PHIND Seminar Series: Identifying Fibroblasts Subtypes Contributing to the Progression of Preinvasive to Invasive Lung Adenocarcinoma
Sylvia Plevritis, Ph.D.
Professor of Biomedical Data Science and of Radiology
Integrative Biomedical Imaging Informatics at Stanford
Stanford University
Location
Webinar URL: https://stanford.zoom.us/s/93945120934?pwd=a29GNjFCUzBtWjRsbFdnUnVUOTMzUT09
Dial: +1 650 724 9799 or +1 833 302 1536
Webinar ID: 939 4512 0934
Password: 767148
11:00am – 12:00pm Seminar & Discussion
RSVP: https://www.onlineregistrationcenter.com/SPlevritis
ABOUT
Dr. Sylvia K. Plevritis is Professor and Chair of Biomedical Data Science, Professor of Radiology at Stanford University and Program Director of the Stanford Biomedical Informatics Graduate Training Program. Dr. Plevritis leads a computational biology cancer research program that bridges genomics, imaging and population sciences to decipher properties of cancer progression and treatment response. Dr. Plevritis received her Ph.D. in Electrical Engineering and M.S. in Health Services Research, both from Stanford University, with a focus on cancer imaging physics and modeling cancer outcomes, respectively. She has had a primary authorship role on over 100 scientific cancer-related articles. She is a fellow of the American Institute for Medical and Biological Engineering (AIMBE) and Distinguished Investigator in the Academy of Radiology Research. She serves on the NCI Board of Scientific Advisors, the Program Leadership Committee of the Stanford Cancer Institute and the Leadership Council of the Stanford Bio-X Program. Dr. Plevritis has served on numerous NIH study sections, chaired scientific programs for the several professional societies including the American Association for Cancer Research (AACR) and presented keynote lectures across multiple scales of computational cancer biology. Currently, she is the Program Director of the Stanford Center in Cancer Systems Biology (CCSB) and has been a Principal Investigator with the NCI Cancer Intervention Surveillance Network (CISNET) for over fifteen years. She has served as Program Director of the Stanford Cancer Systems Biology Scholars Program (CSBS), and co-Division Chief of Integrative Biomedical Imaging Informatics at Stanford (IBIIS).
Sponsored by the PHIND Center and the Department of Radiology
Dear WMIS trainees, colleagues and friends,
We welcome you to join our upcoming virtual WMIS – Stanford Diversity conference on September 9-11, 2020. We are coming together to reinforce our commitment to diversity and to provide a forum for our team members to engage in meaningful discussions. The conference will provide keynote lectures, scientific presentations and educational lectures from leaders and pioneers in the field, who will discuss important topics related to racial justice, women in STEM and Global Health. We are also offering breakout sessions whereby carefully selected individuals will facilitate a discussion about how to implement more supportive and inclusive practices into our daily professional and personal life. The breakout sessions are designed to enable active involvement of smaller groups where people feel safe to discuss current challenges in the STEM field and actionable solutions.
This conference is free of charge and will provide 9.5 CME credits. Abstracts of all conference presentations and a summary of discussion points and insights provided by all conference participants will be published in Molecular Imaging & Biology. The organizing committee will provide 10 trainee prizes in the form of free WMIS memberships to conference attendants for the 2021 WMIC in Miami.
Website: https://www.wmislive.org
PHIND Seminar Series: Maintaining Competitive Advantage through Intellectual Capital
Soody Tronson, M.S., J.D.
Founder
Presque
Location & Timing
11:00am – 12:00pm Seminar & Discussion
Webinar URL: https://stanford.zoom.us/s/98817009379?pwd=U21pYnpCTUlxY3U2TEh4RmhvMXpvQT09
Dial: +1 650 724 9799 or +1 833 302 1536
Webinar ID: 988 1700 9379
Password: 767148
RSVP: https://www.onlineregistrationcenter.com/STronson
ABSTRACT
Digital health has provided a range of solutions, including health and wellness-related management, machine learning algorithms for pattern recognition, AI for genetic analysis, AI-enhanced clinical decision making, and virtual doctors that use AI for patient intake triage. Intellectual property can play an important role in providing a competitive advantage in the digital health industry. We will explore opportunities and challenges for protecting digital health technologies during the program, including patent eligibility challenges and the use of trade secrets.
ABOUT SOODY TRONSON
Soody Tronson is Founding Managing Counsel at STLG Law Firm, counseling domestic and international clients in IP and technology transactions in a wide range of technologies. In 2016 she formed, Presque, a company developing a line of medical devices for mothers and infants.
Soody has over 25 years of operational experience in technology, business, management, and law in start-up and fortune 100 companies, including Schering Plough Pharmaceuticals, Hewlett-Packard Co., Avantec Vascular, and the law firms of HellerEhrman and Townsend and Townsend.
Soody serves in board and leadership capacities with several organizations including the Association of Women in Science STEM to Market national accelerator; Licensing Executives Society USA/Canada, California Lawyers Association, and the Palo Alto Area Bar Association. Soody is a Commissioner with the city of Menlo Park; and an active hands-on volunteer with several civic organizations including Defy Ventures, an entrepreneurship training program for currently and formerly incarcerated. Soody has instructed courses in IP, licensing, and entrepreneurship at the University of California, Stanford University and European institutions. She is the co-author of the book “Women Securing the Future with TIPPSS for IoT: Trust, Identity, Privacy, Protection, Safety, Security for the Internet of Things.”
Hosted by: Garry Gold, MD
Sponsored by the PHIND Center and the Department of Radiology
Judy Gichoya, MD
Assistant Professor
Emory University School of Medicine
Measuring Learning Gains in Man-Machine Assemblage When Augmenting Radiology Work with Artificial Intelligence
Abstract
The work setting of the future presents an opportunity for human-technology partnerships, where a harmonious connection between human-technology produces unprecedented productivity gains. A conundrum at this human-technology frontier remains – will humans be augmented by technology or will technology be augmented by humans? We present our work on overcoming the conundrum of human and machine as separate entities and instead, treats them as an assemblage. As groundwork for the harmonious human-technology connection, this assemblage needs to learn to fit synergistically. This learning is called assemblage learning and it will be important for Artificial Intelligence (AI) applications in health care, where diagnostic and treatment decisions augmented by AI will have a direct and significant impact on patient care and outcomes. We describe how learning can be shared between assemblages, such that collective swarms of connected assemblages can be created. Our work is to demonstrate a symbiotic learning assemblage, such that envisioned productivity gains from AI can be achieved without loss of human jobs.
Specifically, we are evaluating the following research questions: Q1: How to develop assemblages, such that human-technology partnerships produce a “good fit” for visually based cognition-oriented tasks in radiology? Q2: What level of training should pre-exist in the individual human (radiologist) and independent machine learning model for human-technology partnerships to thrive? Q3: Which aspects and to what extent does an assemblage learning approach lead to reduced errors, improved accuracy, faster turn-around times, reduced fatigue, improved self-efficacy, and resilience?
Zoom: https://stanford.zoom.us/j/93580829522?pwd=ZVAxTCtEdkEzMWxjSEQwdlp0eThlUT09
PHIND Seminar Series: Serum Modulation of Mitochondrial Function as a Scalable Sensor of Insulin Resistance
Andrew Lipchik, Ph.D.
Postdoctoral Fellow – Michael Snyder Lab
Stanford University
11:00am – 12:00pm Seminar & Discussion
12:00pm – 12:15pm Reception & Light Refreshments
RSVP: https://stanford.zoom.us/webinar/register/7716009863360/WN_dbeuo7csS8q_AhR88XET0g
Location: Zoom
Webinar URL: . https://stanford.zoom.us/s/96358568342
Webinar ID: 963 5856 8342
Dial: +1 650 724 9799 or +1 833 302 1536 (Toll Free)
Password: 767148
ABSTRACT
The global epidemic of obesity is associated with the dramatic increase in the prevalence of type 2 diabetes mellitus (T2D) with an estimated 400 million people worldwide will have T2D by 2030. T2D is proceeded by insulin resistance (IR) for up to decades prior to onset of T2D. Current estimates suggest approximately one in three individuals are sufficiently insulin resistant to be at risk for IR complications including T2D, coronary heart disease and nonalcoholic fatty liver disease. IR often goes undiagnosed due to the complex, invasive and laborious nature of clamp assays preventing their universal application in the clinic. Surrogate measurements using fasting plasma glucose and insulin levels can estimate IR but are imprecise. There is a need for the identification of new biomarkers and assays for the detection and monitoring of IR. Here, we demonstrate the utility of cellular mitochondrial respiration in response to individuals’ serum as a sensor for personalized monitoring of insulin sensitivity. The modulation of insulin-dependent mitochondrial function by patient serum was highly correlated with insulin sensitivity as determined by the gold-standard modified insulin suppression test (IST). We further applied this methodology to monitor insulin sensitivity over time in response to illness as well as treatment with the insulin sensitizing medication, pioglitazone. Our results demonstrate the development and application of a novel surrogate measurement for the determination and monitoring of insulin sensitivity. This assay offers the advantages of minimal invasiveness and complexity compared to IST as well as superior correlation with IST compared to existing surrogate measurements.
ABOUT ANDREW LIPCHIK
Andrew Lipchik majored in Chemistry at Xavier University where he preformed research on the development of oxygen activation Ni(II) complexes with Dr. Craig Davis and Dr. Michael Baldwin at the University of Cincinnati. He went on to obtain his PhD from Purdue University under mentorship of Dr. Laurie Parker. His thesis work focused on identifying determinants of kinase substrate specificity. This understanding was applied to the development of novel kinase-specific peptide biosensors to monitor intracellular kinase activity. Following his graduate work, he joined the laboratory of Michael Snyder at Stanford University where he has focused on understanding the impact of the immune system on insulin resistance and glucose metabolism.
Hosted by: Garry Gold, M.D.
Sponsored by the PHIND Center and the Department of Radiology
PHIND Seminar Series: Identifying Microbiome Markers of Progression of Alzheimer’s Disease
Ami Bhatt, M.D., Ph.D.
Assistant Professor of Medicine (Hematology) and of Genetics
Stanford University
Gavin Sherlock, Ph.D.
Associate Professor of Genetics
Stanford University
11:00am – 12:00pm Seminar & Discussion
RSVP: https://stanford.zoom.us/webinar/register/8016040837299/WN_iBOM7R4XQjOPSb20rkUxbw
Location: Zoom Webinar
Webinar URL: https://stanford.zoom.us/s/99730716280
Webinar ID: 997 3071 6280
Dial: +1 650 724 9799 or +1 833 302 1536 (Toll Free)
Password: 767148
ABOUT AMI BHATT
In perpetual awe of how ‘simple’ microbial organisms can perturb complex, multicellular eukaryotic organisms, Ami Bhatt has chosen to dedicate her research program to inspecting, characterizing and dissecting the microbe-human interface. Nowhere is the interaction between hosts and microbes more potentially impactful than in immunocompromised hosts and global settings where infectious and environmental exposures result in drastic and sometimes fatal health consequences.
Ami’s group identifies problems and questions that arise in the course of routine clinical care. Often in collaboration with investigators at Stanford and beyond, the group applies modern genetic, molecular and computational techniques to seek answers to these questions, better understand host-microbe interactions and decipher how perturbation of these interactions may result in human disease phenotypes.
GAVIN SHERLOCK’S RESEARCH INTERESTS
Adaptive Evolution and the Fitness Landscape: When yeast are evolved under various selective pressures in a chemostat, mutations that arise and provide an adaptive advantage will expand within the population. We have pioneered the use of high throughput sequencing to determine the identity of such mutations, as well as to understand the dynamics of the mutations within the populations, and the interactions between the mutations (such as epistasis). Further, we have developed a DNA barcode based lineage tracking system to determine the distribution of fitness effects (DFE) for newly arising beneficial mutations. We have also characterized what we call the genotype-fitness map for beneficial mutations, and have investigated why beneficial mutations provide a positive fitness effect. We are also interested in how beneficial mutations trade-off for different traits, and how those trade-offs constrain adaptive evolution.
Hosted by: Garry Gold, M.D.
Sponsored by the PHIND Center and the Department of Radiology
Ge Wang, PhD
Clark & Crossan Endowed Chair Professor
Director of the Biomedical Imaging Center
Rensselaer Polytechnic Institute
Troy, New York
Abstract:
AI-based tomography is an important application and a new frontier of machine learning. AI, especially deep learning, has been widely used in computer vision and image analysis, which deal with existing images, improve them, and produce features. Since 2016, deep learning techniques are actively researched for tomography in the context of medicine. Tomographic reconstruction produces images of multi-dimensional structures from externally measured “encoded” data in the form of various transforms (integrals, harmonics, and so on). In this presentation, we provide a general background, highlight representative results, and discuss key issues that need to be addressed in this emerging field.
About:
AI-based X-ray Imaging System (AXIS) lab is led by Dr. Ge Wang, affiliated with the Department of Biomedical Engineering at Rensselaer Polytechnic Institute and the Center for Biotechnology and Interdisciplinary Studies in the Biomedical Imaging Center. AXIS lab focuses on innovation and translation of x-ray computed tomography, optical molecular tomography, multi-scale and multi-modality imaging, and AI/machine learning for image reconstruction and analysis, and has been continuously well funded by federal agencies and leading companies. AXIS group collaborates with Stanford, Harvard, Cornell, MSK, UTSW, Yale, GE, Hologic, and others, to develop theories, methods, software, systems, applications, and workflows.
PHIND Seminar Series: Topics Below
Ahmed Metwally, PhD
“Pre-symptomatic detection of COVID-19 via wearables biosensors”
Postdoctoral Scholar – Michael Snyder, PhD Lab
Department of Genetics
Stanford University
Pierre-Alexandre Fournier, MS
“Continuous remote cardiorespiratory and health monitoring using the Hexoskin biometric shirt”
Co-founder and CEO
Hexoskin
Location: Zoom Webinar
Webinar URL: https://stanford.zoom.us/s/98925964231
Dial: +1 650 724 9799 or +1 833 302 1536 (Toll Free)
Webinar ID: 989 2596 4231
Passcode: 298382
11:00am – 12:00pm Seminar & Discussion
RSVP: https://stanford.zoom.us/webinar/register/WN_bruT-pvvQUePuBLqm2SLkQ
Ahmed Metwally Abstract
Wearable devices digitally measuring vital signs have been used for monitoring health and illness onset and have a high potential for real-time monitoring and disease detection. As such, they are potentially useful during public health crises, such as the current COVID-19 global pandemic. In my talk, I’ll discuss how wearables biosensors can be used as a tool to early detect COVID19 onset using physiological and activity data. By using retrospective smartwatch data, we showed that 63% of the COVID-19 cases could be detected before symptom onset in real-time via the occurrence of extreme elevations in resting heart rate relative to the individual baseline. Our findings suggest that consumer wearables may be used for the large-scale real-time detection of respiratory infections, often pre-symptomatically, and provide an approach for managing epidemics using digital tracking and health monitoring.
About Ahmed Metwally
Ahmed Metwally is a postdoctoral scholar in the Snyder lab at Stanford University. Ahmed received his Ph.D. in Bioinformatics/Bioengineering and MS in Computer Science (focused on Deep Learning), both from the University of Illinois at Chicago (UIC) in 2018. He currently works on developing novel machine learning methods for longitudinal multimodal biomedical data fusion (omics and wearable biosensors data) to early detect cardiometabolic diseases and personalize their treatments. Ahmed has received numerous awards, such as NIH Predoctoral Translational Scientist fellowship, ISMB’20 best talk award, Stanford COVID-19 RISE Grant, second-place award at Stanford Health++ Hackathon, and many travel awards NSF, IEEE, ISCB, and UIUC for various educational and scholarly activities.
Pierre-Alexandre Fournier Abstract
The Hexoskin Connected Health platform will be discussed as an example of a biometric shirt validated for use in telehealth and clinical research. Hexoskin has the only clinically validated biometric garment which provides continuous monitoring of numerous and unique physiological parameters. Hexoskin is an enabling technology for telehealth use cases, such as remote patient monitoring, rehab, and detect the onset of illness. Hexoskin offers a unique set of high-resolution biometric data that can continuously monitor activity, sleep, cardiac and respiratory data. Projects in fields such as cardiology, respiratory, behavioral and physiological psychology, biofeedback research, sleep research, and health will be described. The Hexoskin Connected Health Platform provides researchers with accessible solutions such as the Hexoskin Dashboards, Open API, and Apps to manage, visualize, annotate, analyze, and export raw & processed health data. Data extraction tools allow access to the raw data with time series for machine learning and artificial intelligence projects.
About Pierre-Alexandre Fournier
Pierre-Alexandre Fournier is co-founder and CEO of Hexoskin, a Montreal-based company focused on clinical-grade wearable sensors and AI software for health and clinical research. Hexoskin was founded in 2006 and in 2013 released the first iPhone compatible smart clothing for health monitoring, winning several international awards. In 2018 Hexoskin launched a remote health monitoring system for astronauts on the International Space Station. Hexoskin recently reached the milestone of 100 scientific publications. Pierre-Alexandre earned his MASc and his BEng in Electrical Engineering from the Ecole Polytechnique de Montreal and became a lecturer there teaching machine learning. He completed the Harvard Business School HBX Core program with high honors. Pierre-Alexandre is also an advocate for transparency in healthcare, patient empowerment, and healthcare innovation through design.
Hosted by: Angela McIntyre, Executive Director, eWEAR Initiative
Sponsored by: PHIND Center, Department of Radiology, eWEAR Initiative
PHIND Seminar Series: Maternal Trauma History, Attachment Style, and Depression Are Associated with Broad DNA Methylation Signatures in Infants
Thalia Robakis, M.D., Ph.D.
Associate Professor
Department of Psychiatry
Mount Sinai School of Medicine
Location: Zoom
Webinar URL: https://stanford.zoom.us/s/95483174518
Dial: US: +1 650 724 9799 or +1 833 302 1536 (Toll Free)
Webinar ID: 954 8317 4518
Passcode: 179384
11:00am – 12:00pm Seminar & Discussion
RSVP Here
ABSTRACT
Background: The early environment provides many cues to young organisms that guide their development as they mature. Maternal personality and behavior are an important aspect of the environment of the developing human infant. The molecular mechanisms by which these influences are exerted are not well understood. We attempted to identify whether maternal traits could be associated with alterations in DNA methylation patterns in infants.
Methods: 32 women oversampled for history of depression were recruited in pregnancy and provided information on depressive symptoms, attachment style, and history of early life adversity. Buccal cell DNA was obtained from their infants at six months of age for a large-scale analysis of methylation patterns across 5×106 individual CpG dinucleotides, using clustering-based criteria for significance to control for multiple comparisons. Separately, associations between maternal depression, attachment style, and history of adversity and psychobehavioral outcomes in preschool-age children were examined.
Results: Tens of thousands of individual infant CpGs were alternatively methylated in association with each of the three studied maternal traits. Genes implicated in cell-cell communication, developmental patterning, growth, immune function/inflammatory response, and neurotransmission were identified. The result sets were highly coextensive among the three maternal traits, but areas of divergence exhibited intriguing parallels with behavioral outcomes.
Conclusions: Maternal personality traits are an important aspect of the infant environment that shapes offspring development in many ways. Infant genes that are epigenetically modified in reponse to maternal traits are potential candidate mediators for these effects. We have identified a large number of such genes and demonstrated parallels to clinically measurable outcomes in children.
ABOUT
Dr. Robakis is a psychiatrist with clinical and research interests in perinatal mood disorders and in the contribution of early life experiences to adult mental health and illness. She completed her M.D. as well as a Ph.D. in developmental neurobiology at Columbia University’s Medical Scientist Training Program, residency training in psychiatry at Stanford University School of Medicine, and a research fellowship in perinatal mood disorders also at Stanford. She remained on the clinical faculty at Stanford until 2019, when she accepted a position at the Icahn School of Medicine at Mount Sinai, where she is currently Associate Clinical Professor of Psychiatry and Assistant Director of the Women’s Mental Health Program.
Dr. Robakis’ research interests include the effects of early life stress and disordered attachment on risk for psychiatric illness in the perinatal period, on alterations in metabolism and cognition, and on psychobehavioral development in offspring. She is particularly interested in using epigenetic marks to help identify the biological pathways through which early life experiences exert their effects on outcomes in adulthood and intergenerationally.
Hosted by: Garry Gold, M.D.
Sponsored by the PHIND Center and the Department of Radiology
Join us for the annual Precision Health & Integrated Diagnostics Symposium. This all-day virtual event will showcase the exciting PHIND work that is going on campus wide. The featured presentations will be from current PHIND investigators and Precision Health experts. We hope you can join us and look forward to building the PHIND community together.