Going Green to Prevent Breast Cancer: The Effect of Epigallocatechin Gallate on Tumor Growth in Planaria

By: Ellia Sweeney Many people struggle with breast cancer, and while there is no cure, there are several studies being done on everyday substances that are believed to contribute to preventing the growth of cancerous tumors. Yet currently, many studies remain inconclusive. New carcinogens are found every year, as are new substances believed to fight the carcinogens. Green tea is …

Design and Optimization of Portable, High Energy Quantum-Nuclear Reactor

By: Aakash Sunkari Nuclear reactors are a promising source of clean energy due to their high energy output and capacity. Operating on either principles of nuclear fission (“splitting the atom”) or nuclear fusion (“fusing the atom), nuclear reactors are currently the only alternative source of energy that can compete with fossil fuels in the long run – other clean sources …

Machine Learning for Single Cell RNA Sequencing Data Analysis: An Unsupervised Learning Approach towards Subclonal Cell Population Identification for Target Therapy Applications Against Tumor Heterogeneity

By Anastasia Dunca In this work, I investigated machine learning algorithms for the effectiveness of statistical analysis on single cell RNA sequencing data for development of immunotherapy strategies. Single-cell RNA sequencing is an innovative tool in bioinformatics that is a group of methods that quantify the amount of RNA in a sample. This is very useful in the topic of …

A Deep Learning Model for Breast Cancer Risk Quantification using Full-Field Digital Mammography and Breast Magnetic Resonance Images

By: Ritvik Pulya Every year, almost 30% of all breast cancer cases are diagnosed late, with a 68% difference in five-year survival rates between Stage 2 and Stage 4 individuals (American Cancer Society). However, current breast cancer risk estimation models such as the Tyler-Cuzick and Gail models have moderate predictive accuracy (only slightly better than 50% or choosing an outcome …

Electrocardiogram-Based Abnormal Heartbeat Classification: A Deep Learning Approach for Arrhythmia Detection

By: Aditya Kendre Heart arrhythmias are irregular rhythms in heartbeats that affect 3 million people worldwide every year. Due to the increasing rate of ECGs recording for diagnosis, it is now possible to devolve autonomous AI driven systems to identify arrhythmias in ECGs. A convolutional neural network (CNN) was developed and trained, to achieve accuracy on par or better than …

Graphene Oxide-Based Hole Transport Layers for Organic Solar Cells

By: Yash Sahoo My project involved working with organic solar cells (use organometals instead of purified silicon; function similarly) to reduce the cost of manufacturing cells while keeping similar energy efficiency. Specifically, my project involved working with special thermoelectric polymers which were used as semiconductors with the addition of graphene-based dopants to improve specifically a single layer (hole transport layer). …

Which Factors Increase the Risk of Contracting the Common Cold?

By: Elizabeth Lesher This project was an epidemiological study that seeks to identify both risk and protective factors for the common cold (i.e., characteristics that make a person more or less susceptible to contracting the common cold). To carry out this project, I collected demographic, lifestyle, and genetic information from over 200 participants and used a range of statistical tools …

Biofilm Structure and Formation in Haemophilus ducreyi

By: Delaney Lacey Biofilms are of particular interest to the scientific and clinical community due to the variety of biotic and abiotic surfaces they can colonize. Teeth, surgical instruments, and organs (such as the lungs of cystic fibrosis patients) can all be colonized by a bacterial biofilm. Biofilm formation is characterized by the following steps: signaling by an environmental cue, …

Combating Malnutrition: The Effect of Eggs on the Development, Learning, and Memory of Drosophila melanogaster

By: Gwyneth MacDonough My project aimed to determine if malnutrition’s effects on development and cognition in Drosophila melanogaster could be reduced by consumption of eggs. I also attempted to find the optimal period for dietary intervention. To conduct my experiment, I reared seven groups of Drosophila on specific combinations of three different diets – malnourished, egg-enriched, and control. I then …