Faculty of Medicine

My project focuses on evaluating the knockdown of multiple genes and assessing their impact on treatment efficacy in sepsis and CAP patients. Specifically, I aim to develop novel drugs utilizing siRNA-LNPs through nanoparticle formulation modifications and exploring various siRNA sequences.
 
 

My research will involve exploring the early underlying mechanisms in development of Neuroendocrine Prostate Cancer from advanced prostate adenocarcinoma.

I am interested in sex differences in the regulation of protein translation in pancreatic beta-cells. Pancreatic beta-cells are the only cells in the body that secrete insulin, a peptide hormone that lowers blood glucose. Therefore, beta-cells must synthesise and process large quantities of protein. In diabetes, beta-cells are subject to endoplasmic reticulum (ER) stress, when insulin demand overwhelms the cell's capacity to process proteins.

Despite its inherent potential, functional magnetic resonance imaging (fMRI) has not been fully integrated into clinical cognitive assessments yet. This research project seeks to bridge this gap by developing an fMRI-based neurocognitive assessment. A notable innovation of this project is the integration of eye-tracking technology with fMRI, which is anticipated to reduce artifacts caused by button presses, thus potentially enhancing the quality of fMRI data.

Organ transplantation is a life-saving therapy for end-stage organ failure. Ischemia–reperfusion injury that leads to delayed graft function (DGF) and immune-mediated rejection are unmet challenges. The key to success in organ transplantation is to suppress the immune system and prevent rejection. Current treatment using immunosuppressive drugs has reduced the incidents of rejection; however, such global immunosuppression leads to severe side effects. Thus, new approaches are needed for improved graft survival.

Develop and apply new algorithms and machine learning methods for analyzing proteomic data and integrating multi-omics data (including genomics, transcriptome, other MS data like metabolomics and lipidomics, and metagnomics).