Search results for: Debprasad%20Chattopadhyay

Authors: Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, Goutam Kumar Ghorai, Gautam Sarkar, Ashis K. Dhara

Abstract:

Accurate segmentation of the optic disc is very important for computer-aided diagnosis of several ocular diseases such as glaucoma, diabetic retinopathy, and hypertensive retinopathy. The paper presents an accurate and fast optic disc detection and segmentation method using an attention based fully convolutional network. The network is trained from scratch using the fundus images of extended MESSIDOR database and the trained model is used for segmentation of optic disc. The false positives are removed based on morphological operation and shape features. The result is evaluated using three-fold cross-validation on six public fundus image databases such as DIARETDB0, DIARETDB1, DRIVE, AV-INSPIRE, CHASE DB1 and MESSIDOR. The attention based fully convolutional network is robust and effective for detection and segmentation of optic disc in the images affected by diabetic retinopathy and it outperforms existing techniques.

Keywords: attention-based fully convolutional network, optic disc detection and segmentation, retinal fundus image, screening of ocular diseases

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Authors: Nidhi S. Chandra, Veena Agrawal, Debprasad Chattopadhyay

Abstract:

Background: Hepatitis E virus (HEV) is a major cause of acute viral hepatitis in developing countries. It spreads feco orally mainly due to contamination of drinking water by sewage. There is limited data on the genotypic comparison of HEV isolates from sewage water and humans. The aim of this study was to identify genotype and conduct phylogenetic analysis of HEV isolates from sewage water and humans. Materials and Methods: 14 sewage water and 60 serum samples from acute sporadic hepatitis E cases (negative for hepatitis A, B, C) were tested for HEV-RNA by nested polymerase chain reaction (RTnPCR) using primers designed with in RdRp (RNA dependent RNA polymerase) region of open reading frame-1 (ORF-1). Sequencing was done by ABI prism 310. The sequences (343 nucleotides) were compared with each other and were aligned with previously reported HEV sequences obtained from GeneBank, using Clustal W software. A Phylogenetic tree was constructed by using PHYLIP version 3.67 software. Results: HEV-RNA was detected in 49/ 60 (81.67%) serum and 5/14 (35.71%) sewage samples. The sequences obtained from 17 serums and 2 sewage specimens belonged to genotype I with 85% similarity and clustering with previously reported human HEV sequences from India. HEV isolates from human and sewage in North West India are genetically closely related to each other. Conclusion: These finding suggest that sewage acts as reservoir of HEV. Therefore it is important that measures are taken for proper waste disposal and treatment of drinking water to prevent outbreaks and epidemics due to HEV.

Keywords: hepatitis E virus, nested polymerase chain reaction, open reading frame-1, nucleotidies

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Authors: Priyanka Bhowmik, Subrata Majumdar, Debprasad Chattopadhyay

Abstract:

Background: Cervical cancer is the third major cause of cancer in women and the second most frequent cause of cancer related deaths causing 300,000 deaths annually worldwide. Evasion of immune response by Human Papilloma Virus (HPV), the key contributing factor behind cancer and pre-cancerous lesions of the uterine cervix, makes immunotherapy a necessity to treat this disease. Objective: A Heat killed fraction of Mycobacterium indicus pranii (MIP), a non-pathogenic Mycobacterium has been shown to exhibit cytotoxic effects on different cancer cells, including human cervical carcinoma cell line HeLa. However, the underlying mechanisms remain unknown. The aim of this study is to decipher the mechanism of MIP induced HeLa cell death. Methods: The cytotoxicity of Mycobacterium indicus pranii against HeLa cells was evaluated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Apoptosis was detected by annexin V and Propidium iodide (PI) staining. The assessment of reactive oxygen species (ROS) generation and cell cycle analysis were measured by flow cytometry. The expression of apoptosis associated genes was analyzed by real time PCR. Result: MIP could inhibit the proliferation of HeLa cell in a time and dose dependent manner but caused minor damage to normal cells. The induction of apoptosis was confirmed by the cell surface presentation of phosphatidyl serine, DNA fragmentation, and mitochondrial damage. MIP caused very early (as early as 30 minutes) transcriptional activation of p53, followed by a higher activation (32 fold) at 24 hours suggesting prime importance of p53 in MIP-induced apoptosis in HeLa cell. The up regulation of p53 dependent pro-apoptotic genes Bax, Bak, PUMA, and Noxa followed a lag phase that was required for the transcriptional p53 program. MIP also caused the transcriptional up regulation of Toll like receptor 2 and 4 after 30 minutes of MIP treatment suggesting recognition of MIP by toll like receptors. Moreover, MIP caused the inhibition of expression of HPV anti apoptotic gene E6, which is known to interfere with p53/PUMA/Bax apoptotic cascade. This inhibition might have played a role in transcriptional up regulation of PUMA and subsequently apoptosis. ROS was generated transiently which was concomitant with the highest transcription activation of p53 suggesting a plausible feedback loop network of p53 and ROS in the apoptosis of HeLa cells. Scavenger of ROS, such as N-acetyl-L-cysteine, decreased apoptosis suggesting ROS is an important effector of MIP induced apoptosis. Conclusion: Taken together, MIP possesses full potential to be a novel therapeutic agent in the clinical treatment of cervical cancer.

Keywords: cancer, mycobacterium, immunity, immunotherapy.

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Authors: Goutam Kumar Ghorai, Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, G. Sarkar, Ashis K. Dhara

Abstract:

Diabetes mellitus is one of the most common chronic diseases in all countries and continues to increase in numbers significantly. Diabetic retinopathy (DR) is damage to the retina that occurs with long-term diabetes. DR is a major cause of blindness in the Indian population. Therefore, its early diagnosis is of utmost importance towards preventing progression towards imminent irreversible loss of vision, particularly in the huge population across rural India. The barriers to eye examination of all diabetic patients are socioeconomic factors, lack of referrals, poor access to the healthcare system, lack of knowledge, insufficient number of ophthalmologists, and lack of networking between physicians, diabetologists and ophthalmologists. A few diabetic patients often visit a healthcare facility for their general checkup, but their eye condition remains largely undetected until the patient is symptomatic. This work aims to focus on the design and development of a fully automated intelligent decision system for screening retinal fundus images towards detection of the pathophysiology caused by microaneurysm in the early stage of the diseases. Automated detection of microaneurysm is a challenging problem due to the variation in color and the variation introduced by the field of view, inhomogeneous illumination, and pathological abnormalities. We have developed aconvolutional neural network for efficient detection of microaneurysm. A loss function is also developed to handle severe class imbalance due to very small size of microaneurysms compared to background. The network is able to locate the salient region containing microaneurysms in case of noisy images captured by non-mydriatic cameras. The ground truth of microaneurysms is created by expert ophthalmologists for MESSIDOR database as well as private database, collected from Indian patients. The network is trained from scratch using the fundus images of MESSIDOR database. The proposed method is evaluated on DIARETDB1 and the private database. The method is successful in detection of microaneurysms for dilated and non-dilated types of fundus images acquired from different medical centres. The proposed algorithm could be used for development of AI based affordable and accessible system, to provide service at grass root-level primary healthcare units spread across the country to cater to the need of the rural people unaware of the severe impact of DR.

Keywords: retinal fundus image, deep convolutional neural network, early detection of microaneurysms, screening of diabetic retinopathy

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