Physical Sciences and Mathematics Commons^™

Treatment Selection Using Prototyping In Latent-Space With Application To Depression Treatment, Akiva Kleinerman, Ariel Rosenfeld, David Benrimoh, Robert Fratila, Caitrin Armstrong, Joseph Mehltretter, Eliyahu Shneider, Amit Yaniv-Rosenfeld, Jordan Karp, Charles F. Reynolds, Gustavo Turecki, Adam Kapelner

Publications and Research

Machine-assisted treatment selection commonly follows one of two paradigms: a fully personalized paradigm which ignores any possible clustering of patients; or a sub-grouping paradigm which ignores personal differences within the identified groups. While both paradigms have shown promising results, each of them suffers from important limitations. In this article, we propose a novel deep learning-based treatment selection approach that is shown to strike a balance between the two paradigms using latent-space prototyping. Our approach is specifically tailored for domains in which effective prototypes and sub-groups of patients are assumed to exist, but groupings relevant to the training objective are not …

The Temperature-Dependent Conformational Ensemble Of Sars-Cov-2 Main Protease (Mpro), Ali Ebrahim, Blake T. Riley, Desigan Kumaran, Babak Andi, Martin R. Fuchs, Sean Mcsweeney, Daniel A. Keedy

Publications and Research

The COVID-19 pandemic, instigated by the SARS-CoV-2 coronavirus, continues to plague the globe. The SARS-CoV-2 main protease, or M^pro, is a promising target for development of novel antiviral therapeutics. Previous X-ray crystal structures of M^pro were obtained at cryogenic temperature or room temperature only. Here we report a series of high-resolution crystal structures of unliganded M^pro across multiple temperatures from cryogenic to physiological, and another at high humidity. We interrogate these datasets with parsimonious multiconformer models, multi-copy ensemble models, and isomorphous difference density maps. Our analysis reveals a temperature-dependent conformational landscape for M^pro, including …

Molecular Dynamics Simulations Of Self-Assemblies In Nature And Nanotechnology, Phu Khanh Tang

Dissertations, Theses, and Capstone Projects

Nature usually divides complex systems into smaller building blocks specializing in a few tasks since one entity cannot achieve everything. Therefore, self-assembly is a robust tool exploited by Nature to build hierarchical systems that accomplish unique functions. The cell membrane distinguishes itself as an example of Nature’s self-assembly, defining and protecting the cell. By mimicking Nature’s designs using synthetically designed self-assemblies, researchers with advanced nanotechnological comprehension can manipulate these synthetic self-assemblies to improve many aspects of modern medicine and materials science. Understanding the competing underlying molecular interactions in self-assembly is always of interest to the academic scientific community and industry. …

Enhanced Platinum (Ii) Drug Delivery For Anti-Cancer Therapy, Marek T. Wlodarczyk

Dissertations, Theses, and Capstone Projects

Over the years, anti-cancer therapies have improved the overall survival rate of patients. Nevertheless, the traditional free drug therapies still suffer from side effects and systemic toxicity, resulting in low drug dosages in the clinic. This often leads to suboptimal drug concentrations reaching cancer cells, contributing to treatment failure and drug resistance. Among available anti-cancer therapies, metallodrugs are of great interest. Platinum (II)-based agents are highly potent and are used to treat many cancers, including ovarian cancer (OC). Cisplatin (cis-diaminedichloroplatinum (II)) is the first Food and Drug Administration (FDA)-approved metallodrug for treatment of solid tumors, and its mechanism …

Decoding Clinical Biomarker Space Of Covid-19: Exploring Matrix Factorization-Based Feature Selection Methods, Farshad Saberi-Movahed, Mahyar Mohammadifard, Adel Mehrpooya, Mohammad Rezaei-Ravari, Kamal Berahmand, Mehrdad Rostami, Saeed Karami, Mohammad Najafzadeh, Davood Hajinezhad, Mina Jamshidi, Farshid Abedi, Mahtab Mohammadifard, Elnaz Farbod, Farinaz Safavi, Mohammadreza Dorvash, Shahrzad Vahedi, Mahdi Eftekhari, Farid Saberi-Movahed, Iman Tavassoly

Publications and Research

One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients’ characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 …

Pattern Of Use Of Electronic Health Record (Ehr) Among The Chronically Ill: A Health Information National Trend Survey (Hints) Analysis, Rose Calixte, Sumaiya Islam, Zainab Toteh Osakwe, Argelis Rivera, Marlene Camacho-Rivera

Publications and Research

Effective patient–provider communication is a cornerstone of patient-centered care. Patient portals provide an effective method for secure communication between patients or their proxies and their health care providers. With greater acceptability of patient portals in private practices, patients have a unique opportunity to manage their health care needs. However, studies have shown that less than 50% of patients reported accessing the electronic health record (EHR) in a 12-month period. We used HINTS 5 cycle 1 and cycle 2 to assess disparities among US residents 18 and older with any chronic condition regarding the use of EHR for secure direct messaging …

Covid-19 Impact On Radiology Students’ Distance Learning (Summer 2021), Mary Lee, Jason Chan, Cheryann Jackson-Holmes, Renzo Marmolejo, Zoya Vinokur

Publications and Research

The Radiological Technology students have adjusted from the urgent distance learning that was enacted in the Spring of 2020, to the hybrid distance learning that is currently in place. This hybrid distance learning is the same way the incoming class of radiological technology students were taught. Both cohorts of students were tracked over the year by online anonymous surveys. We wanted to know how students were adapting to distance learning, if their focus and motivation varied over the course of the year due to changing pandemic conditions. For the students that were working, what impact did it have on their …

Covid-19 Multi-Targeted Drug Repurposing Using Few-Shot Learning, Yang Liu, You Wu, Xiaoke Shen, Lei Xie

Publications and Research

The life-threatening disease COVID-19 has inspired significant efforts to discover novel therapeutic agents through repurposing of existing drugs. Although multi-targeted (polypharmacological) therapies are recognized as the most efficient approach to system diseases such as COVID-19, computational multi-targeted compound screening has been limited by the scarcity of high-quality experimental data and difficulties in extracting information from molecules. This study introduces MolGNN , a new deep learning model for molecular property prediction. MolGNN applies a graph neural network to computational learning of chemical molecule embedding. Comparing to state-of-the-art approaches heavily relying on labeled experimental data, our method achieves equivalent or superior prediction …

Design, Synthesis And Evaluation Of Molecules With Selective And Poly-Pharmacological Actions At D1r, D3r And Sigma Receptors, Pierpaolo Cordone

Dissertations, Theses, and Capstone Projects

The dopamine D3 receptor (D3R) is one of the most studied receptors involved in drug addiction. One of the most common strategies to treat substance use disorders is via D3R antagonism. The majority of the D3R antagonists synthesized so far have poor pharmacokinetic properties and/or lack selectivity toward D3R. In this thesis, the design, synthesis and biological evaluation of novel molecules that target the dopamine D1 receptor (D1R), D3R and the serendipitous discovery of molecules that target s receptors will be described.

Chapter 1 presents a survey of the fundamental pharmacology of D1R, D3R and s receptors and the therapeutic …

Intangible Cultural Heritage: A Benefit To Climate-Displaced And Host Communities, Gül Aktürk, Martha B. Lerski

Publications and Research

Climate change is borderless, and its impacts are not shared equally by all communities. It causes an imbalance between people by creating a more desirable living environment for some societies while erasing settlements and shelters of some others. Due to floods, sea level rise, destructive storms, drought, and slow-onset factors such as salinization of water and soil, people lose their lands, homes, and natural resources. Catastrophic events force people to move voluntarily or involuntarily. The relocation of communities is a debatable climate adaptation measure which requires utmost care with human rights, ethics, and psychological well-being of individuals upon the issues …

Interfacial Dynamics And Ionic Transport Of Radiologic Contrast Media In Carbohydrate Matrix: Utility And Limits Of X-Ray Imaging, Lin Mousa, Hayley Sanchez, Subhendra Sarkar, Zoya Vinokur

Publications and Research

Hello, our names are Lin Mousa and Hayley Sanchez, this semester we participated in a research project dedicated to analyzing the interactions of contrast media with the molecular components of fruits to compare how they would react with the human brain. This project involved the injection of fruits with varying contrasts and the imaging of the diffusion and interactions of the contrast within the fruits with X-rays. With setup technical parameters on the x-ray equipment images were taken with identical setups at an hourly rate for several days. The final results of this experiment indicated that contrasts such as Gadolinium …

Human Ace2‑Functionalized Gold “Virus‑Trap” Nanostructures For Accurate Capture Of Sars‑Cov‑2 And Single‑Virus Sers Detection, Yong Yang, Yusi Peng, Chenglong Lin, Li Long, Jingying Hu, Jun He, Hui Zeng, Zhengren Huang, Zhi-Yuan Li, Masaki Tanemura, Jianlin Shi, John R. Lombardi, Xiaoying Luo

Publications and Research

The current COVID-19 pandemic urges the extremely sensitive and prompt detection of SARS-CoV-2 virus. Here, we present a Human Angiotensin-converting-enzyme 2 (ACE2)-functionalized gold “virus traps” nanostructure as an extremely sensitive SERS biosensor, to selectively capture and rapidly detect S-protein expressed coronavirus, such as the current SARS-CoV-2 in the contaminated water, down to the single-virus level. Such a SERS sensor features extraordinary 106- fold virus enrichment originating from high-affinity of ACE2 with S protein as well as “virus-traps” composed of oblique gold nanoneedles, and 109- fold enhancement of Raman signals originating from multicomponent SERS effects. Furthermore, the identification standard of virus …