Developing a surrogate marker to asthmatic tissue: the nasal cavity

Our research proposal will explore the unified airway theory and determine whether the sinuses express biological similarities to the lungs in participants who only clinically present with Chronic Rhinosinusitis (CRS)or asthma and not with both diseases. The unified airway theory suggests that the lower (lungs) and upper (sinuses) airways are intrinsically connected and function together as one unit and the biological processes, such as inflammation, in the lower airway are similar in the upper airway.

Deep Immunophenotyping of the Immune Response in Obstructive and Interstitial Lung Disease: Optimizing a Cellular and Protein Biomarker Discovery Pipeline for Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF), is a chronic debilitating lung disorder that affects thousands of Canadians and millions of individuals worldwide. The signs and symptoms of IPF often overlap with other common respiratory illnesses making a definitive diagnosis of this disease difficult. As a result, patients are frequently misdiagnosed and treated with inappropriate therapies. As such, there is a unmet clinical need to develop blood-based biomarkers for the confirmation of IPF to minimize the incidence of misdiagnosis.

Improved Phenotyping of Macrophages Using Cell Line Models, Gene Expression Signatures, and Protein Secretion Data

Chronic obstructive pulmonary disease (COPD) is a 3rd leading cause of death, which decreases lung function due to irreversible airway obstruction. Lung immune cells, such as macrophages, play an important role in the disease progression. However, researchers don’t fully understand their diversity and functions. Models of macrophages are useful to better understand patient macrophages. We will first obtain 3 types of model macrophages and compare their characteristics (such as gene expression and secreted proteins) with recently published COPD alveolar macrophage data from literature.

Rational Nanoparticle Design for Efficient Transmucosal Gene Delivery

Cystic fibrosis (CF) is the most common fatal genetic disease affecting Canadian children and young adults, without a cure. Nanoparticles (NPs) have emerged as a promising strategy for delivering genetic treatments for various diseases. However, the development of NPs to treat CF has encountered many obstacles. This is mostly because the human airways, which constantly secrete mucous, pose a challenging environment for the efficient NP-mediated delivery of gene therapy. Several strategies have been proposed and tested; however, rational design criteria for these NPs are still missing.

Multi-SNP prediction model for lung function decline

Chronic obstructive pulmonary disease (COPD) is a 3rd leading cause of death (1) which decreases lung function due to irreversible airway obstruction. The main indicator of the progression of COPD is a rate of the forced expiratory volume of 1 second (FEV1) decline. The intern will build the prediction model for the slope of FEV1 decline and find the genetic variants that affect these FEV1 changes. Some variable selection machine learning algorithms will be applied to screen important genetic variants and the performance of prediction on FEV1 change will be compared.

Eng/aging and HIV: Knowledge Exchange Between Administrative Data Project and Aging Individuals with HIV/AIDS in British Columbia

To an unprecedented degree in the history of HIV/AIDS, people with HIV/AIDS (PLHIV) are aging largely owing to the success of treatment. As a relatively new phenomenon, research on HIV/AIDS and aging is only just emerging, and remains largely epidemiological in focus. One leading epidemiological study called COAST comes from the B.C. Centre for Excellence in HIV/AIDS, a world-renowned HIV/AIDS research organization. COAST assembles administrative epidemiological data to examine aging PLHIV health trends in B.C.

Best Practice Framework for Healthcare Innovation Infrastructure, Implementation and Learning Campus

This study focuses on identifying best practices to guide the development of the PHC healthcare innovation and learning campus. PHC and the UBC research team seeks to build a design structure matrix (DSM) to inform the PHC about governance, key process, organizing structures, operating practices, intellectual property (IP), partnering approaches, partnership agreements, and implementation plans for developing an innovation hub ecosystem.

A Clinical Proteomic Test for Patient Care

There are 2.6 million Canadians with Chronic Obstructive Pulmonary Disease (COPD). COPD is a disease characterized by progressive loss of lung function that leads to shortness of breath, poor quality of life, reduced productivity, emergency visits, hospitalizations and mortality. The World Health Organization estimates that COPD will be the 3rd leading cause of death worldwide by 2030, accounting for more than 7 million deaths/year and 11,000 deaths/year in Canada.

Platform development to assay immune cell chemotaxis in chronic obstructive pulmonary disease (COPD)

Chronic obstructive pulmonary disease (COPD) is an important global health problem afflicting 384 million people and causing 3 million deaths worldwide each year. Currently, there are no effective therapies for COPD patients. In this proposal, we are developing a novel technology that will both monitor the severity of disease in COPD patients, and allow researchers to better study potential targets and pathways for the design of new COPD drugs. Immune cells, such as neutrophils and macrophages, play important roles in the lungs of COPD patients.

Machine learning methods for automatic diagnosis, severity assessment, prognosis, and disease understanding of COPD

Chronic Obstructive Pulmonary Disease (COPD) is a progressive, debilitating, chronic respiratory disease that affects 600 million people worldwide and is responsible for 3 million deaths worldwide each year. Given the recent advances in artificial intelligence (AI) and the availability of large datasets from both the public and private sectors, our project applies AI to analyze large-scale medical datasets and develops tools capable of performing accurate diagnosis, severity assessment, and prognosis of COPD.

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