; Spiro Pantazatos ; Han Yuan ; Robin Goldman ; Truman Brown ; Mark George ; Paul Sajda;
24 Enhancing The MRI Signals of Metabolic Biosensors By >10,000-fold Via Dissolution Dynamic Nuclear Polarization
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Abstract: Dynamic nuclear polarization (DNP) via the dissolution method is a technique that allows the production of highly-amplified or "hyperpolarized" liquid-state nuclear …		 Lloyd Lumata;
25 Dynamic Nuclear Polarization of 23Na and 13C Nuclear Spins at 4.6T and 1.25 K
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Highlight: In this work we attempt to maximize the polarization of the spin active 13C and 23Na nuclei in Sodium acetate at 4.6T and 1.25K.		 Daniel Anable ; Lloyd Lumata;
26 Hyperspectral Imaging with Active Illumination Using Incandescent Lamp and Variable Filament Temperature
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Highlight: We present an algorithm for spectrum reconstruction, addressing the ill-posedness of inverse problem.		 Urban Simoncic ; Matija Milanic;
27 Lattice Boltzmann Method Based Computations for Gold Nanorods Mediated Thermal Ablation During Plasmonic Photothermal Therapy
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Highlight: Herein, D3Q15 scheme of LBM is reported to solve thermal transport using Pennes’ bioheat model and thermal ablation using Arrhenius equation within a 3D tumor-tissue domain during PPTT involving GNRs and on NIR irradiation.		 Amit Shaw ; Sanjeev Soni;
28 Ion Type Dependence of DNA Electronic Excitation in Water Under Proton, Α-particle, and Carbon Ion Irradiation: A First-Principles Simulation Study
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Highlight: Here we use real-time time-dependent density functional theory (RT-TDDFT) to simulate the non-equilibrium energy transfer excitation process in solvated DNA under proton, α-particle, and carbon ion irradiation [1-2].		 Christopher Shepard ; Yosuke Kanai;
29 Bridging The Gap Between Mechanistic and Phenomenological Models of Cell Survival Via The Manifold Boundary Approximation Method (MBAM)
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Highlight: We apply the Manifold Boundary Approximation Method (MBAM) to systematically compress the parameter space of Mechanistic DNA Repair and Survival (MEDRAS), a complex mechanistic radiobiological model for cell survival in the presence of radiation.		 Tahir Yusufaly ; Seyed Ahmad Sabok-Sayr ; Mark Transtrum;
30 Single Module of A Compton Camera Detector for Online Beam Range Monitoring in Proton Therapy
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Highlight: The SiFi-CC (SiPM and scintillating Fiber based Compton Camera) group develops a method of in vivo proton range monitoring with a Compton camera.		 Magdalena Kolodziej ; Achim Stahl ; Aleksandra Wrońska ; Alexander Fenger ; Andrzej Magiera ; Barbara Kołodziej ; George Farah ; Jonas Kasper ; Katarzyna Rusiecka ; Magdalena Rafecas ; Ming-Liang Wong ; Ronja Hetzel ; Vitalii Urbanevych ; Linn Mielke;
31 X-Ray Attenuation and X-ray Fluorescence Measurements of A Primary Incisor Tooth Slice
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Highlight: Primary teeth are accessible human tissues whose analysis can reveal developmental health issues such as toxic exposures, malnutrition, and dietary changes.		 Mihai Gherase ; Benjamin Awad;
32 Fundamental Parameter Method Application to Determinations of Absolute Elemental Concentrations in A Thin Lamb Bone Slice From Microscopic X-ray Fluorescence Measurements at The Canadian Light Source Synchrotron
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Highlight: The mfp of Ca K-shell XRF photons in the human cortical bone is about 35 µm. Making ultrathin bone slices is labor intensive, time consuming, and prone to elemental contaminations. Therefore, developing a data analysis method which accounts for x-ray attenuation in SR XRF microscopy studies of dense tissues is a more practical alternative.		 Mihai Gherase ; Nikhil Hematillake ; David Fleming ; Renfei Feng;
33 Surgical Planning: A Path Planning Approach with Differentiable Simulations and Overdamped Langevin Equation
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Highlight: We introduce a streamlined method for quick path planning.		 jean-baptiste masson ; Robin CREMESE ; françois Laurent;
34 A Novel TCM-based AI Large Model Framework Toward Human Diseases and Drug-Diseases Associations
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Highlight: Our work aims to promote the quantitative underpinning of TCM pharmacological principles, provide a basis for the objectification of the diagnosis and treatment process of TCM, and pave the way for the knowledge fusion of TCM evidence-based medicine and modern biology.		 Haoran LI ; Xingye CHENG ; Jingyuan LUO ; Zhaoxiang BIAN ; Aiping LYU ; Leihan TANG ; Liang TIAN;
35 The Physical Basis of Using MRI for Detecting Cancer and Pre-cancer Cells
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Highlight: In this presentation, we will start by reviewing the history of the development of the spin-echo NMR technique for cancer detection.		 Donald Chang;
36 Magnetic Resonance Elastography: Combining Magnetic Resonance and Acoustics
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Highlight: Like most other advances in medical imaging technology, MRE was developed through convergence science: bringing the disciplines of physics, mathematics, and engineering together with biological science. The presentation will discuss challenges and opportunities where convergence science promises to further advance MRE and its applications.		 Richard Ehman;
37 The Endless Capabilities of Magnetic Resonance, from Zero to High Fields
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Abstract: Magnetic resonance techniques (NMR, MRI, EPR) continue to play ever expanding roles in biomedical research and modern medicine. NMR and MRI detect the angular momentum (“spin”) of …		 Michael Garwood;
38 Time Reveals Length Scale: Human Tissue Microstructure Characterization By Time-dependent Diffusion MR
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Highlight: This talk will discuss: 1) how tissue microstructures at the length scale of micrometer can be specifically characterized by time-dependent diffusion MRI; 2) how the time-dependent diffusion MRI became feasibility in today’s MRI system; and 3) how MRI-based tissue microstructure imaging is defining the future of precision medicine.		 Ante Zhu;
39 Quantitative MRI and The Aging Brain
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Highlight: The goals of our work are twofold: to improve the capacity of MR to evaluate tissue pathology, and to develop methods for application to inverse problems more generally.		 Richard Spencer;
40 Mechanical Properties of Adipose Tissue Mediate Breast Cancer Invasion
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Highlight: We find that increasing the adipocyte stiffness strongly suppresses breast cancer invasion.		 Dong Wang ; Yitong Zheng ; Garrett Beeghly ; Brianna Knode ; Claudia Fischbach ; Mark D Shattuck ; Corey O’Hern;
41 Migration of Circulating Tumor Cells Through A Heterogeneous Constriction Network
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Highlight: In this talk, we will present preliminary data showcasing the coupling effect between CTCs and the fluid flow, shedding light on the development of a statistical model to predict CTC breakthrough through the network.		 Ankur Bordoloi ; Tim Winkel ; Kristian Thijssen ; Amin Doostmohammadi ; Pouyan Boukany;
42 Transport of Cancer Cells in Shear Flows
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Highlight: Our preliminary work ( Akerkouch et al., Ann Biomed Eng 51, 1199–1215 (2023)) suggested a potential link between cancer cell growth and the fluid flow pattern.		 TRUNG LE ; Tam Nguyen ; Lahcen Akerkouch ; Amanda Haage;
43 Using Cancer Cell Motility to Predict The Final Morphology of The Tumor
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Highlight: In this study, we generate three-dimensional engineered spheroids of triple-negative breast cancer cells, comprising two clonal subpopulations with epithelial and mesenchymal characteristics.		 Carolina Trenado Yuste ; Samhita Banavar ; Celeste Nelson;
44 Investigating Glioblastoma Growth and Metabolism Via MNK-eIF4E Pathway Modulation Using NMR Spectroscopy
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Highlight: The study will include the presentation and discussion of data obtained from NMR spectroscopy and other relevant sources.		 Kathleen Cate Domalogdog ; Lloyd Lumata;
45 Biophysical Modeling Identifies An Optimal Hybrid Amoeboid-mesenchymal Phenotype for Maximal T Cell Migration Speeds
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Highlight: Here, we have developed a hybrid stochastic-mean field biophysical model of bleb-based cell motility to study the potential for adhesion-free bleb-based migration.		 Roberto Alonso Matilla ; David Odde ; Paolo Provenzano;
46 Computational Modeling of Breast Cancer Cell Invasion Into Adipose Tissue
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Highlight: We developed novel discrete element method (DEM) simulations of tumor cell invasion into adipose tissue in three dimensions.		 Yitong Zheng ; Dong Wang ; Garrett Beeghly ; Claudia Fischbach ; Mark D Shattuck ; Corey O’Hern;
47 Optimizing Prostate Cancer Treatment: High-Frequency Adaptive Therapy
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Highlight: We present analytical estimations and justifications for high-frequency adaptive therapy, and provide proposals for how it can be implemented through open-loop observations of patients in clinical practice.		 Trung Phan ; Shengkai Li ; Benjamin Howe ; Robert Gatenby ; Joel Brown ; Sarah Amend ; Kenneth Pienta ; Robert Austin ; Yannis Kevrekidis;
48 Mathematical Model for Pancreatic Cancer in Early Intraepithelial Neoplasia
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Highlight: In this work, we present the effects of a gene regulatory network of pancreatic cells when some genes have a delay actions.		 Jose-Roberto Romero-Arias ; Guillermo Ramirez-Santiago;
49 Optical Label-free Determination of Mitochondrial Dynamics Using Deep Learning
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Highlight: Here, we present an optical, label-free, deep learning enabled mitochondria detection technique for live mammalian cells and demonstrate the applicability of the proposed method in characterizing the dynamics of mitochondria in HeLa, Neuroglioblastoma, and CHO cells.		 Neha Goswami ; YoungJae Lee ; Gabriel Popescu ; Mark Anastasio;
50 Longitudinal Interpretability of Deep-Learning Based Breast Cancer Risk Prediction Model
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Highlight: Each study included four images (two views per breast).		 Zan Klanecek ; Yao Kuan Wang ; Tobias Wagner ; Lesley Cockmartin ; Nicholas Marshall ; Brayden Schott ; Alison Deatsch ; Andrej Studen ; Miloš Vrhovec ; Hilde Bosmans ; Robert Jeraj;
51 Assessing The Impact of CNN Architectures for Whole Organ Segmentation on Predictive Models of Organ Toxicity
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Highlight: However, the impact assessment of CNN segmentation model architectures on predictive models’ performance is incipient. Here, we perform such assessment on a 18F-FDG PET histogram metrics-based model for predicting organ inflammation.		 Katja Strasek ; Daniel Huff ; Nežka Hribernik ; Victor Fernandes ; Vincent Ma ; Zan Klanecek ; Andrej Studen ; Katarina Zevnik ; Martina Reberšek ; Robert Jeraj;
52 Spatially Resolved IR Hyperspectral Imaging for Malignant Cell Detection
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Highlight: To systematically investigate the IR spectral alterations associated with carcinogenesis and tumor progression, we initiated a research program to spatially resolve chemistry from IR hyperspectral imaging of individual cells.		 Proity Akbar;
53 Radiomics Assisted Machine Learning Model for Predication of Prostate Specific Antigen Levels
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Highlight: We proposed a machine learning model to predict prostate specific antigen (PSA) levels for intermediate or high-risk prostate cancer patients undergoing definitive treatment course.		 Saad Bin Saeed Ahmed ; Agha Hammad Khan ; Wazir Muhammad;
54 Deep Learning for Image Analysis of Breast and Prostate Cancer Cell Cultures
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Highlight: We present a machine-learning analysis of phase-contrast microscope images of breast cancer (MDA-MB-231) and prostate cancer (PC3) cell cultures.		 Aliakbar Sepehri ; Ian Bergerson ; Yen Lee Loh ; Lucas Bierscheid ; John Wilkinson;
55 Structure Prediction of Iron Hydrides Across Pressure Range with Transferable Machine-learned Interatomic Potential
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Highlight: Here, we demonstrate the efficacy of automated and systematic methods for training and validating transferable ML-IAPs through global optimization techniques.		 Hossein Tahmasbi ; Kushal Ramakrishna ; Mani Lokamani ; Attila Cangi;
56 Development of A Machine Learning Interatomic Potential for Uranium Nitride
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Highlight: In this study, we have extended previous work by developing an MLIP for uranium mononitride (UN).		 Lorena Alzate-Vargas ; Richard Messerly ; Roxanne Tutchton ; Kashi Subedi ; Michael Cooper ; Tammie Gibson;
57 Fast Generation of Ab Initio Training Data for Large-Scale Applications of Neural Network Potentials
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Highlight: We propose a method to quickly generate a dataset to train a NNP tailored to perform well on the target system of interest.		 Jaesuk Park ; Feliciano Giustino;
58 Graph-Transformer Model for Direct Band Structure Prediction from Crystal Structures
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Highlight: We developed the first end-to-end model that directly predicts band structures from crystal structures.		 Weiyi Gong ; Tao Sun ; Hexin Bai ; Jeng-Yuan Tsai ; Haibin Ling ; Qimin Yan;
59 Global Structure Optimization and Metastable Structure Enumeration Using Polynomial Machine Learning Potentials
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Highlight: We show a procedure for performing structure enumerations, including global structure optimization, accelerated by the polynomial MLPs.		 Atsuto Seko;
60 Developing Generalizable Machine Learning Models Using Electronic Structure-based Features
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Highlight: In this study, we explore the construction of a feature space that includes the underlying physics of a system by using information obtained from computationally affordable electronic structure calculations, such as Hartree-Fock.		 Clara Kirkvold ; Jason Goodpaster;
61 Accurate Prediction of Magnetic Properties of Permanent Magnets Using Machine Learning
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Highlight: Moreover, the theoretical determination of macroscopic coercive properties is poor, largely due to Brown’s paradox. To address this limitation, we employ DFT by incorporating machine learning (ML) to synthesize experimentally measured magnetic properties and utilize micromagnetic modeling.		 Churna Bhandari ; Gavin Nop ; Durga Paudyal;
62 Uncertainty Quantification for Deep Learning-based Metastatic Tumor Delineation on 68Ga-DOTATATE PET/CT Images
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Highlight: In this work, we compare DL uncertainty quantification (UQ) methods for metastatic tumor delineation.		 Brayden Schott ; Victor Santoro Fernandes ; Zan Klanecek ; Dmitry Pinchuk ; Robert Jeraj;
63 Quantifying Metastasis Heterogeneity in Colorectal Cancer
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Highlight: We are taking advantage of a unique collection of multi-region sampled metastatic colorectal cancer cases that we have been building over years, encompassing more than 1000 distinct tumor samples from more than 100 patients.		 Kamila Naxerova;
64 Quantifying The Somatic Evolution Occurring in Healthy and Pre-malignant Human Tissues
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Highlight: In this talk I will describe how large-scale sequencing data from hundreds of thousands of individuals can be used to provide quantitative estimates for the key parameters governing clonal evolution including the “fitness effects” conferred by specific variants, the mutation rates of alterations and the population sizes of cycling stem cells.		 Jamie Blundell;
65 Predicting Cancer Evolution: Quantifying Immune Selection and Other Selective Pressures
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Highlight: Here we develop a biophysically grounded model to quantify immunogenicity of tumor neoantigens.		 Marta Luksza;
66 Characterizing The T Cell Response to A Personalized Cancer Vaccine
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Highlight: In this talk I will discuss how to leverage T cell receptor (TCR) repertoire sequencing to characterize and monitor responses to the vaccine.		 Zachary Sethna;
67 Finding Mechanisms of Resistance In Cancer
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Highlight: In this presentation, I will discuss different approaches for finding mechanisms of resistance, including studying pre-treatment and post-resistance samples; estimating clonal fitness; and identifying convergent evolution across subclones.		 Gad Getz;

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