RESUMO
Recent advances in the recognition of biological samples using machine vision have made this technology increasingly important in research and detection. Image segmentation is an important step in this process. This study focuses on how to reduce the interference factors such as the overlap between different types (or within the same type) of urine cells according to microfluidics and improve the machine vision segmentation accuracy for cell images. In this study, we demonstrate that the platform can realize this hypothesis using urine cell image segmentation as an example application. We first discuss the reported urine cell droplet microfluidic chip system, which can realize the test conditions in which urine cells are encapsulated in the droplet and isolated from salt crystallization and/or bacteria and other urine-formed elements. Then, based on the analysis conditions set in the aforementioned experiment, the proportions of red blood cells, white blood cells, and squamous epithelial cells covered by various formed elements in the total urine cells in the same urine sample are measured. We simultaneously analyze the percentage of urine cells covered by salt crystallization and the incidence of overlapping between urine cells. Finally, the Otsu algorithm is used to segment the urine cell images encapsulated by the droplet and the urine cell images not encapsulated by the droplet, and the Dice, Jaccard, precision, and recall values are calculated. The results suggest that the method of encapsulating single cells based on droplets can improve the image segmentation effect without optimizing the algorithm.
Assuntos
MicrofluídicaRESUMO
Competitive immunoassays have unique advantages in the detection of small molecules and are widely used in clinical practice. However, the concentrations of some analytes usually vary greatly among different populations, which makes it difficult to balance the sensitivity and detection range of competitive immunoassays. Studies have shown that using haptens with weaker affinity for specific antibodies as competitive antigens can help improve the sensitivity of the method. Here, we developed a competitive light initiated chemiluminescence assay based on the combination of antigens with different affinities, which has high sensitivity and wide detection range. As a proof of concept, estradiol was used as the analyte. After the mixing ratio was optimized, the two labeled haptens played different competitive roles due to the different concentrations of estradiol to be tested, which improved the sensitivity of estradiol detection, while ensuring a certain detection range. The limit of detection of this method was 5.30 pg/mL, which is lower than most current estradiol immunoassay kits. Good linearity (R 2 = 0.9902) was obtained between estradiol concentrations of 17.07-2376.22 pg/mL. This study provides a new solution for the detection of small molecule biomarkers with a large concentration span, which also has considerable potential in other immunological detection methods.
RESUMO
The clinical characteristics of excreted tumor cells can be found in the urine of bladder cancer patients, meaning the identification of tumor cells in urine can assist in bladder cancer diagnosis. The presence of white blood cells and epithelial cells in the urine interferes with the recognition of tumor cells. In this paper, a technique for detecting cancer cells in urine based on microfluidics provides a novel approach to bladder cancer diagnosis. The bladder cancer cell line (T24) and MeT-5A were used as positive bladder tumor cells and non-tumor cells, respectively. The practicality of the tumor cell detection system based on microfluidic cell chip detection technology is discussed. The tumor cell (T24) concentration was around 1 × 104 to 300 × 104 cells/mL. When phosphate buffer saline (PBS) was the diluted solution, the tumor cell detected rate was 63-71% and the detection of tumor cell number stability (coefficient of variation, CV%) was 6.7-4.1%, while when urine was the diluted solution, the tumor cell detected rate was 64-72% and the detection of tumor cell number stability (CV%) was 6.3-3.9%. In addition, both PBS and urine are tumor cell dilution fluid solutions. The sample was analyzed at a speed of 750 microns per hour. Based on the above experiments, a system for detecting bladder cancer cells in urine by microfluidic analysis chip technology was reported. The rate of recognizing bladder cancer cells reached 68.4%, and the speed reached 2 mL/h.