Dry Eyes & Ocular Surface
The ocular surface and its dysfunction is a key area of interest at CORE. Dry eye disease and conditions affecting the ocular surface are a growing concern in the population. Coupled with the ocular microbiome, this is a rich vein of research interest at LVPEI.
Principle investigators
Dr. Swati Singh’s current focus of interest is improving tear production in patients with dry eye disease. Her pioneering work in dry eye diagnostics earned her recognition as one of the top talents in India.
Dr Singh was the first to demonstrate the in-vivo transcanalicular view of the valve of Rosenmüller, tear secretion from transplanted minor salivary glands, and innovative clinical techniques for the evaluation of the lacrimal gland and salivary secretion in patients with dry eyes.
Dr. Kotakonda Arunasri’s research team is focused on the Ocular Bacterial microbiome, mycobiome and virome to understand the disease pathology associated with the ocular infections or inflammatory disorders by metagenomic sequencing approach.
Her current research on tear film microbiome involves understanding the changes in ocular surface microbiome in dry eye disease.
Dr Sachin Shukla focuses on the biology and therapeutic applications of mesenchymal stem cells (MSCs) for potentially blinding ocular surface disorders.
His current research interests involve studying the role of MSC-derived secretome and extracellular vesicles in ocular surface repair and immunomodulation following injury, infection, and allergy.
Dr Charanya Ramachandran pursues research work on the corneal endothelium. Her lab focuses on understanding the basic biology of corneal endothelial cells and in determining the molecular mechanisms driving endothelial dysfunction.
She works on establishing cell culture protocols for patient transplantation and developing biomaterials for engineering the endothelial layer for transplantation.
Publications
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Donations to research at LVPEI has enabled some of the most cutting-edge work that has focused on delivering impact in a low-resource setting.
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