Young Scholar’s Program 2018

Participating Labs

YSP 2018 Website

LabYSP StudentsTitleAbstract
Faculty: Mansoor Amiji

Mentor: Neha Parayath
Pamina Mejia
Dinesh Sangadi
Synthesis of Gold Modified Silica Nanotubes for Optical Tomography Imaging in Diagnosis of Diabetic RetinopathyNewer approaches are constantly being designed to enhance the effectiveness of cancer therapies. The tumor is formed of different types of cells such as immune cells and fibroblast along with the cancer cells. Macrophages which are a type of immune cells comprise 50% of the tumor mass. Macrophages generally exist in two different forms, the M1 form (supports tumor suppression) and the M2 form (supports tumor progression). Most macrophages which are present in the tumors are of the M2 form which helps in growth and metastasis of the tumors. Studies have shown that this M2 form can be converted to M1 form by use of certain nucleic acids. Our aim is to use these nucleic acids to convert the macrophages present in the tumors from M2 form to M1 form, in turn supporting tumor suppression. Use of nanoformulation is an effective strategy for delivery of cancer therapeutics. Nanosized formulations penetrate the tumor tissue through the leaky tumor vasculatures and are retained in the tumor tissues due to the impaired lymphatic drainage. Thus, we aim to use nanoformulations to deliver nucleic acids for macrophage polarization in tumor tissue. This approach when used in combination can result in effective anticancer therapy for lung cancer.
Faculty: Ambika Bajpayee

Mentor: Armin Vedadghavami
Salima Amiji
Lily Shi
Drug Delivery to Avascular TissuesResearch is focused on designing charged biomaterials using peptides, proteins and polymers for targeted drug delivery to connective tissues for treatment of common musculoskeletal degenerative diseases. A new project in the lab focusses on drug delivery to the back of the eye where students will learn how to culture eye organ, intravitreal injections and then evaluating transport kinetics of drug carriers.
Faculty: Eno Ebong

Mentors: Nandita Bal,
Ian Harding
Jabar Awad
Christopher Ramirez
Blood Vessel Cell Sugar Coating, Reactive Oxygen Species, and InflammationAtherosclerosis, a cardiovascular disease characterized by the buildup of fatty plaques in the blood vessel wall, is the number one cause of death worldwide. Interestingly, atherosclerotic plaques develop in areas characterized by disturbed blood flow and, subsequently, altered shear stresses. Additionally, blood vessels at atherosclerotic plaques are stiffer compared to age-matched, healthy controls. These findings collectively implicate the importance of mechanotransduction, the conversion of mechanical forces into biochemical signals, in the development and progress of atherosclerosis. To better understand the relationship between mechanotransduction and atherosclerosis, we will develop monolayers of endothelial cells, the innermost cell of the vasculature, on synthetic hydrogels of varying stiffnesses. Specifically, endothelial cells will be grown on polyethylene glycol hydrogels with either healthy- or atherosclerotic-like stiffnesses and evaluated for monolayer formation. Furthermore, the glycocalyx of endothelial cells, a known mechanotransducer, will be analyzed. Such investigations will provide a better understanding of the relationship between glycocalyx-induced mechanotransduction and atherosclerosis.
Faculty: Samuel Felton

Mentors: Akshay Vaidya, Marcos Oliveira, Chang Liu
Natalie Daly
Brendan Matulis
Characterization of Fabrication Processes for Soft RobotsSoft Robots can be quickly fabricated using molds and curable polymers. However, this process results in fabrication errors and variations between designs. We will systematically test and measure the effect of different parameters on robot quality including stiffness, resolution, and strength.
Faculty: Tali Konry

Mentors: Wenjing Kang,
Saheli Sarkar 
Taylor Dill
Devin Hartigan
Lab on a ChipAcquired drug resistance is a key factor in the failure of chemotherapy. Due to intratumoral heterogeneity, cancer cells depict variations in intracellular drug uptake and efflux at the single cell level, which may not be detectable in bulk assays. In this study we present a droplet microfluidics-based approach to assess the dynamics of drug uptake, efflux and cytotoxicity in drug-sensitive and drug-resistant breast cancer cells. An integrated droplet generation and docking microarray was utilized to encapsulate single cells as well as homotypic cell aggregates. Drug-sensitive cells showed greater death in the presence or absence of Doxorubicin (Dox) compared to the drug-resistant cells. We observed heterogeneous Dox uptake in individual drug-sensitive cells while the drug-resistant cells showed uniformly low uptake and retention. Dox-resistant cells were classified into distinct subsets based on their efflux properties. Cells that showed longer retention of extracellular reagents also demonstrated maximal death. We further observed homotypic fusion of both cell types in droplets, which resulted in increased cell survival in the presence of high doses of Dox. Our results establish the applicability of this microfluidic platform for quantitative drug screening in single cells and multicellular interactions.
Faculty: Ryan Koppes

Mentors: Tess Torregrosa,
Jon Soucy
Gabrielle Dieu
Heidi Yap
Immunoregulation of Cardiac Output in VitroHere, we aim to design a custom chip to mimic the interactions of the heart and the autonomic nervous system (ANS). In vitro models provide numerous benefits over their in vivo counterparts by reducing variability, lowering cost, and by allowing for the inclusion of knockout transgenic cell lines used to study specific genes. Developing a functional model of the cardiac ANS will allow for an improved fundamental understanding of the relationship between cholinergic and adrenergic neuron populations that act in an opposing manner. Additionally, by studying the cellular responses to physiological relevant changes, new therapeutic targets may be identified to treat cardiovascular disease.
Faculty: Philip Larese-Casanova
Luke Eckel
Nicholas Hudanich
Water Pollutant Behavior Under Different Reaction Kinetics and Flow RegimesNanomaterial-enabled technologies and products are now pervasive in society. However, the manufacturing, use, and disposal of these products may result in release of nanomaterials to the environment. Exposure to these nanomaterials may pose risks to human and ecosystem health, particularly for ones containing toxic elements. Nanomaterials also pose a threat by leaching toxic chemicals into water. This research experience will study how both nanomaterials and dissolved water pollutants behave in water under different reaction kinetics and flow regimes within model reactor vessels the students construct. Safe, non-toxic versions of the pollutants will be used as model materials.
Faculty: Jose Martinez Lorenzo

Mentors: Juan Heredia,
Ali Molaei
Nabil Kebichi
Liane Xu
Cost Effective Sensors for 4D mm-Wave Airport Security SystemsOne of the key features of next generation sensing and imaging systems will be the ability to maximize the sensing capacity, that is, the information-transfer efficiency between the pixels in the imaging region and the data measured by the system. This can occur when the mutual information of successive measurements is as low as possible. One way to achieve this goal is to dynamically control the “wave field information” that is encoded in several dimensions in any given sensing experiment – a methodology known as multi-dimensional coding. Recently, we have been working on the fundamental science, computational models and imaging algorithms needed for developing a novel high-capacity Compressive Imaging System, capable of performing multi-dimensional codification. In our system, this codification will be achieved by feeding a Compressive Reflector with a Multiple-Input-Multiple-Output (MIMO) milliliter wave radar system. As a result, one can make 3D images at higher rates, thus enabling the detection of security threats while the target is “on-the-move.” Our goal is to enable the detection of security threats in open environments where people are walking at speeds of about 1 m/s. Machine and Deep Learning techniques are also being developed to perform the detection, identification and classification of targets. Concretely, applying transfer learning to some pre-trained Convolutional Neural Networks (CNN), region-based classification of the structures in an image can be done. The fusion of the mm-wave radar imaging techniques with the classification capabilities of the CNNs allows improvements in the identification and detection of threat targets.
Faculty: Marvin Onabajo

Mentors: Mengting Yan,
Gaurav Jha
Rohit Chopra
Brian Estevez
Digitally Programmable Variable Gain Amplifier for Wireless Communication ApplicationsAnalog circuits play a key role in devices for the wireless transmission and reception of information. They have to be designed with high performance and reliability. However, the quality of analog circuits depends strongly on variations of electronic component parameters and manufacturing processes. A general research approach aimed at improving analog circuits in the presence of random variations involves the measurement of key performance parameters in combination with automatic tuning for optimum performance through the aid of circuits in the same system. To allow the tuning of analog circuits with digital control, programmable elements have to be incorporated into the analog circuits. This approach will be investigated in this research project by prototyping a digitally controllable variable gain amplifier.
Faculty: Robert Platt

Mentor: Colin Kohler
Aiman Najah
Halleluia Zeyohannes
Assistive Robotic Scooter ProjectMany people with motor disabilities are unable to complete activities of daily living (ADLs) without assistance. However, there are very few options for using robotic manipulation technologies to help these people perform the manipulation tasks required by ADLs. To this end, the HelpingHands lab has developed a robotic system consisting of a robot arm mounted to an assistive mobility device which enables users to grasp and manipulate novel objects in complex environments. Using grasp detection algorithms we can achieve a success rate of 90% in a non-mobile scenario and 72% in a mobile scenario. This project explores the potential of under actuated grippers, such as the Yale OpenHand, to improve these grasping success rates.

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