To help advance care, the DNA Microarray Laboratory within the Department of Pathology and Laboratory Medicine is participating in a new multi-institutional study aimed at validating an up-and-coming genomic technology, with the goal of getting it one step closer to clinical application.

As part of a study agreement with San Diego-based Bionano Genomics, Medical Center researchers are testing the company’s Saphyr optical genome mapping (OGM) instrument, as a way to help clinical labs identify genetic abnormalities. Whether the patient is a pregnant mother, a young child, or someone with rare cancer or genetic disease, detection of genetic abnormalities can be a first step in reaching an accurate diagnosis and targeted therapy.

The microarray lab is now running hundreds of (previously tested and de-identified) abnormal patient samples on Saphyr. The data will then be compared to those yielded by traditional methods: DNA microarray, FISH, and karyotyping.

M. Anwar Iqbal, professor and director of the DNA Microarray Lab, explains that each of these methods has its own strengths and weaknesses for a variety of reasons. In simple terms, there are certain abnormalities that can be detected by one method but may go undetected by another, so it’s common to test the same patient sample with more than one method.

Hopefully, future developments in genomics may provide a single platform for all types of tests. The benefit of OGM, experts say, is that it combines the best of all three into one by scanning the entire genome to flag and report any and all possible abnormalities. Read more.

The Goergen Institute for Data Science (GIDS) seed funding awards for 2021 go to collaborative projects that extend from the Medical Center to Eastman School of Music. The goal is to support projects that could eventually attract major external funding, with a particular focus on work aligned with data science research priorities.

• Designing Effective Intervention to Promote Green Products in Online Shopping Platforms: Ehsan Hoque, computer science, principal investigator. Karen Berger, earth and environmental sciences, co-PI. Award amount: $19,831.
  The project centers on designing an intervention study to analyze the effect of providing sustainability information and product eco-friendliness ratings on e-commerce websites; it explores whether including such information will encourage consumers to buy more eco-friendly products and product alternatives.
• Artificial Intelligence for Effective Communication on Health Effects of Electronic Cigarettes through Instagram:  Dongmei Li, clinical and translational research, public health sciences, obstetrics and gynecology, PI. Chenliang Xu, computer science, co-PI. Award amount: $20,000.
  The project will develop a statistical model to predict likes on Instagram for images related to educating and warning the public about the risks of vaping. The statistical model will explore both post-level features (number of hashtags, image features, caption features extracted by deep learning methods) and user-level features (user’s number of followers, number of posts) to determine which features are most successful at promoting vaping awareness.
• Automatic Rendering of Augmented Effects in Immersive Concert: Zhiyao Duan, electrical and computer engineering and computer science, PI. Matthew Brown, Eastman School of Music and Raffaella Borasi, Warner School of Education, co-PIs. Award amount: $18,854.
  The project will develop a proof-of-concept system that can automatically coordinate live music performances with multimedia content, such as visual effects. The system will synchronize annotations in the musical score with a music recognition system; it will be built on preliminary music score-following algorithm work, QLab software, and the Eastman School of Music’s TableTopOpera system.
• Interactive Climate Network Exploration over Real-Time Data:  Fatemeh Nargesian, computer science, PI. Gourab Ghoshal, physics and astronomy, mathematics, and computer science, co-PI. Award amount: $20,000.
  The project will develop a software solution to process, analyze, and visualize global climate data that varies across time and space, using network-science tools.
• Physics-Aware Learning-Based Ultrasound Tumor Ablation Monitoring: Ajay Anand, data science, PI. Mujdat Cetin, data science and electrical and computer engineering, and Diane Dalecki, biomedical engineering and electrical and computer engineering, co-PIs. Award amount: $20,000.
  The project aims to reconstruct the 3-D temperature distribution in an ultrasound using sparse thermometry data from the periphery of the heating zone, and the underlying heat transfer process. The applications are in tumor ablation for the treatment of cancers in organs such as liver, kidney, and prostate. In such treatments, heat energy is applied using Radio-frequency or High Intensity Focused Ultrasound (HIFU). The temperature rapidly rises and coagulates the tissue to treat the tumors.

Jiebo Luo, professor of computer science, who has received the 2021 Award for Outstanding Technical Contributions to Multimedia Computing, Communications and Applications from the Association for Computing Machinery (ACM) Special Interest Group on Multimedia (SIGMM). The award is given in recognition of his outstanding, pioneering, and continued research contributions in the areas of multimedia content analysis and social media analytics, and for outstanding and continued service to the multimedia community.

A new, more secure, and convenient way for researchers across the University to access and analyze clinical data containing protected health information (PHI) is now available.

The Secure Environment for Research Data Analytics (SERDA) offers a virtual collaborative workspace with free select analytical tools and secure data storage and backup to help researchers work with data and comply with federal data privacy laws.

A host of educational resources and learning modules in the design and conduct of clinical and population health studies is available in the UR CTSI’s Research Education Hub on Blackboard.

The modules are designed to provide professionals and trainees across the entire translational research spectrum with an overview. Read more.

The UR CTSI’s Digital Health Seedling Award provides up to $25,000 to support research that advances the development, approval, adoption and use of innovative digital health tools, methods and approaches.

The one-year award is available to full-time faculty at the University of Rochester who are studying digital health approaches, tools and data including utilizing sensors and mobile technologies, electronic medical records, data from registries and other real-world data and approaches to advance clinical research and address regulatory science needs. Apply by Monday, February 7, 2022.