Breast cancer is on the rise, but new tools for early detection could save lives.
In Journal of Vacuum Science & Technology B, by AIP Publishing, researchers from the University of Florida and National Yang Ming Chiao Tung University in Taiwan reported successful results from a hand-held breast cancer screening device that can detect breast cancer biomarkers from a tiny sample of saliva. Their biosensor design uses common components, such as widely available glucose testing strips and the open-source hardware-software platform Arduino.
“Imagine medical staff conducting breast cancer screening in communities or hospitals,” author Hsiao-Hsuan Wan said. “Our device is an excellent choice because it is portable — about the size of your hand — and reusable. The testing time is under five seconds per sample, which makes it highly efficient.”
The device uses paper test strips treated with specific antibodies that interact with the targeted cancer biomarkers. A saliva sample is placed on the strip, and pulses of electricity are sent to electrical contact points on the biosensor device. These pulses cause the biomarkers to bind to the antibodies and alter the charge and capacitance over the electrode. This produces a change in the output signal, which can be measured and translated into digital information about how much biomarker is present.
The design is revolutionary compared to its alternatives. Mammograms, ultrasounds, and MRIs are costly and invasive and require large, specialized equipment, present low-dose radiation exposure, and can take days or weeks to return test results.
“In many places, especially in developing countries, advanced technologies like MRI for breast cancer testing may not be readily available,” Wan said. “Our technology is more cost-effective, with the test strip costing just a few cents and the reusable circuit board priced at $5. We are excited about the potential to make a significant impact in areas where people might not have had the resources for breast cancer screening tests before.”
The biosensor requires just a drop of saliva, and it can provide accurate test results even if the concentration of the cancer biomarker in the sample is only one quadrillionth of a gram, or one femtogram, per milliliter.
“The highlight for me was when I saw readings that clearly distinguished between healthy individuals and those with cancer,” Wan said. “We dedicated a lot of time and effort to perfecting the strip, board, and other components. Ultimately, we’ve created a technique that has the potential to help people all around the world.”
Reference
High sensitivity saliva-based biosensor in detection of breast cancer biomarkers: HER2 and CA15-3 featured
Hsiao-Hsuan Wan, Haochen Zhu, Chao-Ching Chiang, Jian-Sian Li, Fan Ren , Cheng-Tse Tsai, Yu-Te Liao, Dan Neal, Josephine F. Esquivel-Upshaw, Stephen J. Pearton
https://pubs.aip.org/avs/jvb/article/42/2/023202/3262988/High-sensitivity-saliva-based-biosensor-in
Nanoparticles are found in many everyday products, from cosmetics and textiles to air pollution. While they offer many benefits, scientists still need better ways to understand how long-term exposure may affect our skin. Researchers from Alfaro-Moreno group at INL have developed a new skin-on-a-chip platform that closely mimics human skin, providing a more realistic way to study how nanoparticles interact with our body's first protective barrier. Unlike conventional lab models (which grow...
Researchers at the University of Osaka have developed an autonomous solid-state nanopore that senses molecules, generates electrical signals, and retains memory of recent events without external control. Chemical reactions inside the pore continuously reshape its structure, producing molecule-specific signal patterns. Machine learning distinguished DNA nucleotides and amino acids from these signatures. Published in ACS Nano.
Scientists have developed “glycan atlassing,” a breakthrough super-resolution technique that maps the precise nanoscale architecture of sugars on cell surfaces. Published in Nature Nanotechnology, the method reveals that the spatial organization of glycans encodes critical information about cell state — opening powerful new possibilities for cancer diagnostics, stem cell research, and precision nanomedicine.
