[Detection and analysis of moving reaction boundary-based electrophoresis distance using smartphone images]

Electrophoresis titration (ET) based on the moving reaction boundary (MRB) theory can detect the analyte contents in different samples by converting content signals into distance signals. However, this technique is only suitable for on-site qualitative testing, and accurate quantification relies on complex optical equipment and computers. Hence, applying this method to real-time point-of-care testing (POCT) is challenging. In this study, we developed a smartphone-based ET system based on a visual technique to achieve real-time quantitative detection. First, we developed a portable quantitative ET device that can connect to a smartphone; this device consisted of five components, namely, an ET chip, a power module, a microcontroller, a liquid crystal display screen, and a Bluetooth module. The device measured 10 cm×15 cm×2.5 cm, weighed 300 g, and was easy to hold. Thus, it is suitable for on-site testing with a run time of only 2-4 min. An assistant mobile software program was also developed to control the device and perform ET. The colored electrophoresis boundary can be captured using the smartphone camera, and quantitative detection results can be obtained in real time. Second, we proposed a quantitative algorithm based on ET channels. The software was used to recognize the boundary migration distance of three channels, a standard curve based on two given contents of the standards was established using the two-point method, and the content of the test sample was calculated. Human serum albumin (HSA) and uric acid (UA) were used as a model protein and biosample, respectively, to test the performance of the detection system. For HSA detection, different HSA solutions were mixed with a polyacrylamide gel (PAG) stock solution, phenolphthalein was added as an indicator, and sodium persulfate and tetramethyl ethylenediamine (TEMED) were used to promote polymerization to form a gel. For UA detection, agarose gel was filled into the ET channel, the UA sample, urate oxidase, and leucomalachite green were added into the anode cell and incubated for 20 min. ET was then performed. The fitting goodness (R2) values of HSA and UA were 0.9959 and 0.9935, respectively, with a linear range of 0.5-35.0 g/L and a log-linear range of 100-4000 μmol/L. The limits of detection for HSA and UA were 0.05 g/L and 50 μmol/L, respectively, and the corresponding relative standard deviations (RSDs) were not greater than 2.87% and 3.21%, respectively. These results demonstrate that the detection system has good accuracy and sensitivity. Clinical samples collected from healthy volunteers were used as target blood samples, and the developed system was used to measure serum total protein and UA levels. Serum samples from five volunteers were selected, standard curves of total serum protein and UA were established, and the test results were compared with hospital standard testing results. The relative errors for serum total protein and UA were less than 6.03% and 6.21%, respectively, and the corresponding RSDs were less than 3.72% and 5.84%, respectively. These findings verify the accuracy and reliability of the proposed detection system. The smartphone-based ET detection system introduced in this paper presents several advantages. First, it enables the portable real-time detection of total serum protein and UA. Second, compared with traditional ET strategies based on colored boundaries, it does not rely on optical detection equipment or computers to obtain quantitative detection results; as such, it can reduce the complexity of the operation and provide portability and real-time metrics. Third, the detection of two biomarkers, serum total protein and UA, is achieved on the same device, thereby improving the multitarget detection potential of the ET method. These advantages render the developed method a promising detection platform for clinical applications and real-time POCT.

[Determination of human serum total protein via electrophoresis titration and capacitively coupled contactless conductivity detection]

Serum total protein refers to the sum of all proteins in the serum, and its content determination is relevant to human health monitoring and disease diagnosis. However, existing detection techniques present a number of limitations; for example, the Kjeldahl method suffers from the negative effects of interfering substances such as non-protein nitrogen (NPN). Although the electrophoresis titration (ET) method has solved interference problems to some extent, the current ET technique relies on optical detection methods, which increases the tediousness of the operation. This study addresses the challenge of accurate serum total protein detection by combining the traditional ET technique with capacitively coupled contactless conductivity detection (C4D). The research contributions of this work are multifold. First, it presents the first development of an ET-C4D detection system, which consists of six components: an ET power module, an ET chip, a C4D sensing module, a detection module, a data acquisition card, and software. The developed system can capture the conductivity of substances in the channel using the software developed by our laboratory during ET. The detection system can be used to quantify the total protein content in human serum without the addition of specific labeling reagents or using optical detection equipment, and its running time is approximately 300 s. Second, this research proposes the corresponding principle of the system. Under an electric field, ion migration results in different pH levels before and after the boundary, leading to a protein surface charge difference. The maintenance of the electrical neutrality of the substances in the detection channel is related to the protein surface charge; therefore, the ion concentration distribution of the substances in the detection channel changes as the protein surface charge varies. A plot of conductivity as a function of running time showed an "inverted clock shape", first falling and then rising. Owing to the addition of different types and concentrations of proteins, the microenvironment of the entire system changes, resulting in different changes in conductivity. Third, the performance of the detection system was tested using human serum albumin (HSA) standard protein, which was mixed with polyacrylamide gel (PAG) mother liquor, riboflavin, etc., and irradiated under ultraviolet light for 10 min to form a gel. The ET experiments were then carried out. The shape of the conductivity curve was consistent with the proposed principle, and the higher the HSA concentration, the lower the conductivity curve trough, followed by a lagged time of the trough. Quantitative analysis of the conductivity signals showed that the linear range was 0.25-3.00 g/L, with a linearity of up to 0.98. The limit of detection (LOD) was 0.01 g/L, the relative standard deviation (RSD) was 1.90%, and the relative error of the test values was <7.20%, indicating the good detection stability and sensitivity of the system. Clinical samples collected from healthy volunteers were used as target blood samples for serum total protein content measurement using our detection system. Blood samples from a volunteer were used to obtain a standard curve, and the serum samples of other four volunteers were selected for ET-C4D and biuret detection. The results showed that the relative errors between the two methods were within 4.43%, indicating the accuracy and reliability of the detection system. The advantages of the ET-C4D detection system proposed in this paper are as follows: (i) ET-C4D realizes the rapid detection of total serum protein content based on the ET technique; (ii) compared with the traditional protein ET technique, the ET-C4D method does not rely on specific labeling components or optical detection equipment, thereby reducing the complexity of the operation; and (iii) the output signal of ET-C4D can be used for quantitative analysis with excellent analytical performance and high accuracy. These merits highlight the potential of the developed system for clinical application and biochemical analysis.