Amarendranath Choudhury
@pkdc.ac.in
Assistant Professor, Department of Zoology
Patharkandi College
Dr. Amarendranath Choudhury has completed his Ph. D from Assam University, India. Currently, he is working as an Assistant Professor at Dept. of Zoology, Patharkandi College. Dr. Choudhury’s research interest focuses on 1). Biochemical aspects of neurodegeneration, 2). Effect of diet on brain neurochemistry, 3). Ethnopharmacological approaches for neurotherapeutics, 4). Vesicular trafficking. Dr. Choudhury is having 9 years of Academic & Industrial research Experiences.
Disciplines
Green ChemistryChemical BiologyBiological PsychologyAbnormal PsychologyMolecular BiologyNeuroscienceZoology
Skills and expertise
NeurodegenerationHypercholesterolemiaEndosomal Sorting Complexes Required for TransportNeurobiochemistryNeuroprotective AgentsParkinson's DiseaseNeuropathologyNeurobiologyAlzheimer's DiseaseDiabetes ComplicationsBiochemistryActive Pharmaceutical Ingredients
RESEARCH, TEACHING, or OTHER INTERESTS
Health, Toxicology and Mutagenesis, Neuroscience, Neurology, Animal Science and Zoology
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Amarendranath Choudhury, Sathish E., Dhilleshwara Rao Vana, and L. Ganesh Babu
CRC Press
Rudrarup Bhattacharjee, Lopamudra Das Roy, and Amarendranath Choudhury
Springer Science and Business Media LLC
AbstractThe research focus on CRISPR/Cas9 has gained substantial concentration since the discovery of ‘an unusual repeat sequence’ reported by Ishino et al. (J Bacteriol 169:5429–5433, 1987) and the journey comprises the recent Nobel Prize award (2020), conferred to Emmanuelle Charpentier and Jennifer Doudna. Cumulatively, the CRISPR has a short, compact, and most discussed success of its application in becoming one of the most versatile and paradigm shifting technologies of Biological Research. Today, the CRISPR/Cas9 genome editing system is almost ubiquitously utilized in many facets of biological research where its tremendous gene manipulation capability has been harnessed to create miracles. From 2012, the CRISPR/Cas 9 system has been showcased in almost 15,000 research articles in the PubMed database, till date. Backed by some strong molecular evidence, the CRISPR system has been utilized in a few clinical trials targeted towards various pathologies. While the area covered by CRISPR is cosmic, this review will focus mostly on the utilization of CRISPR/Cas9 technology in the field of cancer therapy.
Ankumoni Dutta, Banashree Chetia Phukan, Rubina Roy, Muhammed Khairujjaman Mazumder, Rajib Paul, Amarendranath Choudhury, Diwakar Kumar, Pallab Bhattacharya, Joyobrato Nath, Sanjeev Kumar,et al.
Springer Science and Business Media LLC
P. William, Mohd Shamim, Ajay Reddy Yeruva, Durgaprasad Gangodkar, Swati Vashisht, and Amarendranath Choudhury
IEEE
Using deep learning and a behavioural approach, this study presents a real-time detection and monitoring system for tired drivers. The objective is to develop and build software that collects real-time driver behaviour while driving and trains it using convolutional neural networks (CNNs) to anticipate the driver's behaviour. An intelligent video-based gadget, a dataset of drowsy drivers, and CNN architecture were used to achieve this goal. MATLAB and a deep learning technology were used to implement the concepts. Tests revealed that the system has a 99.8% accuracy rate for detecting anomalies. A prototype model of the system was created using MATLAB.
Shobha Tyagi, Neha Tyagi, Amarendranath Choudhury, Gauri Gupta, Musaddak Maher Abdul Zahra, and Saima Ahmed Rahin
Hindawi Limited
Prostate cancer is one of the most common cancers in men worldwide, second only to lung cancer. The most common method used in diagnosing prostate cancer is the microscopic observation of stained biopsies by a pathologist and the Gleason score of the tissue microarray images. However, scoring prostate cancer tissue microarrays by pathologists using Gleason mode under many tissue microarray images is time-consuming, susceptible to subjective factors between different observers, and has low reproducibility. We have used the two most common technologies, deep learning, and computer vision, in this research, as the development of deep learning and computer vision has made pathology computer-aided diagnosis systems more objective and repeatable. Furthermore, the U-Net network, which is used in our study, is the most extensively used network in medical image segmentation. Unlike the classifiers used in previous studies, a region segmentation model based on an improved U-Net network is proposed in our research, which fuses deep and shallow layers through densely connected blocks. At the same time, the features of each scale are supervised. As an outcome of the research, the network parameters can be reduced, the computational efficiency can be improved, and the method’s effectiveness is verified on a fully annotated dataset.
Suneet Gupta, V. Saravanan, Amarendranath Choudhury, Abdullah Alqahtani, Mohamed R. Abonazel, and K. Suresh Babu
Hindawi Limited
Alzheimer’s disease is incurable at the moment. If it can be appropriately diagnosed, the correct treatment can postpone the patient’s illness. To aid in the diagnosis of Alzheimer’s disease and to minimize the time and expense associated with manual diagnosis, a machine learning technique is employed, and a transfer learning method based on 3D MRI data is proposed. Machine learning algorithms can dramatically reduce the time and effort required for human treatment of Alzheimer’s disease. This approach extracts bottleneck features from the M-Net migration network and then adds a top layer to supervised training to further decrease the dimensionality and delete portions. As a consequence, the transfer network presented in this study has several advantages in terms of computational efficiency and training time savings when used as a machine learning approach for AD-assisted diagnosis. Finally, the properties of all subject slices are combined and trained in the classification layer, completing the categorization of Alzheimer’s disease symptoms and standard control. The results show that this strategy has a 1.5 percentage point better classification accuracy than the one that relies exclusively on VGG16 to extract bottleneck features. This strategy could cut the time it takes for the network to learn and improve its ability to classify things. The experiment shows that the method works by using data from OASIS. A typical transfer learning network’s classification accuracy is about 8% better with this method than with a typical network, and it takes about 1/60 of the time with this method.
D. Vana, D. Adapa, Prasad Vss, Dr. Amarendranath Choudhury and G. Ahuja
The characteristic symptom of diabetes is consistently elevated levels of blood sugar. This is instigated either by complete lack of insulin production (type 1 diabetes), reduced level of insulin production (type 2 diabetes) or insulin resistance (inability of body cells to take up glucose). Other types of diabetes include maturity onset of diabetes of the young (MODY), a form of type 2 diabetes and gestational diabetes which affects pregnant women mostly in second or third trimester. The term type-3-diabetes is now being used for insulin resistance in brain. Apart from environmental and dietary causes which pose the risk of diabetes, genetic constitution and gene mutations execute the manifestation of diabetes. So far, several hundreds of genes having genomic, metabolic and immunological functions have been associated with different forms of diabetes. Due to complexity in diabetes etiology, involvement of multiple genetic factors and overlap between phenotypes, the treatment for diabetes remains a major challenge. Single gene mutations can be potentially targeted therapeutically; however, the prevalence of single gene mutations in diabetic condition is rare. Comprehensive analysis of genes and genetic variants relevant to diabetes enables development of effective treatment or interventional strategies. The current literature survey was conducted and reviewed to identify studies that proposed the genetic basis for specific subtypes of diabetes and related complications. In addition, this review emphasizes the role of genome wide association studies and epigenetic factors. In the present review, we have identified some of the most significant protein encoding genes whose mutations have great impact in the development of diabetic condition. The characteristic features of these genes such as the risk level associated with the genes and inter-genic associations both in terms of position and functional proximity have been discussed. Additionally, genomic studies and epigenetic aspects have also been highlighted for wider comprehension of the diabetic condition from a genetic perspective. The present review would be of significance in prevention, screening, diagnosis, treatment and management of different forms of diabetes.
Udaya Kumar Vandana, Ankita Chopra, Amarendranath Choudhury, Dattatreya Adapa, and Pranab Behari Mazumder
OMICS Publishing Group
Microbial activity in root environment is responsible for plant nutrition, growth and defence. The objective of this study is to analyse the plant growth promoting and antagonistic activity rendered by the rhizospheric bacteria of tea plant. In this study, 292 bacterial isolates were screened for indole acetic acid (IAA) production, phosphate solubilisation, ammonia production, chitinase production and protease production. Among all the bacterial isolates, 58 isolates were able to elicit minimum four plant growth promoting rhizobacteria (PGPR) traits, which were further analysed quantitatively for hydrogen cyanide (HCN), siderophore production and antagonistic activity. Based on the plant growth promoting potential scores and principle component analysis, 12 samples were further screened for the study of salt tolerance and antifungal activity profile against tea fungal pathogens (Rhizoctonia solani, Fomes lamenensis, Corticium invisum). The identity the isolates was revealed by 16s rDNA sequence analysis. Six isolates (n63, k32, n61, 31k, n57, n56) showing efficient PGPR traits were evaluated for growth promotion studies on rice seedlings. Isolate n61 (Bacillus cereus) induced significant increase in root length (9.85 mm), shoot length (7.86 mm), germination percentage (92.44) and vigour index (1566.42) in rice seedlings. Fresh bio mass was significantly higher in 31k (Pseudomonas putida) (81.33 mg) followed by n61 (Bacillus cereus) (80.84 mg) and dry mass was higher in n63 (Bacillus pseudomycoides) (15.84 mg) followed by n61 (Bacillus cereus ) (15.82 mg) while compared with control and the other isolates selected for in vitro growth experiments. ANOVA analysis showed significant (P<0.05) increase compared with control, indicating that, bacterial isolates are potent for plant growth promotion and productivity.
A. R. Choudhury, S. B. Paul, and S. Choudhury
Pleiades Publishing Ltd
Rajib Paul, Amarendranath Choudhury, Dulal Chandra Boruah, Rajlakshmi Devi, Pallab Bhattacharya, Manabendra Dutta Choudhury, and Anupom Borah
Elsevier BV
Anupom Borah, Amarendranath Choudhury, Rajib Paul, Muhammed K. Mazumder, and Swapnali Chetia
Wiley
Parkinson’s disease (PD) is an old-age neurodegenerative motor disorder characterized by resting tremor, rigidity, bradykinesia, and postural instability due to degeneration of midbrain dopaminergic neurons that results in decrease in the level of neurotransmitter dopamine (DA) in the striatum. In the eighteenth century, James Parkinson first described the disease as “shaking palsy,” which was later named as PD. However, a description of equivalent parkinsonian symptoms is found in ancient Indian medical system of Ayurveda under the name Kampavata. As early as 300 BC, a coherent picture of parkinsonism was found in the Ayurvedic literature – Charaka Samhita, where head tremor (Sirakampa) and generalized tremor were described. Ayurvedic physicians used a cocktail of powdered seeds of Atmagupta (Mucuna pruriens) and Paraseekayavanee (Hyoscyamus reticulatus) with roots of Ashwagandha (Withania somnifera) and Bala (Sida cordifolia) in cow’s milk to treat Kampavata. Presently, use of a DA precursor, 3,4-dihydroxyphenylalanine (l-DOPA), is the choice of treatment to alleviate motor symptoms of PD. However, long-term l-DOPA treatment is associated with adverse side effects, such as motor fluctuations, dyskinesia, and drug-induced toxicity. A prospective clinical trial on the effectiveness of the Ayurvedic formulation in PD patients provided significant improvement of the symptoms, which has been attributed to the presence of l-DOPA and other neuroactive components in the formulations. Thus, the recent trend of therapeutic approaches in PD research has shifted to natural products or herbal formulations that would provide independent therapy or neuroprotective support to the existing drug, where Ayurveda will be of immense significance. In this chapter, we discuss the potentials of natural products used in Ayurvedic formulations as alternative/adjuvant to the DA replenishment therapy for PD and highlighted their molecular mechanisms of action.
Rajib Paul, Amarendranath Choudhury, Sanjeev Kumar, Anirudha Giri, Rajat Sandhir, and Anupom Borah
Public Library of Science (PLoS)
Hypercholesterolemia is a known contributor to the pathogenesis of Alzheimer’s disease while its role in the occurrence of Parkinson’s disease (PD) is only conjecture and far from conclusive. Altered antioxidant homeostasis and mitochondrial functions are the key mechanisms in loss of dopaminergic neurons in the substantia nigra (SN) region of the midbrain in PD. Hypercholesterolemia is reported to cause oxidative stress and mitochondrial dysfunctions in the cortex and hippocampus regions of the brain in rodents. However, the impact of hypercholesterolemia on the midbrain dopaminergic neurons in animal models of PD remains elusive. We tested the hypothesis that hypercholesterolemia in MPTP model of PD would potentiate dopaminergic neuron loss in SN by disrupting mitochondrial functions and antioxidant homeostasis. It is evident from the present study that hypercholesterolemia in naïve animals caused dopamine neuronal loss in SN with subsequent reduction in striatal dopamine levels producing motor impairment. Moreover, in the MPTP model of PD, hypercholesterolemia exacerbated MPTP-induced reduction of striatal dopamine as well as dopaminergic neurons in SN with motor behavioral depreciation. Activity of mitochondrial complexes, mainly complex-I and III, was impaired severely in the nigrostriatal pathway of hypercholesterolemic animals treated with MPTP. Hypercholesterolemia caused oxidative stress in the nigrostriatal pathway with increased generation of hydroxyl radicals and enhanced activity of antioxidant enzymes, which were further aggravated in the hypercholesterolemic mice with Parkinsonism. In conclusion, our findings provide evidence of increased vulnerability of the midbrain dopaminergic neurons in PD with hypercholesterolemia.
Nivedita Bhattacharjee, Muhammed Khairujjaman Mazumder, Rajib Paul, Amarendranath Choudhury, Sabanum Choudhury, and Anupom Borah
Elsevier BV
Rajib Paul, Amarendranath Choudhury, Sabanum Choudhury, Muhammed K. Mazumder, and Anupom Borah
Ovid Technologies (Wolters Kluwer Health)
Abstract The mechanisms or causes of pancreatic &bgr;-cell death as well as impaired insulin secretion, which are the principal events of diabetic etiopathology, are largely unknown. Diabetic complications are known to be associated with abnormal plasma lipid profile, mainly elevated level of cholesterol and free fatty acids. However, in recent years, elevated plasma cholesterol has been implicated as a primary modulator of pancreatic &bgr;-cell functions as well as death. High-cholesterol diet in animal models or excess cholesterol in pancreatic &bgr;-cell causes transporter desensitization and results in morphometric changes in insulin granules. Moreover, cholesterol is also held responsible to cause oxidative stress, mitochondrial dysfunction, and activation of proapoptotic markers leading to &bgr;-cell death. The present review focuses on the pathways and molecularevents that occur in the &bgr;-cell under the influence of excess cholesterol that hampers the basal physiology of the cell leading to the progression of diabetes.
Rajib Paul, Amarendranath Choudhury, and Anupom Borah
Elsevier BV
Anupom Borah, Rajib Paul, Sabanum Choudhury, Amarendranath Choudhury, Bornalee Bhuyan, Anupam Das Talukdar, Manabendra Dutta Choudhury, and Kochupurackal P Mohanakumar
Wiley
Silymarin, a C25 containing flavonoid from the plant Silybum marianum, has been the gold standard drug to treat liver disorders associated with alcohol consumption, acute and chronic viral hepatitis, and toxin‐induced hepatic failures since its discovery in 1960. Apart from the hepatoprotective nature, which is mainly due to its antioxidant and tissue regenerative properties, Silymarin has recently been reported to be a putative neuroprotective agent against many neurologic diseases including Alzheimer's and Parkinson's diseases, and cerebral ischemia. Although the underlying neuroprotective mechanism of Silymarin is believed to be due to its capacity to inhibit oxidative stress in the brain, it also confers additional advantages by influencing pathways such as β‐amyloid aggregation, inflammatory mechanisms, cellular apoptotic machinery, and estrogenic receptor mediation. In this review, we have elucidated the possible neuroprotective effects of Silymarin and the underlying molecular events, and suggested future courses of action for its acceptance as a CNS drug for the treatment of neurodegenerative diseases.