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34 results on '"Koganti, Raghuram"'

5. Cellular senescence implication in mustard keratopathy

Author

Soleimani, Mohammad, Baharnoori, Seyed Mahbod, Cheraqpour, Kasra, Momenaei, Bita, Mirshahi, Reza, Chow, Collin, Shahjahan, Sumaiya, Nguyen, Tara, Ashraf, Mohammad Javad, Huang, Xiaoke, Koganti, Raghuram, Cheraghpour, Makan, Ghassemi, Mahmood, and Djalilian, Ali R.

Published
2023
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15. Artificial Intelligence and Infectious Keratitis: Where Are We Now?

Author

Soleimani, Mohammad, Cheraqpour, Kasra, Sadeghi, Reza, Pezeshgi, Saharnaz, Koganti, Raghuram, and Djalilian, Ali R.

Subjects
ARTIFICIAL intelligence, KERATITIS, DELAYED diagnosis, OPHTHALMOLOGIC emergencies, CONFOCAL microscopy
Abstract

Infectious keratitis (IK), which is one of the most common and catastrophic ophthalmic emergencies, accounts for the leading cause of corneal blindness worldwide. Different pathogens, including bacteria, viruses, fungi, and parasites, can cause IK. The diagnosis and etiology detection of IK pose specific challenges, and delayed or incorrect diagnosis can significantly worsen the outcome. Currently, this process is mainly performed based on slit–lamp findings, corneal smear and culture, tissue biopsy, PCR, and confocal microscopy. However, these diagnostic methods have their drawbacks, including experience dependency, tissue damage, cost, and time consumption. Diagnosis and etiology detection of IK can be especially challenging in rural areas or in countries with limited resources. In recent years, artificial intelligence (AI) has opened new windows in medical fields such as ophthalmology. An increasing number of studies have utilized AI in the diagnosis of anterior segment diseases such as IK. Several studies have demonstrated that AI algorithms can diagnose and detect the etiology of IK accurately and fast, which can be valuable, especially in remote areas and in countries with limited resources. Herein, we provided a comprehensive update on the utility of AI in IK. [ABSTRACT FROM AUTHOR]

Published
2023
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33. In vitroprotocol for the optimal induction of inflammation in human monocyte cell lines

Author

Koganti, Raghuram, Yadavalli, Tejabhiram, and Shukla, Deepak

Abstract

The study of inflammation is of key interest to biomedical research; however, techniques to induce inflammation in vitroare difficult to implement. Here, we present a protocol that optimizes the induction and measurement of NF-kB-mediated inflammation in vitrousing a human macrophage cell line. We describe steps for growing, differentiating, and inducing inflammation in THP-1 cells. We detail the process of staining and grid-based confocal imaging. We also discuss approaches to test anti-inflammatory drug efficacy in inhibiting inflammatory milieu.

Published
2023
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34. Infection-Induced Porcine Ex Vivo Corneal Wound Model to Study the Efficacy of Herpes Simplex Virus-1 Entry and Replication Inhibitors.

Author

Yadavalli T, Koganti R, and Shukla D

Subjects
Animals, Antiviral Agents pharmacology, Chlorocebus aethiops, Cornea cytology, Cornea virology, Corneal Injuries etiology, Corneal Injuries pathology, Host-Pathogen Interactions, Keratitis, Herpetic pathology, Simplexvirus drug effects, Simplexvirus pathogenicity, Swine, Vero Cells, Virus Internalization, Virus Replication drug effects, Corneal Injuries virology, Disease Models, Animal, Keratitis, Herpetic virology, Simplexvirus physiology, Tissue Culture Techniques methods
Abstract

Corneal infections by viruses and bacteria can result in ocular surface defects, ulcers, or wounds. Herpes simplex virus type-1 (HSV-1) is a human virus with global seroprevalence in the range of 60-90%. While the virus more commonly causes mucocutaneous lesions including ulcers on the face and mouth, it is also a leading cause of infection-associated blindness. In this chapter, we discuss an in-depth protocol required to evaluate corneal damage due to HSV-1 infection using porcine models of ex vivo infection. Our methods can be adapted to study similar infections caused by other viruses and bacteria.

Published
2021
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