Fabrication of Fish Scale-Based Gelatin Methacryloyl for 3D Bioprinting Application

Gelatin methacryloyl (GelMA) is an ideal bioink that is commonly used in bioprinting. GelMA is primarily acquired from mammalian sources; however, the required amount makes the market price extremely high. Since garbage overflow is currently a global issue, we hypothesized that fish scales left over from the seafood industry could be used to synthesize GelMA. Clinically, the utilization of fish products is more advantageous than those derived from mammals as they lower the possibility of disease transmission from mammals to humans and are permissible for practitioners of all major religions. In this study, we used gelatin extracted from fish scales and conventional GelMA synthesis methods to synthesize GelMA, then tested it at different concentrations in order to evaluated and compared the mechanical properties and cell responses. The fish scale GelMA had a printing accuracy of 97%, a swelling ratio of 482%, and a compressive strength of about 85 kPa at a 10% w/v GelMA concentration. Keratinocyte cells (HaCaT cells) were bioprinted with the GelMA bioink to assess cell viability and proliferation. After 72 h of culture, the number of cells increased by almost three-fold compared to 24 h, as indicated by many fluorescent cell nuclei. Based on this finding, it is possible to use fish scale GelMA bioink as a scaffold to support and enhance cell viability and proliferation. Therefore, we conclude that fish scale-based GelMA has the potential to be used as an alternative biomaterial for a wide range of biomedical applications.

One-step colorimetric isothermal detection of COVID-19 with AI-assisted automated result analysis: A platform model for future emerging point-of-care RNA/DNA disease diagnosis

Colorimetric loop-mediated DNA isothermal amplification-based assays have gained momentum in the diagnosis of COVID-19 owing to their unmatched feasibility in low-resource settings. However, the vast majority of them are restricted to proprietary pH-sensitive dyes that limit downstream assay optimization or hinder efficient result interpretation. To address this problem, we developed a novel dual colorimetric RT-LAMP assay using in-house pH-dependent indicators to maximize the visual detection and assay simplicity, and further integrated it with the artificial intelligence (AI) operated tool (RT-LAMP-DETR) to enable a more precise and rapid result analysis in large scale testing. The dual assay leverages xylenol orange (XO) and a newly formulated lavender green (LG) dye for distinctive colorimetric readouts, which enhance the test accuracy when performed and analyzed simultaneously. Our RT-LAMP assay has a detection limit of 50 viral copies/reaction with the cycle threshold (Ct) value ≤ 39.7 ± 0.4 determined by the WHO-approved RT-qPCR assay. RT-LAMP-DETR exhibited a complete concordance with the results from naked-eye observation and RT-qPCR, achieving 100% sensitivity, specificity, and accuracy that altogether render it suitable for ultrasensitive point-of-care COVID-19 screening efforts. From the perspective of pandemic preparedness, our method offers a simpler, faster, and cheaper (∼$8/test) approach for COVID-19 testing and other emerging pathogens with respect to RT-qPCR.