Doctor of Philosophy

dissertationDNA microarrays have been plagued with analytical problems with quantitation, metrics, figures of merit, and reliability and reproducibility issues, hindering their acceptance in clinical and diagnostic settings. The main deficiency in the printed DNA format is the microspot heterogeneity occurring during array fabrication and further amplified during target hybridization. Work described in this dissertation focuses on assessment of DNA microarray spots generated with conventional pin-type contact printing of fluorescently labeled DNA probes, on industry-standard commercial polymer-coated array slides and their hybridization with complementary oligomer DNA target. Printing of probe DNA microspots shares many features of commonly reported droplet evaporation dynamics that lead to different drying patterns and spot morphologies. This study directly identifies and analyzes different DNA probe chemical and spatial microenvironments within spots, analyzed with high-resolution time-of-flight secondary ion mass spectrometry (TOF-SIMS) chemical imaging, confocal epifluorescence, and probe microscopy force imaging methods. Drying of DNA probe spots shows Marangoni flow effects with high densities of probe DNA-Cy3 located in spot centers and nonhomogeneous DNA distributed radially within printed spots with both TOF-SIMS imaging and epifluorescence microscopy. Target hybridization kinetics and duplex formation were assessed using real-time in situ confocal imaging, and confirmed radial hemispherical diffusion-mediated distribution of target capture from spot edge to its interior. Kinetic modeling indicates pseudo-first order kinetics due to transport limitations and local density-dependent probe interactions with diffusing target. Fluorescence resonance energy transfer (FRET) and photobleaching results show that the high- density probe overcrowding in spots facilitates a broad range of target binding interactions regardless of dye orientations. Moreover, lateral probe density heterogeneity observed with high-resolution imaging techniques confirmed with confocal microscopy produces equally iv heterogeneous target capture under normal assay conditions, showing how spot drying produces signal variability. These methods are the first to interrogate single printed array spots providing new support that microspot signal heterogeneity is not purely a result of target hybridization but is initially sourced during immobilization of probes with droplet printing techniques. This will guide new thinking on immobilized density influence on assay performance and how to approach assay endpoints, either kinetically or at equilibrium binding, by modifying spot molecular environments to reliably capture their signal

DL-CNN Framework for Medical Image Analysis

Deep Learning is the newest and the current trend of the machine learning field that paid a lotof the researchers' attention in the recent few years. As a proven powerful machine learningtool, deep learning was widely used in several applications for solving various complexproblems that require extremely high accuracy and sensitivity, particularly in the medicalfield. In general, the brain tumor is one of the most common and aggressive malignant tumordiseases which is leading to a noticeably short expected life if it is diagnosed at a highergrade. Based on that, brain tumor classification is an overly critical step after detecting thetumor in order to achieve an effective treating plan. In this paper, we used ConvolutionalNeural Network (CNN) which is one of the most widely used deep learning architectures forclassifying a dataset of 3064 T1 weighted contrast-enhanced brain MR images for grading(classifying) the brain tumors into three classes (Glioma, Meningioma, and Pituitary Tumor).The proposed CNN classifier is a powerful tool and its overall performance with an accuracyof 98.93% and sensitivity of 98.18% for the cropped lesions, while the results for theuncropped lesions are 99% accuracy and 98.52% sensitivity and the results for segmentedlesion images are 97.62% for accuracy and 97.40% sensitivity

Evaluation of Gymnema sylvestre Antimicrobial Activity in Methanol

G. sylvestre is a medicinal plant known for its sugar destroying property, as an anti-diabetic agent. The major phytoconstituents are the triterpenoid saponins, responsible for the various activities. The antimicrobial activity of this plant has been assessed in methanol as the solvent system for the extraction of active principles. The gram positive and gram negative organisms used in the study, have shown susceptibility towards the extracts, with the root extracts at acidic pH, showing higher activity. E. coli and E. cloacae were found to be the most sensitive and Pseudomonas aeruginosa, the resistant type of microorganisms, based on the results obtained from the zones of inhibition. The broad spectrum activity of the plant can be utilised in the development of new antimicrobial drugs

Antimicrobial Activity of the Extracts of Salacia oblonga Wall.

Salacia oblonga Wall. belonging to the family celastraceae is used in the treatment of diabetes, rheumatism, gonorrhoea, itches, asthma, wound healing, amenorrhea and ear diseases. It is a woody climber distributed in Sri Lanka and Southern regions of India. In the present study antimicrobial activity of Salacia oblonga was evaluated against pathogenic strains, gram +ve Staphylococcus aureus, Staphylococcus epidermidis, Enterococcus faecalis, Bacillus subtilis, Listeria monocytogenes and gram -ve Klebsiella pneumoniae, Enterobacter aerogenes, Enterobacter cloacae, Pseudomonas aeruginosa, Escherichia coli, Salmonella typhimurium. Ethyl acetate (EtOAc) aerial and root part extracts of Salacia oblonga have shown good activity towards all the pathogenic species. The zones of inhibition in the acidic EtOAc aerial and root extracts were measured to assess the antimicrobial activity

Some Improved Estimators of Co-efficient of Variation from Bi-variate normal distribution: A Monte Carlo Comparison

<div>Co-efficient of variation is a unitless measure of dispersion and is very frequently used in scientific investigations. This has motivated several researchers to propose estimators and tests concerning the co-efficient of variation of normal distribution(s). While proposing a class of estimators for the co-efficient of variation of a finite population, Tripathi et al., (2002) suggested that the estimator of co-efficient of variation of a finite population can also be used as an estimator of C.V for any distribution when the sampling design is SRSWR. This has motivated us to propose 28 estimators of finite population co-efficient of variation as estimators of co-efficient of variation of one component of a bivariate normal distribution when prior information is available regarding the second component. Cramer Rao type lower bound is derived to the mean square error of these estimators. Extensive simulation is carried out to compare these estimators. The results indicate that out of these 28 estimators, eight estimators have larger relative efficiency compared to the sample co-efficient of variation. The asymptotic mean square errors of the best estimators are derived to the order of &nbsp;for the benefit of users of co-efficient of variation.</div><div><br /></div

Using innovative copper‑loaded activated alumina (Cu/AA) as the catalyst for catalytic wet peroxidation (CWPO) of catechol

In this study, copper-loaded activated alumina (Cu/AA) was synthesized and used for the CWPO of catechol (a representative refractory organic pollutant). Various characterization techniques were deployed to characterize the catalysts, e.g., activated alumina (AA), as well as pristine and spent 1% Cu/AA. The innovative 1% Cu/AA catalyst exhibited good thermal stability up to 1173 K with a marginal weight loss of 13%. The Cu species were well dispersed on the activated alumina framework with no significant cluster formation. Typically, the average copper particle size of 5 nm was dispersed on the AA framework. Catechol removal was observed to be 92% with 87% mineralization at optimized conditions (initial catechol concentration = 200 mg/L, catalyst dose of 1% Cu/AA = 2 g/L; temperature = 323 K; pH = 6; and H2O2/ catechol stoichiometric ratio = 0.5). The mineralization of catechol was analyzed using mass spectroscopy, with the associated mechanism has been elucidated. Results of this study indicated that synthesized catalyst has phenomenal advantages in terms of simple separation and high removal efficiency of catechol, suggesting the feasibility of employing Cu/AA as the effective catalyst for the CWPO of catechol

Phytochemical investigations and antibacterial activity of Salacia oblonga Wall ethanolic extract

Abstract Salacia oblonga Wall, a medicinally important plant, belonging to the family Celastraceae, is a large woody climber distributed in southern India and Sri Lanka. In the present investigation, ethanol extracts of S. oblonga were prepared from aerial and root parts of the plant in the presence and absence of HCl and antibacterial activity was tested. Both aerial and root extracts exhibited pronounced activity against human pathogens. The MIC and MBC values ranged from 0.078-1.25 mg/ml and 0.156 -2.50 mg/ml, respectively. GC-MS profile of aerial and root extracts displayed the presence of 11 and 6 compounds. The present investigation demonstrated that ethanolic extracts of S. oblonga have potential antibacterial activity against human pathogens and could serve as a source for the development of new age antimicrobials

Heart Failure and Cardiac Device Therapy: A Review of Current National Institute of Health and Care Excellence and European Society of Cardiology Guidelines

Guidelines help clinicians to deliver high-quality care with therapies based on up-to-date evidence. There has been significant progress in the management of heart failure with regards to both medication and cardiac device therapy. These advances have been incorporated into national and international guidelines with varying degrees of success. This article reviews current guidance from the National Institute of Health and Care Excellence in the UK and compares this with European Society of Cardiology guidelines, and evaluates how differences between them may impact on clinical practice

Comparative Estimation of Arginine Content in Peanuts: An Analytical Study

Introduction: Arginine is an amino acid that has several positive effects on human health and peanut seeds are the richest source of it. Peanuts are the store houses loaded with proteins, fatty acids, vitamins, fiber and other phytochemicals. It has been shown that the intake of arginine at the concentration of 3-6 g/day has been found to improve the cardiovascular system, reduce intestinal permeability and activate the immune system that aids in early recovery of tuberculosis patients. Aim: To evaluate the variation of arginine content in raw, boiled, soaked, soaked and boiled type of peeled and unpeeled peanuts Materials and Methods: The analytical study on various groups of peanuts (raw, boiled, soaked, soaked and boiled peanuts of both peeled and unpeeled varieties) was conducted at Gayatri Vidya Parishad Institute of Health Care and Medical Technology at Visakhapatnam, Andhra Pradesh, India, in December 2019. The arginine content was estimated in peanut seeds using the Sakaguchi method by Spectrophotometry at wavelength of 520 nm. Descriptive statistics were done for all 12 groups and were represented with mean, standard deviation and standard error. Analysis of Variance (ANOVA), Post-hoc Tukey’s were applied to find statistical significance. The p-value <0.05 was considered as statistically significant. Statistical Package for Social Sciences (SPSS) version 25.0 was used for analysis. Results: Concentration of arginine was recorded for each type in triplicate considering the mean. The raw soaked peeled peanuts had the lowest concentration of arginine (31.82 μg/g) and the soaked boiled for 15 minutes, unpeeled peanuts had the highest amount of arginine (1438.18 μg/g). Significant difference was found among the twelve groups by using ANOVA test p<0.001. Soaked and boiled 15 min peeled peanuts, soaked unpeeled, soaked and boiled 15 min unpeeled and soaked and boiled 30 min unpeeled were significantly different when compared to the remaining groups using Post hoc Tukey’s test p<0.05. Conclusion: Soaked, boiled and unpeeled peanuts were the best types with the highest amounts of arginine which could be chosen as adjuvant nutritional therapeutic supplement to aid in the recovery of certain diseases