Exploring Validated Instruments for Measuring Quality of Life (QoL) in Patients Undergoing Resection of a Meningioma

*Under Dr. Debraj Mukherjee, M.D*

Meningiomas are benign, often slow-growing, intracranial tumors that often present due to the symptoms produced by mass effect as the tumors compress surrounding tissues. These symptoms greatly impact the quality of life (QOL) of patients with a meningioma. However, it is unclear how providers can best quantify these changes. This study aims to identify instruments that have been validated for measuring QOL and patient-reported outcomes (PROs) for patients with meningiomas. We designed a search string to identify studies of patients with intracranial meningiomas that include QOL tools or PRO surveys as part of their outcomes. The search string was translated for PubMed and Embase. The studies identified through these three databases were screened for the inclusion of at least 10 adult patients with a meningioma who completed a QOL assessment or PRO survey. The search string resulted in 181 abstracts of which 123 were excluded. The 58 studies in full-text review were screened, resulting in the exclusion of 20 studies. Thirty-eight papers met the inclusion criteria. These studies validated a variety of instruments including broad PRO surveys, anatomically-based QOL tools, and disease-specific symptom control and functional status assessments. Each study demonstrated the value of these measures for assessing the efficacy of treatment and validated their role in guiding future management. The authors identified 38 studies that utilized various PRO metrics to measure quality of life in patients who were being treated for a meningioma. These findings demonstrate the wide variety of instruments that have been validated for this purpose and highlight the need for improved organization and disease-driven tools for measuring these outcomes.

*Under Dr. John Carey, M.D*

Superior semicircular canal dehiscence syndrome (SCDS) is a rare and often underdiagnosed condition characterized by a thinning or absence of the bone over the superior semicircular canal of the inner ear. This anomaly leads to debilitating symptoms, including vertigo, hearing loss, and tinnitus, which significantly impact the quality of life for affected individuals. 

Surgical intervention is frequently required to alleviate these symptoms, but optimal treatment strategies and long-term recovery outcomes remain poorly understood. Our study aims to develop the world’s largest clinical database for patients diagnosed and surgically treated for SCDS, utilizing RedCap to manage data from approximately 1,800 patients. The database includes detailed patient information, pre- and post-operative symptom assessments, surgical approaches, and long-term follow-up data. By analyzing these data, we seek to identify key factors influencing surgical outcomes, symptom management, and recovery. Our findings will provide crucial insights into improving surgical care, enhancing long-term outcomes, and ultimately guiding clinical decision-making to improve the quality of life for patients with SCDS.

*Under Dr. Ernst Niebur (JHU) and Dr. Jan Pielage (University of Kaisersluatern)*

The Mushroom Body Output Neuron (MBON) – 18 in Drosophila melanogaster plays a crucial role in the sensory association and memory mechanisms that underlie learning and behavior. Understanding the neural circuits and processes involved in memory formation is fundamental to advancing our knowledge of cognitive functions in both invertebrates and higher organisms. However, the precise mechanisms through which sensory inputs are integrated and lead to memory encoding remain poorly understood. Our research focused on developing a computational model of MBON-18 to explore these memory mechanisms and sensory associations. Under the mentorship of Dr. Ernst Niebur, we built a detailed model to simulate the neuronal activity of MBON-18 and its role in memory formation. This project was part of an international research collaboration with the University of Kaiserslautern in Germany, under the guidance of Dr. Jan Pielage. We integrated electrophysiological data into our model and performed simulations using NEURON and Python to gain deeper insights into the neural processes involved in memory. Our findings aim to contribute to a better understanding of memory encoding at the cellular and circuit levels, with broader implications for neuroscience research.

The effect of koumine on social interaction and locomotion of a traumatic injury induced Drosophila melanogaster offspring model (mimicking preterm birth defects) 

Each year, around 15 million infants are born premature, often resulting in birth defects that affect social interaction and motor skills. The fruit fly, Drosophila melanogaster, serves as a model organism as its behaviors mirror premature birth defects, including anxiety, agoraphobia, and impaired movement. Maternal flies subjected to traumatic injury through a High Impact Trauma (HIT) device produce progeny with decreased social interaction and locomotion. Maternal trauma serves as a model for premature birth defects among fly progeny. Social interaction is assessed through a social space assay, which defines a fly’s nearest neighbor as its social space. Shorter distances between flies indicate greater social interaction, as they tend to cluster more closely together. Locomotion is measured using a climbing assay, where the progeny flies are tested on their ability to perform negative geotaxis successfully. Gelsemium sempervirens (GS) extract administration improves social interaction levels among fly progeny mimicking preterm birth defects, and increased locomotion levels in the mice model for chronic stress. Koumine is a major chemical compound of Gelsemium sempervirens and the study investigates the chemical as the active ingredient driving the increase in social interaction and locomotion. My hypothesis that administering koumine to maternal flies with traumatic injury improves social interaction and locomotion levels in progeny is supported by the significant differences observed. Fly progeny exhibited increased social interaction and locomotion when koumine was administered at the maternal level. The research provides a pathway for novel drug discovery, employing koumine as a treatment for premature birth defects in neonates.

Strategic reduction of Plasmodium falciparum infant mortality in Nigeria: Enhancing healthcare equity through medical drone delivery of the RTS,S/AS01 vaccine 

During his time at Yale University in the 2023 Summer, Saumik and his team conducted research on sustainable solutions in global health for malaria in Nigeria under the guidance of Edwin Ruiz Fuentes, M.P.H. Under the Solving Global Challenges (UN Sustainability Development Goals) program, he developed innovative approaches to alleviate hunger, studied enhancing sanitation infrastructure, driving hygiene education and socio-behavior change as well as waste management technology tied to sustainable agricultural strategies and energy production.

Malaria is the leading cause of child and infant mortality in Nigeria, due to the many healthcare disparities and inadequate access to current treatments. By integrating self-assembled, automated, GPS-routed, electronic drones and optimizing the storage system, our research aims to propose a cutting-edge, sustainable ethical solution for the distribution of the RTS,S/AS01 vaccine. This research can shine light on how to effectively combat similar health crises via the usage of medical delivery drones for mass administration in Nigeria. 

Investigating the effectiveness of Convolutional

Neural Networks (CNNs) on retinal disease diagnosis

using MURED dataset

Saumik and his team researched on using innovative ways to diagnose retinal diseases, especially for rural and elderly population using machine learning with neural networks in a fast-processing image analysis algorithm. From his clinical experience in ophthalmology, Saumik was able to provide valuable insight in both constructing the algorithm and current technology used in the ophthalmology field. The research was accepted for publication in the IEEE's 2nd International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI-2024).