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Agent-Dependent Enhanced Optical Projection Tomography:
With the conventional cancer detection methods having a sensitivity of hardly 40%-70%, an estimate of 50,000 women per year are at risk of getting misdiagnosed with stage I/II cancer when it is actually at stage III. This fact emphasizes the fact that early detection is crucial, especially when we are talking about a lethal disease such as cancer.
This 5-year grant research focuses on developing a molecular imaging methodology that will help detect breast cancer with a sensitivity >95% without increasing the rate of false positives in a comparatively reduced overall pathology duration. The goal is to design, optimize and evaluate ADEPT's clinical utility. My assignment being in the wet lab includes roles such as sample handling, and optimizing the staining and rinsing protocols along with my fellow teammates.
The project is being executed at the Medical Imaging Research Centre (MIRC) in Illinois Institute of Technology, Chicago.
Amplification technique for ultra-sensitive detection of proteins:
The abundance of diseases in today’s world demands efficient diagnosis and treatment plans. The efficacy of a lot of treatments depends on when the diagnosis is actually done. If detected early, there is a better chance of improvement. To do so, proteins are commonly being used as biomarkers for a variety of diseases ranging from cancer to Alzheimer’s.
I have worked on designing a protein detection assay that incorporates an enzyme-free signal amplification technique. It can utilize superparamagnetic beads in order to produce a highly sensitive assay that can perform detection by the measurement of customized real-time fluorescent probes.
The work was carried out in the Microfluidics and Fluorescence Microscopy Laboratory, at the Illinois Institute of Technology, Chicago.
Screening for Type 2 Diabetes:
This research study was aimed to understand the prospect of infrared thermography in early diagnosis of Type 2 Diabetes. The objective was to discover a non-invasive diagnostic tool for this purpose and compare its performance with an existing tool, namely Indian Diabetic Risk Score. The study was conducted for over 100 volunteer subjects of different age groups. Amperometric data and medical history survey data were statistically analysed using the SPSS software. To know more, click here.
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