Home Department: Biology
Supported by: The Rose Hills Foundation
Mentor: Samuel Yang, Emergency Medicine

Sepsis is the primary cause of infection-related death in the world and accounts for 60-80% of all deaths in developing countries; however, current diagnostics for the condition are time-consuming and often lead to false-negative results, making them insufficient for proper patient treatment. Annie is developing a rapid test for sepsis using high-resolution melt and machine learning to identify pathogens directly from clinical samples while simultaneously profiling their antibiotic susceptibility. This project will improve not only patient outcomes in a clinical setting, but also the state of pathogen profiling in the scientific community. 

Poster presented at the Stanford Bio-X Interdisciplinary Initiatives Symposium on August 24, 2016:

Replacing Blood Culture: Combined Broad-Range Microbial ID and AST Directly from Whole Blood

Annie Hu¹, Nadya Andini¹, Samuel Yang¹
[Department of Emergency Medicine¹, Stanford University]

Home Department: Biology
Supported by: Bio-X
Mentor: Samuel Yang, Surgery

Annie is developing a method for distinguishing groups of Streptococcus pneumoniae based on their surface proteins. She is using high-resolution melt to "fingerprint" the different groups and to create a fast and cheap classification method for use in optimizing future pneumococcal vaccines and monitoring their effectiveness.

Poster presented at the Stanford Bio-X Interdisciplinary Initiatives Symposium on August 26, 2015:

DNA Melt as a Rapid Fingerprint for Broad-Range Pathogen Identification and Serotyping

Annie Hu¹, Nadya Andini¹, Samuel Yang¹
[Department of Emergency Medicine¹, Stanford University]