Rapid detection of microorganisms in a fish infection microfluidics platform.

Inadequate access to clean water is detrimental to human health and aquatic industries. Waterborne pathogens can survive prolonged periods in aquatic bodies, infect commercially important seafood, and resist water disinfection, resulting in human infections. Environmental agencies and research laboratories require a relevant, portable, and cost-effective platform to monitor microbial pathogens and assess their risk of infection on a large scale. Advances in microfluidics enable better control and higher precision than traditional culture-based pathogen monitoring approaches. We demonstrated a rapid, high-throughput fish-based teleost (fish)-microbe (TelM) microfluidic-based device that simultaneously monitors waterborne pathogens in contaminated waters and assesses their infection potential under well-defined settings. A chamber-associated port allows direct access to the animal, while the transparency of the TelM platform enables clear observation of sensor readouts. As proof-of-concept, we established a wound infection model using Pseudomonas aeruginosa-contaminated water in the TelM platform, where bacteria formed biofilms on the wound and secreted a biofilm metabolite, pyoverdine. Pyoverdine was used as fluorescent sensor to correlate P. aeruginosa contamination to infection. The TelM platform was validated with environmental waterborne microbes from marine samples. Overall, the TelM platform can be readily applied to assess microbial and chemical risk in aquatic bodies in resource-constrained settings.

A density-based threshold model for evaluating the separation of particles in heterogeneous mixtures with curvilinear microfluidic channels.

Particle separation techniques play an important role in biomedical research. Inertial focusing based microfluidics using nonlinear channels is one of the promising label-free technologies for biological applications. The particle separation is achieved as a result of the combination of inertial lift force (FL) and Dean drag force (FD). Although the mathematical expressions of FL and FD have been well derived in prior studies, they are still complicated, which limits their popularity in practice. Recent studies modified these expressions through experiments and proposed a threshold model, which assumes that only particles larger than the threshold will be well focused. Although this threshold model has been used in recent studies, two varying versions of the threshold model (TM1 and TM2) prevents standardisation in practice. In addition, both models were developed with regular low-density particles and may not be applicable to samples with higher density or samples with irregular shapes. Here, we evaluated the threshold models with samples of different densities. Based on these evaluations, we derived a modified model (TM4), which additionally considers the factor of particle density to improve the accuracy of existing models. Our results demonstrated that TM4 could more reliably predict the sorting efficiency of samples within a wider density range.

Urine biopsy technologies: Cancer and beyond.

Since the discovery of circulating tumor cells in 1869, technological advances in the study of biomarkers from liquid biopsy have made it possible to diagnose disease in a less invasive way. Although blood-based liquid biopsy has been used extensively for the detection of solid tumors and immune diseases, the potential of urine-based liquid biopsy has not been fully explored. Advancements in technologies for the harvesting and analysis of biomarkers are providing new opportunities for the characterization of other disease types. Liquid biopsy markers such as exfoliated bladder cancer cells, cell-free DNA (cfDNA), and exosomes have the potential to change the nature of disease management and care, as they allow a cost-effective and convenient mode of patient monitoring throughout treatment. In this review, we addressed the advancement of research in the field of disease detection for the key liquid biopsy markers such as cancer cells, cfDNA, and exosomes, with an emphasis on urine-based liquid biopsy. First, we highlighted key technologies that were widely available and used extensively for clinical urine sample analysis. Next, we presented recent technological developments in cell and genetic research, with implications for the detection of other types of diseases, besides cancer. We then concluded with some discussions on these areas, emphasizing the role of microfluidics and artificial intelligence in advancing point-of-care applications. We believe that the benefits of urine biopsy provide diagnostic development potential, which will pave opportunities for new ways to guide treatment selections and facilitate precision disease therapies.