Characterization of Protein Residue Surface Accessibility Using Sequence Homology

Residues present on the surface of the proteins are involved in a number of functions, especially in ligand-protein interactions, that are important for drug design. The residues present in the core of the protein provide stability to the protein and help in maintaining protein structure. Hence, there is a need for a binary characterization of protein residues based on their surface accessibility (surface accessible or buried). Such a classification can aid in the directed study of either residue type. A number of methods for the prediction of surface accessible protein residues have been proposed in the past. However, most of these methods are computationally complex and time consuming. In this thesis, we propose a simple method based on protein sequence homology parameters for the binary classification of protein residues as surface accessible or “buried”. To aid in the classification of protein residues, we chose three highly conservative homology-based parameter filter thresholds. The filter thresholds predicted and evaluated are: residue sequence entropy ≥0:15, fraction of strongly hydrophobic residues \u3c0:5 and fraction of small residues \u3c 0:15. The application of these filter thresholds to the residues, is expected to predict the “buried residues” with a better percentage accuracy than that of the surface accessible residues. These filter thresholds were selected from the frequency distributions and the aggregate correlation plots of the various homology-based parameters. An analysis of the plots suggests the presence of a strongly hydrophobic core between packing density 14 –22 where the presence of strongly hydrophobic residues is maximum and the presence of small and non-strongly hydrophobic residues is minimum. However, the densest portion of the protein (density 26 – 35) is indicated to be occupied by a combination of small and non-strongly hydrophobic residues with a negligible presence of strongly hydrophobic residues

Successful management of pregnancy with dual mechanical heart valves: a case report

Incidence of cardiovascular diseases in pregnancy is increasing due to advanced maternal age at first conception and frequent association of comorbid chronic medical conditions. Rheumatic heart diseases comprise 56-89% of all CVDs in pregnancy in non-western countries. Management of pregnant women with mechanical valves is very challenging due to high risk of cardiac and non-cardiac complications either due to heart disease itself or changes in hemodynamics during pregnancy or due to anticoagulant therapy. We presented here a case of a 35-year-old pregnant woman with rheumatic heart disease with dual mechanical (aortic and mitral) valve replacement who was managed successfully by our team of expert clinicians with intensive antepartum surveillance with good obstetric outcome. It is very important for managing clinicians to have necessary information about high-risk cardiovascular diseases during pregnancy along with their management and treatment related feto-maternal complications in order to have optimal feto-maternal outcome

Oxidative Stress and Heart Failure in Altered Thyroid States

Increased or reduced action of thyroid hormone on certain molecular pathways in the heart and vasculature causes relevant cardiovascular derangements. It is well established that hyperthyroidism induces a hyperdynamic cardiovascular state, which is associated with a faster heart rate, enhanced left ventricular systolic and diastolic function whereas hypothyroidism is characterized by the opposite changes. Hyperthyroidism and hypothyroidism represent opposite clinical conditions, albeit not mirror images. Recent experimental and clinical studies have suggested the involvement of ROS tissue damage under altered thyroid status. Altered-thyroid state-linked changes in heart modify their susceptibility to oxidants and the extent of the oxidative damage they suffer following oxidative challenge. Chronic increase in the cellular levels of ROS can lead to a catastrophic cycle of DNA damage, mitochondrial dysfunction, further ROS generation and cellular injury. Thus, these cellular events might play an important role in the development and progression of myocardial remodeling and heart failure in altered thyroid states (hypo- and hyper-thyroidism). The present review aims at elucidating the various signaling pathways mediated via ROS and their modulation under altered thyroid state and the possibility of antioxidant therapy

Emerging Issues and Opportunities in Disaster Response Supply Chain Management

The world is facing an increasing frequency and intensity of disasters both natural and man-made that have devastating impact on life, livelihood and economy of the affected communities. In the context it is very important to plan for disaster response activities and preparedness to minimize the economic and human loss. In a post disaster situation various aid organizations and government agencies start supplying food, water, clothing, medicines and other emergency relief materials efficiently and quickly to maximize survival rate and continue normalcy. However, managing disaster response supply chain is not that straight forward. In most disasters, information is scarce (between the supplier and end users) and coordination rarely exists (Long Wood, 1995) which creates disruption in flow of supply chain. Hence disaster response supply chain operates in a level of high uncertainty and is very different from what most supply chain managers perceive. This article describes the main characteristics of disaster response supply chain, particular issues faced by the managers and the opportunities on which the future strategy could be capitalized. It also suggests a model that captures the interaction between different components of supply chain and controls the flow of the commodities from the source through the chain to reach the end users

Automated Detection of Acute Leukemia using K-mean Clustering Algorithm

Leukemia is a hematologic cancer which develops in blood tissue and triggers rapid production of immature and abnormal shaped white blood cells. Based on statistics it is found that the leukemia is one of the leading causes of death in men and women alike. Microscopic examination of blood sample or bone marrow smear is the most effective technique for diagnosis of leukemia. Pathologists analyze microscopic samples to make diagnostic assessments on the basis of characteristic cell features. Recently, computerized methods for cancer detection have been explored towards minimizing human intervention and providing accurate clinical information. This paper presents an algorithm for automated image based acute leukemia detection systems. The method implemented uses basic enhancement, morphology, filtering and segmenting technique to extract region of interest using k-means clustering algorithm. The proposed algorithm achieved an accuracy of 92.8% and is tested with Nearest Neighbor (KNN) and Naive Bayes Classifier on the data-set of 60 samples.Comment: Presented in ICCCCS 201

Myrica Esculenta and it’s Anti-Asthmatic Property with Ayurvedic approach : A Review

Myrica esculenta is a perennial shrub, of myricaceae family. From ancient time myrica esculanta reported to be used in traditional system of medicine. Various parts of the tree bark, fruit, flower are used therapetucally including for treatment of anemia, bronchitis, cough, chronic dysentery, fever, liver complaints, nasal catarrh, piles, sores, throat complaints, tumors, ulcers, urinary discharges. This review gives us a bird’s eye view on detailed information of this plants and targeted anti-asthmatic property of plant,as per Ayurvedic view concern

A Framework for Computerized Adaptive Assessment based on Trajectory Driven Pedagogy Implemented in an Engineering Course

Engineering education needs to be flexible with the changing technology, and it must blend traditional and new teaching pedagogy for the overall knowledge creation in the students. A survey of prevalent experiential learning methods has shown tremendous potential to improve engineering students' learning. However, existing experiential learning methods are hard to integrate with current teaching-learning process at Amity University, Uttar Pradesh, Lucknow Campus, India. A pilot study conducted during Power plant Instrumentation taught in the seventh semester of the Electrical and Electronics undergraduate program balances the current teaching method with the proposed Trajectory -driven pedagogy as an alternative teaching pedagogy. A trajectory driven computerized adaptive assessment procedure for teaching has been proposed in this paper. The system follows a trajectory of courses to generate the subsequent questions from the vast database of questions. A sequence of questions is guided by Concept Map which represents the questions from three courses in a hierarchical manner. Analysis of students' assessments shows that the proposed methodology could is accurate for quantitative measurement of the course learning outcomes in a summative assessment. &nbsp

Deep 3D Convolutional Neural Network for Automated Lung Cancer Diagnosis

Computer Aided Diagnosis has emerged as an indispensible technique for validating the opinion of radiologists in CT interpretation. This paper presents a deep 3D Convolutional Neural Network (CNN) architecture for automated CT scan-based lung cancer detection system. It utilizes three dimensional spatial information to learn highly discriminative 3 dimensional features instead of 2D features like texture or geometric shape whick need to be generated manually. The proposed deep learning method automatically extracts the 3D features on the basis of spatio-temporal statistics.The developed model is end-to-end and is able to predict malignancy of each voxel for given input scan. Simulation results demonstrate the effectiveness of proposed 3D CNN network for classification of lung nodule in-spite of limited computational capabilities.Comment: Initial draft of PAPER Presented at IRSCNS 2018 , Goa , India final version available at Mishra S., Chaudhary N.K., Asthana P., Kumar A. (2019) Deep 3D Convolutional Neural Network for Automated Lung Cancer Diagnosis. In: Peng SL., Dey N., Bundele M. (eds) Computing and Network Sustainability. Lecture Notes in Networks and Systems, vol 75. Springer, Singapor

Halotolerant Plant Growth Promoting Bacilli from Sundarban Mangrove Mitigate the Effects of Salinity Stress on Pearl Millet (Pennisetum glaucum L.) Growth

Pearl millet (Pennisetum glaucum L.) is one of the major crops in dry and saline areas across the globe. During salinity stress, plants encounter significant changes in their physio and biochemical activities, leading to decreased growth and yield. Bacillus species are used as biofertilizers and biopesticides for pearl millet and other crops to promote growth and yield. The use of Bacillus in saline soils has been beneficial to combat the negative effect of salinity on plant growth and yield. In this context, the present study emphasizes the use of two Bacillus species, i.e. Bacillus megaterium JR-12 and B. pumilus GN-5, which helped in alleviating the impact of salinity stress on the growth activities in salt-stressed pearl millet. Pearl millet seeds were treated with two strains, B. megaterium JR-12 and B.pumilus GN-5, individually and in combination under 50, 100 and 150 mM of sodium chloride stress. The treated plants showed higher plant height, biomass accumulation, and photosynthetic apparatus than the non-treated plants. Additionally, the treated plants showed increased osmoprotectant levels under salinity stress compared to control plants. The antioxidant enzyme content was improved post-inoculation, indicating the efficient stress-alleviating potential of both strains of Bacillus species. Moreover, inoculation of these microbes significantly increased plant growth attributes in plants treated with a combination of Bp-GN-5 + Bm-JR-12 and the reduction rates of plant growth were found to be alleviated to 9.12%, 20.30% and 33%, respectively. Overall, the results of the present study suggested that these microbes could have a higher potential to improve the productivity of pearl millet under salinity stress

Formulation Development and Evaluation of Pravastatin-Loaded Nanogel for Hyperlipidemia Management

Hyperlipidemia is a crucial risk factor for the initiation and progression of atherosclerosis, ultimately leading to cardiovascular disease. The nanogel-based nanoplatform has emerged as an extremely promising drug delivery technology. Pravastatin Sodium (PS) is a cholesterol-lowering drug used to treat hyperlipidemia. This study aimed to fabricate Pravastatin-loaded nanogel for evaluation of its effect in hyperlipidemia treatment. Pravastatin-loaded chitosan nanoparticles (PS-CS-NPs) were prepared by the ionic gelation method; then, these prepared NPs were converted to nanogel by adding a specified amount of 5% poloxamer solution. Various parameters, including drug entrapment efficacy, in vitro drug release, and hemolytic activity of the developed and optimized formulation, were evaluated. The in vitro drug release of the nanogel formulation revealed the sustained release (59.63% in 24 h) of the drug. The drug excipients compatibility studies revealed no interaction between the drug and the screened excipients. Higher drug entrapment efficacy was observed. The hemolytic activity showed lesser toxicity in nanoformulation than the pure drug solution. These findings support the prospective use of orally administered pravastatin-loaded nanogel as an effective and safe nano delivery system in hyperlipidemia treatment