Pipette-operable microfluidic devices with hydrophobic valves in sequential dispensing with various liquid samples: multiplex disease assay by RT-LAMP.

Microfluidic dispensing technologies often require additional equipment, posing challenges for their integration into point-of-care testing (POCT) applications. In response to this challenge, we have developed a pipette-operable microfluidic device fabricated using 3D printing technology for precise liquid dispensing. This device features three reaction chambers and three distinct hydrophobic valves to control the flow direction of liquids. Through these valves, the pipette-operable microfluidic device can sequentially dispense and isolate the liquid into the three reaction chambers, allowing for the individual conduction of three distinct reactions. These hydrophobic valves, with optimized flow resistance and burst pressure, can sustain a volumetric flow rate of up to 25 µL s-1, making them compatible with a standard pipette, a syringe, or a dropper operation. Furthermore, the device is successfully used to operate with various liquids, including BSA, DMEM, FBS, plasma, and blood, representing that the device has the potential to be used for various applications. Additionally, distinct RT-LAMP primer sets have been incorporated for diagnosing SARS-CoV-2, influenza A, and influenza B within each chamber through lyophilization. This pipette-operable microfluidic device serves as a versatile tool for diagnosing these three diseases using a single loading process, with results readable by the naked eye or image assay within 30 minutes of incubation. Finally, the design concepts are extended to engineer a microfluidic device with 20 reaction chambers, offering significant potential for multi-disease diagnostics.

Blood multiomics reveal insights into population clusters with low prevalence of diabetes, dyslipidemia and hypertension.

Diabetes, dyslipidemia and hypertension are important metabolic diseases that impose a great burden on many populations worldwide. However, certain population strata have reduced prevalence for all three diseases, but the underlying mechanisms are poorly understood. We sought to identify the phenotypic, genomic and metabolomic characteristics of the low-prevalence population to gain insights into possible innate non-susceptibility against metabolic diseases. We performed k-means cluster analysis of 16,792 subjects using anthropometric and clinical biochemistry data collected by the Taiwan Biobank. Nuclear magnetic resonance spectra-based metabolome analysis was carried out for 217 subjects with normal body mass index, good exercise habits and healthy lifestyles. We found that the gene APOA5 was significantly associated with reduced prevalence of disease, and lesser associations included the genes HIF1A, LIMA1, LPL, MLXIPL, and TRPC4. Blood plasma of subjects belonging to the low disease prevalence cluster exhibited lowered levels of the GlycA inflammation marker, very low-density lipoprotein and low-density lipoprotein cholesterol, triglycerides, valine and leucine compared to controls. Literature mining revealed that these genes and metabolites are biochemically linked, with the linkage between lipoprotein metabolism and inflammation being particularly prominent. The combination of phenomic, genomic and metabolomic analysis may also be applied towards the study of metabolic disease prevalence in other populations.