Rapid identification of pathogens with higher sensitivity and specificity plays a significant role in maintaining public health, environmental monitoring, controlling food quality, and clinical diagnostics. Different methods have been widely used in food testing laboratories, quality control departments in food companies, hospitals, and clinical settings to identify pathogens. Some limitations in current pathogens detection methods are time-consuming, expensive, and laborious sample preparation, making it unsuitable for rapid detection. Microfluidics has emerged as a promising technology for biosensing applications due to its ability to precisely manipulate small volumes of fluids. Microfluidics platforms combined with spectroscopic techniques are capable of developing miniaturized devices that can detect and quantify pathogenic samples. The review focuses on the advancements in microfluidic devices integrated with spectroscopic methods for detecting bacterial microbes over the past five years. The review is based on several spectroscopic techniques, including fluorescence detection, surface-enhanced Raman scattering, and dynamic light scattering methods coupled with microfluidic platforms. The key detection principles of different approaches were discussed and summarized. Finally, the future possible directions and challenges in microfluidic-based spectroscopy for isolating and detecting pathogens using the latest innovations were also discussed.

A fast and accurate method that is independent of physicians’ experience for the intraoperative examination of colorectal tumors is proposed by fusing elastic scattering spectrum with Raman spectrum and using an AI model called spec-transformer.

The incidence of infectious diseases has risen in recent years, leading to a significant surge in the demand for medical molecular detection. High-throughput molecular detection platforms play a crucial role in facilitating rapid and efficient molecular detection. Among the various techniques employed in high-throughput molecular detection, microliquid transfer stands out as one of the most frequently utilized methods. However, ensuring the accuracy of liquid transfer poses a challenge due to variations in the physical and chemical properties of different samples and reagents. In this study, a pipetting complementation model was developed specifically for the serum, paraffin oil, and throat swabs. The aim was to enhance the transfer accuracy of diverse liquids in the context of high-throughput molecular detection, ultimately ensuring detection reliability and stability. The experimental findings revealed notable improvements in pipetting accuracy after compensating for the three liquids. In particular, the pipetting error rates decreased by 52.5, 96, and 71.4% for serum, paraffin oil, and throat swabs, respectively. These results underscore the model’s effectiveness in providing reliable support for the precise transfer of liquids on the high-throughput molecular detection platform.