Use of Large, Immunosignature Databases to Pose New Questions About Infection and Health Status

abstract: Immunosignature is a technology that retrieves information from the immune system. The technology is based on microarrays with peptides chosen from random sequence space. My thesis focuses on improving the Immunosignature platform and using Immunosignatures to improve diagnosis for diseases. I first contributed to the optimization of the immunosignature platform by introducing scoring metrics to select optimal parameters, considering performance as well as practicality. Next, I primarily worked on identifying a signature shared across various pathogens that can distinguish them from the healthy population. I further retrieved consensus epitopes from the disease common signature and proposed that most pathogens could share the signature by studying the enrichment of the common signature in the pathogen proteomes. Following this, I worked on studying cancer samples from different stages and correlated the immune response with whether the epitope presented by tumor is similar to the pathogen proteome. An effective immune response is defined as an antibody titer increasing followed by decrease, suggesting elimination of the epitope. I found that an effective immune response usually correlates with epitopes that are more similar to pathogens. This suggests that the immune system might occupy a limited space and can be effective against only certain epitopes that have similarity with pathogens. I then participated in the attempt to solve the antibiotic resistance problem by developing a classification algorithm that can distinguish bacterial versus viral infection. This algorithm outperforms other currently available classification methods. Finally, I worked on the concept of deriving a single number to represent all the data on the immunosignature platform. This is in resemblance to the concept of temperature, which is an approximate measurement of whether an individual is healthy. The measure of Immune Entropy was found to work best as a single measurement to describe the immune system information derived from the immunosignature. Entropy is relatively invariant in healthy population, but shows significant differences when comparing healthy donors with patients either infected with a pathogen or have cancer.Dissertation/ThesisDoctoral Dissertation Molecular and Cellular Biology 201

An Integrative Approach to Mindfulness-Based Symptom Management for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic health condition; its etiology is poorly understood, and treatment options are limited to management of symptoms. Current recommended treatment options are controversial, and evidence of effectiveness is limited. This paper proposes a novel model for symptom management of ME/CFS using mindfulness-based interventions, cognitive behavioural therapy (CBT), and relaxation techniques. A comprehensive review of available evidence is used to support this approach. The idea is that, working synergistically, these three approaches, grounded by mindfulness-based principles, can address many of the symptoms of the illness and help patients better cope and manage their day-to-day lives. This work is particularly important in a field that is under-researched and under-funded. There is still little understanding of pathology, or viable treatments, for ME/CFS patients. Yet there are millions of individuals afflicted with ME/CFS who deserve current scientifically-validated treatment options. In the absence of curative options, treatment alternatives must recognize the gravity of, and how best to address, the unique symptomology of the condition. The literature review suggests that the combined use of mindfulness, CBT and restorative yoga can be effective in individual symptom management for ME/CFS. However, the limitations are that this three-pronged model has not yet been empirically tested. This project leaves the door open for, and establishes the importance of, future research