Cancer Innovation Scholars

Triple-negative breast cancer accounts for about 10-15% of all breast cancer cases and is highly common in younger women and women of African descent. This subtype lacks expression of estrogen receptors (ER), progesterone receptors (PR), and HER2 protein, limiting treatment options. We designed shear-thinning, thixotropic multidomain peptide hydrogels containing an apoptosis signaling domain to examine as a carrier for sustained chemotherapeutics. Hydrogels were characterized using rheology, circular dichroism, fourier transform infrared spectroscopy, and cytocompatibility assays to determine injectability and cytocompatibility.

We focused on using machine learning models to expedite pneumonia diagnosis in children from medical images. Using a dataset of pediatric chest X-rays from Guangzhou, China, we developed CNN algorithms that achieved accuracies greater than 90% on training data and 70% on test data. Our results demonstrate that CNNs can accurately identify pneumonia and could have practical applications in shortening diagnosis time and leading to quicker treatments.

ESSENCE (Electrochemical Sensor that uses a Shear-Enhanced, flow-through Nanoporous Capacitive Electrode) is a sensor platform that overcomes electrochemical sensor limitations. The device consists of a microfluidic channel with interdigitated microelectrodes, offering unprecedented sensitivity through receptor probe design and electrode configuration. Our study focused on detecting microtoxins in freshwater at 0.01, 0.1, 1, and 10 ppb concentrations, providing accurate and speedy diagnosis capabilities.

Chemical Warfare Agents are weapons of mass destruction that impose lethal effects including cancer through skin absorption. We developed a physiologically based pharmacokinetic (PBPK) computer modeling approach to assess risk posed by toxic chemicals. Complex partial differential equations were solved using Mathematica to evaluate liquid chemical agent diffusion through different skin layers, providing crucial insights for protection and treatment strategies.

Platinum nanoparticles (PtNPs) show potent anticancer effects with low toxicity in healthy cells. We performed platinum ion release studies using ICP-MS to test if PtNPs work by releasing Pt2+ rather than increasing ROS. We also studied protein corona formation and aggregation behavior in bovine blood plasma using nanoparticle tracking analysis, providing valuable information for designing safe and effective PtNP drug delivery systems for cancer treatment.

We developed electrospun piezoelectric nanofibers for a wearable cancer detection biosensor. The device layers PDMS, carbon nanotubes, electrospun nanofibers, PBS, and linker solutions to detect prostate cancer through PSA antibody-antigen interactions. This self-powered biosensor converts mechanical stress from the human body into electrical charge, eliminating the need for batteries and enabling continuous monitoring of PSA levels in the bloodstream.

Bioprinted hydrogel-based microfluidic models can mimic cellular composition and extracellular matrix properties of tumor tissue for personalized medicine development. We formed spheroids in low attachment plates and encapsulated them in 5% GelMA hydrogels using light-based bioprinting. Cell spheroids remained viable and formed hypoxic cores similar to in-vivo conditions, demonstrating GelMA's capability to provide a biomimicking extracellular matrix for cancer research.

PFOA has a half-life longer than 92 years in water and poses significant cancer risks. Our electrochemical impedance spectroscopy (EIS) platform provides rapid, sensitive PFOA detection in field conditions. Using Zirconium-based MOFs (UiO-66 and UiO-66 NH2) with microfluidic impedance sensors, we demonstrated proof-of-concept detection of minute PFOA quantities, offering advantages over traditional chromatography-mass spectroscopy methods.

Digital light processing (DLP) 3D printing technology is advancing for medical applications. We analyzed the impact of molecular weight on PEGDA curing properties under DLP printing. Solutions with varying molecular weights (575, 700, 4000, 6000 Mn) showed that higher molecular weights increase curing time but decrease resolution. For tissue engineering applications requiring high-resolution prints, PEGDA 575 Mn proved most appropriate.