Browsing by Author "Maity, Dipak"

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    Advances in Optical Contrast Agents for Medical Imaging: Fluorescent Probes and Molecular Imaging
    (MDPI, 2025-03-18) Tripathi, Divya; Hardaniya, Mayurakshi; Pande, Suchita; Maity, Dipak; Chemistry and Chemical Biology, School of Science
    Optical imaging is an excellent non-invasive method for viewing visceral organs. Most importantly, it is safer as compared to ionizing radiation-based methods like X-rays. By making use of the properties of photons, this technique generates high-resolution images of cells, molecules, organs, and tissues using visible, ultraviolet, and infrared light. Moreover, optical imaging enables real-time evaluation of soft tissue properties, metabolic alterations, and early disease markers in real time by utilizing a variety of techniques, including fluorescence and bioluminescence. Innovative biocompatible fluorescent probes that may provide disease-specific optical signals are being used to improve diagnostic capabilities in a variety of clinical applications. However, despite these promising advancements, several challenges remain unresolved. The primary obstacle includes the difficulty of developing efficient fluorescent probes, and the tissue autofluorescence, which complicates signal detection. Furthermore, the depth penetration restrictions of several imaging modalities limit their use in imaging of deeper tissues. Additionally, enhancing biocompatibility, boosting fluorescent probe signal-to-noise ratios, and utilizing cutting-edge imaging technologies like machine learning for better image processing should be the main goals of future research. Overcoming these challenges and establishing optical imaging as a fundamental component of modern medical diagnoses and therapeutic treatments would require cooperation between scientists, physicians, and regulatory bodies.
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    Artificial Intelligence in Biomedical Engineering and Its Influence on Healthcare Structure: Current and Future Prospects
    (MDPI, 2025-02-08) Tripathi, Divya; Hajra, Kasturee; Mulukutla, Aditya; Shreshtha, Romi; Maity, Dipak; Chemistry and Chemical Biology, School of Science
    Artificial intelligence (AI) is a growing area of computer science that combines technologies with data science to develop intelligent, highly computation-able systems. Its ability to automatically analyze and query huge sets of data has rendered it essential to many fields such as healthcare. This article introduces you to artificial intelligence, how it works, and what its central role in biomedical engineering is. It brings to light new developments in medical science, why it is being applied in biomedicine, key problems in computer vision and AI, medical applications, diagnostics, and live health monitoring. This paper starts with an introduction to artificial intelligence and its major subfields before moving into how AI is revolutionizing healthcare technology. There is a lot of emphasis on how it will transform biomedical engineering through the use of AI-based devices like biosensors. Not only can these machines detect abnormalities in a patient's physiology, but they also allow for chronic health tracking. Further, this review also provides an overview of the trends of AI-enabled healthcare technologies and concludes that the adoption of artificial intelligence in healthcare will be very high. The most promising are in diagnostics, with highly accurate, non-invasive diagnostics such as advanced imaging and vocal biomarker analyzers leading medicine into the future.
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    Hydrogel Innovations in Biosensing: A New Frontier for Pancreatitis Diagnostics
    (MDPI, 2025-03-03) Sutar, Prerna; Pethe, Atharv; Kumar, Piyush; Tripathi, Divya; Maity, Dipak; Chemistry and Chemical Biology, School of Science
    Pancreatitis is a prominent and severe type of inflammatory disorder that has grabbed a lot of scientific and clinical interest to prevent its onset. It should be detected early to avoid the development of serious complications, which occur due to long-term damage to the pancreas. The accurate measurement of biomarkers that are released from the pancreas during inflammation is essential for the detection and early treatment of patients with severe acute and chronic pancreatitis, but this is sub-optimally performed in clinically relevant practices, mainly due to the complexity of the procedure and the cost of the treatment. Clinically available tests for the early detection of pancreatitis are often time-consuming. The early detection of pancreatitis also relates to disorders of the exocrine pancreas, such as cystic fibrosis in the hereditary form and cystic fibrosis-like syndrome in the acquired form of pancreatitis, which are genetic disorders with symptoms that can be correlated with the overexpression of specific markers such as creatinine in biological fluids like urine. In this review, we studied how to develop a minimally invasive system using hydrogel-based biosensors, which are highly absorbent and biocompatible polymers that can respond to specific stimuli such as enzymes, pH, temperature, or the presence of biomarkers. These biosensors are helpful for real-time health monitoring and medical diagnostics since they translate biological reactions into quantifiable data. This paper also sheds light on the possible use of Ayurvedic formulations along with hydrogels as a treatment strategy. These analytical devices can be used to enhance the early detection of severe pancreatitis in real time.