Detection of SASR-CoV-2 plays a significant role in reducing the transmission of COVID-19. Antigen swab test is widely used for screening due to its low processing time and cost, while RT-PCR is used in patient monitoring since it is quite expensive. Although the antigen swab test is more affordable than the RT-PCR, it only generates a discrete result: positive or negative. Thus, it cannot be used for patient monitoring. A method using antigen-antibody binding and surface plasmon resonance (SPR) principle was developed in this research to create an affordable, instant, and quantified SARS-CoV-2 detection method. In this study, modified scFv is tested as a potential bioreceptor since it is easier to be expressed than the whole antibody. The results show that the scFv with the best potential was harvested from the periplasm of E. coli and purified. It has a maximum response at 8.02 RU, LOD at 8.34 ng/mL, linearity at 1.38 in the range of 25-200 ng/mL, and a determination coefficient at 92 percent.
Two years after SARS-CoV-2 caused the first case of COVID-19, we are now in the “new normal” period, where people’s activity has bounced back, followed by the easing of travel policy restrictions. The lesson learned is that the wide availability of accurate and rapid testing procedures is crucial to overcome possible outbreaks in the future. Therefore, many laboratories worldwide have been racing to develop a new point-of-care diagnostic test. To aid continuous innovation, we developed a plasmonic-based biosensor designed explicitly for portable Surface Plasmon Resonance (SPR). In this study, we designed a single chain variable fragment (scFv) from the CR3022 antibody with a particular linker that inserted a cysteine residue at the second position. It caused the linker to have a strong affinity to the gold surface through thiol-coupling and possibly become a ready-to-use bioreceptor toward a portable SPR gold chip without purification steps. The theoretical affinity of this scFv on spike protein was −64.7 kcal/mol, computed using the Molecular Mechanics Generalized Born Surface Area (MM/GBSA) method from the 100 ns molecular dynamics trajectory. Furthermore, the scFv was produced in Escherichia coli BL21(DE3) as a soluble protein. The binding activity toward Spike Receptor Binding Domain (RBD) SARS-CoV-2 was confirmed with a spot-test, and the experimental binding free energy of −10.82 kcal/mol was determined using portable SPR spectroscopy. We hope this study will be useful in designing specific and low-cost bioreceptors, particularly early in an outbreak when the information on antibody capture is still limited.
Early lymphoma diagnosis is essential to improve the patients' survival rate and avoid irreversible damage. Immunohistochemistry-based lymphoma diagnostics is an expensive and time-consuming process, especially in developing countries with limited resources. Image-based lymphoma diagnostics might serve as an inexpensive, yet less accurate alternative to immunohistochemistry-based methods. One challenge in image-based methods is that carcinoma can occur in the same organ as lymphoma, thus making it hard to differentiate the two types of cancer. To assist lymphoma diagnostics, this study proposes a deep learningbased method to classify nasopharyngeal microscopic biopsy images into one of three classes: lymphoma, carcinoma, and benign lesion. The method works by splitting the images into patches, classifying each patch using a deep learning model, and taking the average confidence score of each patch. We compared three deep learning-based feature extractor architectures and studied the effects of three image color preprocessing techniques on classification performance. We reached 88.7% sensitivity and 91.3% specificity in differentiating lymphoma on 400x magnification CLAHE-enhanced microscopic images using the InceptionResNetV2 model. We also reached 87.0% three-class classification accuracy using the same model.
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