This research investigates how glioblastoma brain cancer cells invade healthy brain tissue. Using patient-derived tumor organoids and traction force microscopy, the study measures how cancer cells generate and apply forces to move through the brain. Understanding these invasion mechanisms could help develop therapies that slow tumor spread and improve patient survival.

This research develops “nanozymes,” nanoparticle-based catalysts that activate cancer drugs directly at tumor sites. Instead of carrying large amounts of chemotherapy drugs, nanozymes locally trigger inactive drugs into their active form only within cancer tissue. Early mouse studies show effective tumor destruction with significantly reduced side effects compared to conventional chemotherapy.

This research uses artificial intelligence to predict the progression of Alzheimer’s disease and cancer using medical imaging data. By analyzing brain scans, tumor scans, and treatment responses, AI models can forecast disease development and treatment outcomes, enabling earlier intervention, more personalized care, and improved quality of life for aging populations.

This research develops nanoscale “smart package” delivery systems for PROTAC cancer drugs. Antibody nanogel conjugates selectively target cancer cells, enter them, and release therapeutic molecules while minimizing exposure to healthy tissue. The approach improves delivery efficiency and aims to reduce the severe side effects that often limit cancer treatment.

This research develops synthetic genetic circuits that automatically alternate CAR T-cell activity between active cancer killing and recovery states. By preventing immune-cell exhaustion, these circuits could improve cancer immunotherapy effectiveness. The work also suggests broader biomedical applications where controlled cycling of gene activity may enhance treatment safety, longevity, and therapeutic performance.

This research introduces iCares, a smart wound-monitoring bandage designed to detect infection and inflammation before visible symptoms appear. Using biosensors, fluid sampling, and machine learning, the system provides real-time wound analysis, enabling earlier intervention, personalized treatment, reduced complications, and improved healing outcomes for patients with chronic wounds.

This research develops a rapid, accessible technique for analyzing extracellular vesicles (EVs), tiny cellular messengers found in blood. By measuring both the size and molecular contents of individual EVs, the method could enable earlier and more accurate diagnosis of diseases such as cancer, Alzheimer’s, and HIV using simple blood samples.

Using a Twilight analogy, this research explains antibiotic-resistant bacteria as “vampires” protected by membranes. By crystallizing membrane proteins and analyzing them with X-ray techniques, the study reveals their structure and function. This enables precise drug design to block these proteins, potentially overcoming antibiotic resistance and targeting harmful bacteria more effectively.

This research uses spatial transcriptomics to map interactions between T cells, cancer cells, and immunosuppressive cells in tumours. Findings suggest cancer suppresses immune responses by surrounding and weakening T cells. The work aims to improve immunotherapy and enable personalised cancer treatment through detailed tumour mapping.

This research develops targeted radiopharmaceutical therapies for HER2-positive cancers. By attaching radioactive isotopes to trastuzumab, treatment delivers precise radiation to cancer cells, overcoming drug resistance. The work includes creating practical drug kits and aims to improve cancer outcomes by replacing non-specific therapies with highly accurate, targeted interventions.