The bio-efficacy study confirmed that the calli mediated tissues showed the maximum zone of inhibition. The present study paved a protocol to establish high potential cell lines by in vitro culture.

Increased incidence of OSSN was observed in males and people with outdoor occupations. Nodular type of lesion is the commonest variety. HIV positive individuals have an increased incidence of OSSN with invasive characteristics. Hence, ophthalmologists need to be aware of this association and a thorough workup is warranted for all patients presenting with OSSN, especially in the younger age group. Our study Also suggests that OSSN may be the first manifestation of underlying HIV infection.

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Problem statement: Diabetic retinopathy is one of the most significant factors contributing to blindness and so early diagnosis and timely treatment is particularly important to prevent visual loss. Approach: An integrated approach for extraction of blood vessels and exudates detection was proposed to screen diabetic retinopathy. An automated classifier was developed based on Adaptive Neuro-Fuzzy Inference System (ANFIS) to differentiate between normal and nonproliferative eyes from the quantitative assessment of monocular fundus images. Feature extraction was performed on the preprocessed fundus images. Structure of Blood vessels was extracted using Multiscale analysis. Hard Exudates were detected using CIE Color channel transformation, Entropy Thresholding and Improved Connected Component Analysis from the fundus images. Features like Wall to Lumen ratio in blood vessels, Texture, Homogeneity properties and area occupied by Hard Exudates, were given as input to ANFIS.ANFIS was trained with Back propagation in combination with the least squares method. Proposed method was evaluated on 200 real time images comprising 70 normal and 130 retinopathic eyes. Results and Conclusion: All of the results were validated with ground truths obtained from expert ophthalmologists. Quantitative performance of the method, detected exudates with an accuracy of 99.5%. Receiver operating characteristic curve evaluated for real time images produced better results compared to the other state of the art methods. ANFIS provides best classification and can be used as a screening tool in the analysis and diagnosis of retinal images.