A Web Based User Interface for Machine Learning Analysis of Health and Education Data

The objective of this thesis is to develop a user friendly web application that will be used to analyse data sets using various machine learning algorithms. The application design follows human computer interaction design guidelines and principles to make a user friendly interface [Shn03]. It uses Linear Regression, Logistic Regression, Backpropagation machine learning algorithms for prediction. This application is built using Java, Play framework, Bootstrap and IntelliJ IDE. Java is used in the backend to create a model that maps the input and output data based on any of the above given learning algorithms while Play Framework and Bootstrap are used to display content in frontend. Play framework is used because it is based on web-friendly architecture. As a result it uses predictable, minimal resources (CPU, memory, threads) for highly scalable applications. It is also developer friendly where changes can be made in the code and hitting the refresh button in browser will update the interface. Bootstrap is used to style the web application and it adds responsiveness to the interface with added feature of cross-browser compatible designs. As a result, the website is responsive and fits the screen size of computer. Using this web application users can predict features, category of the entity in the data sets. User needs to submit data set where each row in the data set must represent attributes of the entity. Once data is submitted the application builds a model using user selected machine learning algorithm logistic regression, linear regression or backpropagation. After the model is developed in second stage of the application user can submit attributes of the entity whose category needs to predicted. The predicted category will be displayed on screen in third stage of the application. The interface of the application shows its current active stage. These models are built using 80% of submitted dataset and remaining 20% is used to test the accuracy of the application. In this thesis, prediction accuracy of each algorithm is tested using UCI breast cancer data sets. When tested on breast cancer data with 10 attributes both Logistic Regression and Backpropagation gave 98.5% accuracy. And when tested on breast cancer data with 31 attributes Logistic Regression gave 92.85% accuracy and Backpropagation gave 94.64%

MEKK-3 Acts Cooperatively with NSY-1 in SKN-1-Dependent Manner against Oxidative Stress and Aging in Caenorhabditis elegans

Oxidative stress resulting from reactive oxygen species and other toxic metabolites is involved in human diseases, and it plays an important role in aging. In Caenorhabditis elegans, SKN-1 is required for protection against oxidative stress and aging. As p38 mitogen-activated protein kinase signaling is activated in response to oxidative stress, SKN-1 accumulates in intestinal nuclei and induces phase II detoxification genes. However, NSY-1, a well-known mitogen-activated protein kinase kinase kinase (MAPKKK) of C. elegans, acts as a partial regulator of the SKN-1-induced oxidative stress signaling pathway, suggesting that the regulator for optimal activation of SKN-1 remains unknown. Here, we report a MAPKKK, MEKK-3, as a new regulator required for full activation of SKN-1-mediated resistance against oxidative stress and aging. In RNA-interference-based screening, we found that the simultaneous knockdown of mekk-3 and nsy-1 significantly decreased the oxidative stress resistance and survival of SKN-1 transgenic worms. MEKK-3 was induced in response to oxidative stress. Mechanistic analysis revealed that double knockdown of mekk-3 and nsy-1 completely suppressed the nuclear localization of SKN-1. These results were reproduced in mutant worms in which SKN-1 is constitutively localized to intestinal nuclei. In addition, mekk-3 and nsy-1 were required for optimal induction of SKN-1 target genes such as gcs-1 and trx-1. These data indicate that MEKK-3 plays an essential role in the SKN-1-dependent signaling pathway involved in oxidative stress resistance and longevity by cooperating with NSY-1

Genital Hailey- Hailey disease: a case report

Hailey – Hailey disease is a rare autosomal dominant acantholytic disorder, previously not reported from Nepal. We report a case of 30 years old female who presented with pruritic hyperkeratotic papules and plaques on vulva, perianal area and inner left thigh for a period of one year. Biopsy from the lesion showed suprabasal acantholysis with loss of intercellular bridges resulting in a dilapidated brick-wall appearance; characteristic of Hailey – Hailey disease. Treatment of this disease till date is far from satisfactory