Screening Of Interactions Research Articles

Identification of Immune-Related Gene Signature and Prediction of CeRNA Network in Active Ulcerative Colitis.

BackgroundUlcerative colitis (UC) is an inflammatory disease of the intestinal mucosa, and its incidence is steadily increasing worldwide. Intestinal immune dysfunction has been identified as a central event in UC pathogenesis. However, the underlying mechanisms that regulate dysfunctional immune cells and inflammatory phenotype remain to be fully elucidated.MethodsTranscriptome profiling of intestinal mucosa biopsies were downloaded from the GEO database. Robust Rank Aggregation (RRA) analysis was performed to identify statistically changed genes and differentially expressed genes (DEGs). Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to explore potential biological mechanisms. CIBERSORT was used to evaluate the proportion of 22 immune cells in biopsies. Weighted co-expression network analysis (WGCNA) was used to determine key module-related clinical traits. Protein-Protein Interaction (PPI) network and Cytoscape were performed to explore protein interaction network and screen hub genes. We used a validation cohort and colitis mouse model to validate hub genes. Several online websites were used to predict competing endogenous RNA (ceRNA) network.ResultsRRA integrated analysis revealed 1838 statistically changed genes from four training cohorts (adj. p-value < 0.05). GSEA showed that statistically changed genes were enriched in the innate immune system. CIBERSORT analysis uncovered an increase in activated dendritic cells (DCs) and M1 macrophages. The red module of WGCNA was considered the most critical module related to active UC. Based on the results of the PPI network and Cytoscape analyses, we identified six critical genes and transcription factor NF-κB. RT-PCR revealed that andrographolide (AGP) significantly inhibited the expression of hub genes. Finally, we identified XIST and three miRNAs (miR-9-5p, miR-129-5p, and miR-340-5p) as therapeutic targets.ConclusionsOur integrated analysis identified four hub genes (CXCL1, IL1B, MMP1, and MMP10) regulated by NF-κB. We further revealed that AGP decreased the expression of hub genes by inhibiting NF-κB activation. Lastly, we predicted the involvement of ceRNA network in the regulation of NF-κB expression. Collectively, our results provide valuable information in understanding the molecular mechanisms of active UC. Furthermore, we predict the use of AGP and small RNA combination for the treatment of UC.

Fluorescence-Based Binding Characterization of Small Molecule Ligands Targeting CUG RNA Repeats.

Pathogenic CUG and CCUG RNA repeats have been associated with myotonic dystrophy type 1 and 2 (DM1 and DM2), respectively. Identifying small molecules that can bind these RNA repeats is of great significance to develop potential therapeutics to treat these neurodegenerative diseases. Some studies have shown that aminoglycosides and their derivatives could work as potential lead compounds targeting these RNA repeats. In this work, sisomicin, previously known to bind HIV-1 TAR, is investigated as a possible ligand for CUG RNA repeats. We designed a novel fluorescence-labeled RNA sequence of r(CUG)10 to mimic cellular RNA repeats and improve the detecting sensitivity. The interaction of sisomicin with CUG RNA repeats is characterized by the change of fluorescent signal, which is initially minimized by covalently incorporating the fluorescein into the RNA bases and later increased upon ligand binding. The results show that sisomicin can bind and stabilize the folded RNA structure. We demonstrate that this new fluorescence-based binding characterization assay is consistent with the classic UV Tm technique, indicating its feasibility for high-throughput screening of ligand-RNA binding interactions and wide applications to measure the thermodynamic parameters in addition to binding constants and kinetics when probing such interactions.

Modulating Role of Co-Solutes in Complexation between Bovine Serum Albumin and Sodium Polystyrene Sulfonate.

The action of three types of co-solutes: (i) salts (NaCl, NaBr, NaI), (ii) polymer (polyethylene glycol; PEG-400, PEG-3000, PEG-20000), and (iii) sugars (sucrose, sucralose) on the complexation between bovine serum albumin (BSA) and sodium polystyrene sulfonate (NaPSS) was studied. Three critical pH parameters were extracted from the pH dependence of the solution’s turbidity: corresponding to the formation of the soluble complexes, corresponding to the formation of the insoluble complexes, and corresponding to the charge neutralization of the complexes. In the presence of salts, the formation of soluble and insoluble complexes as well as the charge neutralization of complexes was hindered, which is a consequence of the electrostatic screening of attractive interactions between BSA and NaPSS. Distinct anion-specific trends were observed in which the stabilizing effect of the salt increased in the order: NaCl < NaBr < NaI. The presence of PEG, regardless of its molecular weight, showed no measurable effect on the formation of soluble complexes. PEG-400 and PEG-3000 showed no effect on the formation of insoluble complexes, but PEG-20000 in high concentrations promoted their formation due to the molecular crowding effect. The presence of sugar molecules had little effect on BSA-NaPSS complexation. Sucralose showed a minor stabilizing effect with respect to the onset of complex formation, which was due to its propensity to the protein surface. This was confirmed by the fluorescence quenching assay (Stern-Volmer relationship) and all-atom MD simulations. This study highlights that when evaluating the modulatory effect of co-solutes on protein-polyelectrolyte interactions, (co-solute)-protein interactions and their subsequent impact on protein aggregation must also be considered.

Development of the supply system, control algorithm and architecture of verbal robot

This work is supported by grant from the Ministry of Education and Science of the Republic of Kazakhstan within the framework of the Work №AP08053034 «Development of new methods for modeling and recognition of Kazakh sign language», Institute Information and Computational Technologies CS MES RK. This article reviews the supply system, control algorithm and architecture of verbal robot. The robot is based on publicly available 3D printer. In this research was developed architecture of general programme system of verbal robot, also improved supply system and control algorithm of overall system. Using Jetson Tx1 equipment and a touch screen for interaction with InMoov, an interface was made to control the entire system. The Kinect detector plays a major role in the process of studying this topic. Compared with the existing humanoid robots, the verbal robot is highly automated platform, low cost and fully functional.

Polyelectrolyte Hydrogels as Draw Agents for Desalination of Solutions with Multivalent Ions

We model a process of seawater desalination that employs compression of a weak polyelectrolyte hydrogel as the drawing force for ion transfer. We model seawater as an aqueous solution containing mono- and divalent ions, Na+, Cl–, and Ca2+. We demonstrate that the compression of hydrogel in equilibrium with a bath containing such a solution creates two types of ion flow. The first type is the exchange of divalent Ca2+ by monovalent Na+. The charge density during this process is preserved, so that per one absorbed Ca2+ two Na+ are released. The second type is the desalination itself which leads to the uptake of Na+ and Cl– pairs from the surrounding solution. The first flow predominates when Ca2+ are in excess; however, as their fraction in the solution decreases, desalination flow becomes more significant. We have shown that although the gel is a weak polyelectrolyte, its compression in the presence of divalent ions does not influence its ionization degree. This is caused by a significant screening of electrostatic interactions by divalent ions. When the density of Ca2+ is small, the gel compression may lead to its discharge and to the release of counterions, which shows up in an increase of the solution ionic strength.

Interaction screening via canonical correlation

Interaction screening via canonical correlation

Barcode fusion genetics-protein-fragment complementation assay (BFG-PCA): tools and resources that expand the potential for binary protein interaction discovery.

Barcode fusion genetics (BFG) utilizes deep sequencing to improve the throughput of protein–protein interaction (PPI) screening in pools. BFG has been implemented in Yeast two-hybrid (Y2H) screens (BFG-Y2H). While Y2H requires test protein pairs to localize in the nucleus for reporter reconstruction, dihydrofolate reductase protein-fragment complementation assay (DHFR-PCA) allows proteins to localize in broader subcellular contexts and proves to be largely orthogonal to Y2H. Here, we implemented BFG to DHFR-PCA (BFG-PCA). This plasmid-based system can leverage ORF collections across model organisms to perform comparative analysis, unlike the original DHFR-PCA that requires yeast genomic integration. The scalability and quality of BFG-PCA were demonstrated by screening human and yeast interactions for >11 000 bait-prey pairs. BFG-PCA showed high-sensitivity and high-specificity for capturing known interactions for both species. BFG-Y2H and BFG-PCA capture distinct sets of PPIs, which can partially be explained based on the domain orientation of the reporter tags. BFG-PCA is a high-throughput protein interaction technology to interrogate binary PPIs that exploits clone collections from any species of interest, expanding the scope of PPI assays.

The Kendall interaction filter for variable interaction screening in high dimensional classification problems

Accounting for important interaction effects can improve the prediction of many statistical learning models. Identification of relevant interactions, however, is a challenging issue owing to their ultrahigh-dimensional nature. Interaction screening strategies can alleviate such issues. However, due to heavier tail distribution and complex dependence structure of interaction effects, innovative robust and/or model-free methods for screening interactions are required to better scale analysis of complex and high-throughput data. In this work, we develop a new model-free interaction screening method, termed Kendall Interaction Filter (KIF), for the classification in high-dimensional settings. KIF method suggests a weighted-sum measure, which compares the overall to the within-cluster Kendall's τ of pairs of predictors, to select interactive couples of features. The proposed KIF measure captures relevant interactions for the clusters response-variable, handles continuous, categorical or a mixture of continuous-categorical features, and is invariant under monotonic transformations. The tKIF measure enjoys the sure screening property in the high-dimensional setting under mild conditions, without imposing sub-exponential moment assumptions on the features' distribution. We illustrate the favorable behavior of the proposed methodology compared to the methods in the same category using simulation studies, and we conduct real data analyses to demonstrate its utility.

ScreenGarden: a shinyR application for fast and easy analysis of plate-based high-throughput screens

BackgroundColony growth on solid media is a simple and effective measure for high-throughput genomic experiments such as yeast two-hybrid, synthetic dosage lethality and Synthetic Physical Interaction screens. The development of robotic pinning tools has facilitated the experimental design of these assays, and different imaging software can be used to automatically measure colony sizes on plates. However, comparison to control plates and statistical data analysis is often laborious and pinning issues or plate specific growth effects can lead to the detection of false-positive growth defects.ResultsWe have developed ScreenGarden, a shinyR application, to enable easy, quick and robust data analysis of plate-based high throughput assays. The code allows comparisons of different formats of data and different sized arrays of colonies. A comparison of ScreenGarden with previous analysis tools shows that it performs, at least, equivalently. The software can be run either via a website or offline via the RStudio program; the code is available and can be modified by expert uses to customise the analysis.ConclusionsScreenGarden provides a simple, fast and effective tool to analyse colony growth data from genomic experiments.

Impact of COVID-19 Pandemic on Screen Time: Findings From a Cross-Sectional Observational Study Among College Students From India

In this study, we aimed to assess the impact of the COVID-19 pandemic on the amount and pattern of screen time among college students. The relationship between increased screen time and quality of life (QoL), COVID-related stress, and personality traits were also explored. A cross-sectional online survey-based study was conducted among Indian college students who were recruited by purposive sampling. Details regarding socio-demographics, amount and pattern of screen time usage, change in screen time patterns during the COVID-19 pandemic, and COVID-related stress were collected. In addition, personality traits and QoL were assessed with validated questionnaires. A total of 731 responses (51% female, mean age 20.7 years) were analysed. Of the participants, 93.2% self-reported an increase in daily screen time during COVID-19. The predominant reasons for the increased screen time were educational screen time (89.6%), streaming or watching videos for entertainment (82.8%), use of social media for non-communication purposes (78.1%), communication with friends and/or family members (76.2%), reading or watching news (65.9%), and interactive recreational screen time (44.7%). A small but significant negative correlation between increased screen time and QoL (rs = -0.154, p &lt; .001) was found. Increased screen time due to the use of social media for non-communication purposes was associated with poorer QoL (U = 32947.50; p = .02) and greater COVID stress (U = 32381.50; p = .01). Educational screen time was the most common cause for increased screen time among college students and was not associated with negative effects on QoL. The context and purpose of screen time appears to be important in ascertaining the impact of screen time on QoL.&#x0D;

Renal tumouroids: challenges of manufacturing 3D cultures from patient derived primary cells.

Recent advancements in 3D in vitro culture have allowed for the development of cancer tissue models which accurately recapitulate the tumour microenvironment. Consequently, there has been increased innovation in therapeutic drug screening. While organoid cultures show great potential, they are limited by the time scale of their growth in vitro and the dependence upon commercial matrices, such as Matrigel, which do not allow for manipulations of their composition or mechanical properties. Here, we show a straightforward approach for the isolation and culture of primary human renal carcinoma cells and matched non-affected kidney. This approach does not require any specific selection for cancer cells, and allows for their direct culture in amenable 3D collagen-based matrices, with the preservation of cancer cells as confirmed by NGS sequencing. This method allows for culture of patient-derived cancer cells in 3D microenvironment, which can be used for downstream experimentation such as investigation of cell-matrix interaction or drug screening.

Giant Photoresponse Enhancement in Mixed‐Dimensional Van der Waals Heterostructure through Dielectric Engineering

AbstractThe reduced dielectric screening in the out of plane direction, makes 2D materials sensitive to the surrounding environment, offering a unique platform with greatly tunable optoelectronic properties. Large exciton binding energy in 2D materials limits their photogeneration efficiency. The strong electric field generated at a p–n junction will help in separating these strongly bound electron hole pairs. Here, the present study demonstrates how engineering the surrounding dielectric environment would facilitate a mixed dimensional van der Waals p–n junction to improve the photoresponse to a great extent. A 3D silicon‐2D monolayer MoS2 heterostructure is fabricated as a model system. Nearly three orders of magnitude enhancement in photoresponse is observed by modulating the surrounding dielectric environment. This huge enhancement is attributed to the easy separation of photogenerated carriers due to the screening of Coulomb interaction. The dielectric also screens the impurity potential, reducing the charge carrier scattering. In addition, there is a change in the overall bandgap of the heterostructure producing a lower energy barrier for the charge carriers. The findings lay a general pathway for improving the efficiency of 2D material based photodetectors through dielectric engineering.

Epistasis Detection via the Joint Cumulant

Selecting influential non-linear interactive features from ultrahigh-dimensional data has been an important task in various fields. However, statistical accuracy and computational feasibility are the two biggest concerns when billions of interactive pairs are screened in practice. Many extant feature screening approaches are either focused on only main effects or heavily rely on heredity structure, hence rendering them ineffective in a scenario presenting strong interactive but weak main effects. In this article, we propose a new interaction screening procedure based on joint cumulant (named JCI-SIS). We show that the proposed procedure has strong sure screening consistency and is theoretically sound to support its performance. Finite sample simulation studies designed for both continuous and categorical predictors are performed to demonstrate the versatility and practicability of the JCI-SIS method. We further illustrate the power of JCI-SIS by applying it to screen 27,554,602,881 interaction pairs involving 234,754 single-nucleotide polymorphisms for 4098 subjects collected from polycystic ovary syndrome patients and healthy controls.

Ligand Interactions and Nanoparticle Shapes Guide the Pathways toward Interfacial Self-Assembly.

Non-equilibrium molecular dynamics simulations are used to probe the driving forces behind the formation of highly ordered, epitaxially connected superlattices of polyhedral-shaped nanoparticles (NPs) at fluid-fluid interfaces. By explicitly modeling coarse-grained ligands that cap the NP surface, it is shown that differences in NP shapes and time-dependent facet-specific ligand densities give rise to drastically different transformation mechanisms. Our results indicate that the extent of screening of the inter-particle interactions by the surrounding solvation environment has a significant impact on reversibility and ultimately the coherence of the final two-dimensional superlattice obtained. For the particle shapes examined, a hexagonal pre-assembly and a square superlattice final assembly (upon preferential ligand desorption from {100} facets) were prevalent; however, cuboctahedral NPs formed intermediate epitaxially bonded branched clusters, which eventually grew and rearranged into a square lattice; in contrast, truncated octahedral NPs exhibited an abrupt rhombic-to-square transition driven by the clustering of their numerous {111}-ligands that favored the stacking of linear NP rods. To track the incipient order in the system, we also outline a set of novel order parameters that measure the local orientation alignment between nearest-neighbor pairs. The simulation protocols advanced in this work could pave the way forward for exploration of the vast phase space associated with the interfacial self-assembly of NPs.

Prognostic Value and Immune-Infiltration Pattern of KIF4A in Patients with Endometrial Carcinoma.

Background With the development of sequencing technology, an increasing number of biomarkers has been identified in endometrial carcinoma (EC). However, there have been few comprehensive analyses of the KIF4A gene in patients with EC. Methods Based on raw data in public databases, the KIF4A gene and protein expression in EC were validated. Logistic regression analysis was conducted to analyze the correlations between clinical characteristics and the KIF4A expression. Kaplan-Meier analysis was used to explore the difference in survival in clinical subgroups. Meanwhile, we used meta-analysis in multiple datasets to investigate the prognostic value of KIF4A. In addition, Cox regression analysis was used to confirm the independent prognostic value of KIF4A, and we constructed a nomogram based on KIF4A expression. Subsequently, we used ESTIMATE and ssGSEA algorithms to excavate the correlation between KIF4A, tumour-infiltrating immune cells, and related gene markers of immune cells. Moreover, the potential biological functions of KIF4A were investigated by gene function annotation. Finally, we identified the hub genes interacting with KIF4A by constructing a protein-protein interaction (PPI) network and screening differential genes (DEGs). Results In the pan-cancer analysis, KIF4A was upregulated in most tumors (21/33). Similarly, the overexpression of KIF4A in EC patients was confirmed in the TCGA cohort, the GEO cohort, and immunohistochemistry. In addition, upregulated KIF4A is associated with age, survival status, grade, FIGO stage, histological type, tumour invasion, and TCGA molecular subtypes (p < 0.05). KIF4A overexpression was correlated with the grade, histological type, and pathological stage according to logistic regression analysis (p < 0.05). Meanwhile, survival analysis and meta-analysis revealed that KIF4A was associated with a poor prognosis and acted as an independent prognostic marker in EC patients (p < 0.05). KIF4A is associated to immune response and may have a function in controlling immune cell infiltration in EC (20/24, p < 0.05). This is noteworthy given that gene enrichment analysis suggested KIF4A may be involved in the neuroactive ligand-receptor interaction pathway, etc. Finally, we identified transcription factors which have a potential interaction with KIF4A. Conclusion We provided robust evidences that KIF4A is an indicator of poor prognosis and a potential target for immunotherapy in patients with EC.

Promotion of Innovative Microchip in the Market of Medical Services: Marketing Aspects

In current conditions, people can quickly move between regions, countries, and continents. This freedom of movement makes it easier to share knowledge and strengthen potential. However, the period of the COVID-19 pandemic showed that diseases move too. It becomes more challenging to detect and control conditions in time. Accordingly, there is a need to develop a concept of an innovative product. This innovative product must facilitate the timely detection, treatment, or prevention of diseases caused by pathogenic components, poisons, or toxins that may endanger human life and health during travel. The article aims to develop an innovation in the field of medicine and describe the marketing aspects of its promotion. The study showed that innovation is becoming an essential part of medicine. Artificial intelligence technologies and nanosized (microscopically tiny) materials and objects develop rapidly in the medical sphere. Following specific trends in treatment, we have formed the concept of an innovative product. The essence of the idea is as follows: a microchip «InBlood» can detect specific pathogens and toxins and create opportunities for timely medical care. At the initial stage, it was proposed to produce two versions of the innovative product: 1) «InBlood Tourist» the primary target audience of which are people who travel; 2) «InBlood Life» the target audience of which are people who have health problems and monitor the state of their performance or people for whom disease prevention is important. The analysis of indirect competitors helped to determine the price of innovative microchips. A system of discounts has also been developed. In addition, it is advisable to use a multi-channel distribution system to sell innovative microchips. It means using direct sales through online stores and sales departments of the manufacturer and sales through intermediaries. Thus, the principal intermediaries in the sale of chips «InBlood Tourist» will be travel agencies and «InBlood Life» – medical centers. For the innovative microchip promotion on the market, we proposed the following plan of communication activities: (1) participation in international electronics exhibitions; (2) collaborations with techno-bloggers on Youtube, Instagram, Tiktok; (3) personal presentation of goods to future partner companies (medical centers, travel companies, etc.); (4) launch of review articles on technological and tourist resources and stories in the media; (5) mailing to consumers, launching contextual advertising, and targeting search networks; (6) placement of outdoor advertising in the form of billboards and interactive screens. Moreover, a brand with a complete visual identity will be formed. Thus, the practical significance of the article consists in the strategy formation for innovative microchip presentation and dissemination among consumers in the field of medicine.

Covid-19: Transformation of Edtech in India from Real to Virtual: An Analysis of Issues and Challenges by University Students in Tamilnadu

Edtech refers to innovative technical implementations in the classroom teaching management. In-classroom tablets, interactive outcrop screens and whiteboards, online fulfilled delivery, and MOOCs are all examples of EdTech. However, the existing crisis of the COVID-19 pandemic forced the intact planet to confide on it for learning. To estimate the university student’s perceptions, evaluate their experiences, recognize their barriers, challenges of e-learning during the COVID-19 pandemic, and examine factors influencing the getting and use of e-learning as a tool teaching within higher education. Data was collected using a Google form questionnaire among Students of University in Chennai. Researcher prepared the Percentage Analysis, Mean Analysis, Chi-square Analysis, This study highlights the challenges and factors influencing the acceptance, and use of e-learning as a tool for teaching within higher education.

Anchor Retouching via Model Interaction for Robust Object Detection in Aerial Images

Object detection has made tremendous strides in computer vision. Small object detection with appearance degradation is a prominent challenge, especially for aerial observations. To collect sufficient positive/negative samples for heuristic training, most object detectors preset region anchors in order to calculate intersection-over-union (IoU) against the ground-truth data. In this case, small objects are frequently abandoned or mislabeled. In this article, we present an effective dynamic enhancement anchor network (DEA-Net) to construct a novel training sample generator. Different from the other state-of-the-art (SOTA) techniques, the proposed network leverages a sample discriminator to realize interactive sample screening between an anchor-based unit and an anchor-free unit to generate eligible samples. Besides, multi-task joint training with a conservative anchor-based inference scheme enhances the performance of the proposed model while reducing computational complexity. The proposed scheme supports both oriented and horizontal object detection tasks. Extensive experiments on two challenging aerial benchmarks (i.e., Dataset of Object deTection in Aerial images (DOTA) and HRSC2016) indicate that our method achieves SOTA performance in accuracy with moderate inference speed and computational overhead for training. On DOTA, our DEA-Net which integrated with the baseline of RoI-transformer surpasses the advanced method by 0.40&#x0025; mean-average-precision (mAP) for oriented object detection with a weaker backbone network (ResNet-101 vs. ResNet-152) and 3.08&#x0025; mAP for horizontal object detection with the same backbone. Besides, our DEA-Net which integrated with the baseline of ReDet achieves the SOTA performance by 80.37&#x0025;. On HRSC2016, it surpasses the previous best model by 1.1&#x0025; using only three horizontal anchors. The source code and the training set are made publicly available at <uri>https://github.com/QxGeng/DEA-Net</uri>.

High-Throughput Microenvironment Microarray (MEMA) High-Resolution Imaging.

The interaction between cells and their surrounding microenvironment has a crucial role in determining cell fate. In many pathological conditions, the microenvironment drives disease progression as well as therapeutic resistance. A number of challenges arise for researchers examining these cell-microenvironment interactions: (1) Tissue microenvironments are combinatorial and dynamic systems, and in pathological situations like cancer, microenvironments become infamously chaotic and highly heterogeneous. (2) Cells exhibit heterogeneous phenotypes, and even rare cell subpopulations can have a substantial role in tissue homeostasis and disease progression. This chapter discusses technical aspects relevant to dissecting cell-microenvironment interaction using the Microenvironment Microarray (MEMA) platform, which is a cell-based functional high-throughput screening of interactions between cells and combinatorial microenvironments at the single-cell level. MEMA provides insights into how cell phenotype and function is elicited by microenvironmental components. In this chapter, we describe automating a high-throughput and high-resolution imaging pipeline for single-cell-resolution analysis.

Development of a Biosensor Based on Angiotensin-Converting Enzyme II for Severe Acute Respiratory Syndrome Coronavirus 2 Detection in Human Saliva.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the novel coronavirus responsible for COVID-19. Infection in humans requires angiotensin-converting enzyme II (hACE2) as the point of entry for SARS-CoV-2. PCR testing is generally definitive but expensive, although it is highly sensitive and accurate. Biosensor-based monitoring could be a low-cost, accurate, and non-invasive approach to improve testing capacity. We develop a capacitive hACE2 biosensor for intact SARS-CoV-2 detection in saliva. Laser-induced graphene (LIG) electrodes were modified with platinum nanoparticles. The quality control of LIG electrodes was performed using cyclic voltammetry. Truncated hACE2 was used as a biorecognition element and attached to the electrode surface by streptavidin–biotin coupling. Biolayer interferometry was used for qualitative interaction screening of hACE2 with UV-attenuated virions. Electrochemical impedance spectroscopy (EIS) was used for signal transduction. Truncated hACE2 binds wild-type SARS-CoV-2 and its variants with greater avidity than human coronavirus (common cold virus). The limit of detection (LoD) is estimated to be 2,960 copies/ml. The detection process usually takes less than 30 min. The strength of these features makes the hACE2 biosensor a potentially low-cost approach for screening SARS-CoV-2 in non-clinical settings with high demand for rapid testing (for example, schools and airports).