A self-enhanced electrochemiluminescence array chip for portable label-free detection of SARS-CoV-2 nucleocapsid protein with smartphone.

SARS-CoV-2 antigen detection plays a key role in the rapid diagnosis of COVID-19. However, current clinically used immunoassays are often limited by assay throughput, sensitivity, accuracy, and field operating conditions. To address these challenges, we constructed a self-enhanced electrochemiluminescence (ECL) array chip (SE2AC) for highly sensitive and label-free detection of SARS-CoV-2 nucleocapsid protein (N protein) with a facile and portable assay setup. Firstly, the self-enhanced ECL nanomaterials with inherent film-forming properties were synthesized by co-doping Ru(bpy)32+ and polyethyleneimine (PEI) in silica nanoparticles (Ru/PEI@SiO2). Secondly, a resistance-induced potential difference-based single-electrode electrochemical system (SEES) was adapted to serve as the electrode array to facilitate one-step assembly without the need for chip alignment. Thirdly, the chip electrode array was functionalized with the synthesized self-enhanced ECL emitters and captured antibodies. In addition, a portable detection box equipped with a smartphone was 3D-printed to serve as the chip holder and "dark room" for imaging acquisition. The SE2AC performance was validated with N protein with a limit of detection (LOD) of 0.47 pg/mL in the range of 1-10,000 pg/mL. Furthermore, the chip successfully detected the viral antigen residue as low as 1.92 pg/mL from diluted rehabilitation patients' serum samples. This is the first study reporting label-free detection of SARS-Cov-2 N protein based on a self-enhanced ECL immunosensor, which provides a novel facile method for highly sensitive diagnosis of COVID-19 with high throughput, portability, and low cost.

Emission Onset Time-Adjustable Chemiluminescent Gold Nanoparticles with Ultrastrong Emission for Smartphone-Based Immunoassay of Severe Acute Respiratory Syndrome Coronavirus 2 Antigen.

Recently, our group reported a chemical timer approach to manipulate the onset time of chemiluminescence (CL) emission. However, it is still in the proof-of-concept stage, and its analytical applications have not been explored yet. Nanomaterials have merits of good catalytic effect, large specific surface area, good biocompatibility, and ease of self-assembly, which are ideal for constructing analytical-interfaces for bioassays. Herein, an emission onset time-adjustable chemiluminescent L012-Au/Mn2+ was synthesized for the first time by modifying Mn2+ on the surface of L012-protected gold nanoparticle. By using H2O2 and NaHCO3 as coreactants, L012-Au/Mn2+ could not only generate an ultrastrong and long-time CL emission but also its CL emission onset time could be adjusted by the addition of thiourea, which could effectively eliminate interference from the addition of coreactants, shorten the exposure time, reduce the detection background, and finally achieve high sensitivity CL imaging analysis. On this basis, a label-free CL immunoassay was constructed with a smartphone-based imaging system for high-throughput and sensitive determination of severe acute respiratory syndrome coronavirus 2 nucleocapsid (N) protein. The CL image of the immunoassay with different concentrations of N proteins was captured in one photograph 100 s after the injection of H2O2 with a short exposure time of 0.5 s. The immunoassay showed good linearity over the concentration range of 1 pg/mL to 10 ng/mL with a detection limit of 0.13 pg/mL, which was much lower than the reported CCD imaging detection method. In addition, it showed good selectivity and stability and was successfully applied in serum samples from healthy individuals and COVID-19 rehabilitation patients.

The Predictive Value of Magnetic Resonance Imaging-based Texture Analysis in Evaluating Histopathological Grades of Breast Phyllodes Tumor.

PURPOSE: Knowing the distinction between benign and borderline/malignant phyllodes tumors (PTs) can help in the surgical treatment course. Herein, we investigated the value of magnetic resonance imaging-based texture analysis (MRI-TA) in differentiating between benign and borderline/malignant PTs. METHODS: Forty-three women with 44 histologically proven PTs underwent breast MRI before surgery and were classified into benign (n = 26) and borderline/malignant groups (n = 18 [15 borderline, 3 malignant]). Clinical and routine MRI parameters (CRMP) and MRI-TA were used to distinguish benign from borderline/malignant PT. In total, 298 texture parameters were extracted from fat-suppression (FS) T2-weighted, FS unenhanced T1-weighted, and FS first-enhanced T1-weighted sequences. To evaluate the diagnostic performance, receiver operating characteristic curve analysis was performed for the K-nearest neighbor classifier trained with significantly different parameters of CRMP, MRI sequence-based TA, and the combination strategy. RESULTS: Compared with benign PTs, borderline/malignant ones presented a higher local recurrence (p = 0.045); larger size (p < 0.001); different time-intensity curve pattern (p = 0.010); and higher frequency of strong lobulation (p = 0.024), septation enhancement (p = 0.048), cystic component (p = 0.023), and irregular cystic wall (p = 0.045). TA of FS T2-weighted images (0.86) showed a significantly higher area under the curve (AUC) than that of FS unenhanced T1-weighted (0.65, p = 0.010) or first-enhanced phase (0.72, p = 0.049) images. The texture parameters of FS T2-weighted sequences tended to have a higher AUC than CRMP (0.79, p = 0.404). Additionally, the combination strategy exhibited a similar AUC (0.89, p = 0.622) in comparison with the texture parameters of FS T2-weighted sequences. CONCLUSION: MRI-TA demonstrated good predictive performance for breast PT pathological grading and could provide surgical planning guidance. Clinical data and routine MRI features were also valuable for grading PTs.