A humanistic model of corporate social responsibility in e-commerce with high-tech support in the artificial intelligence economy.

This paper aims to develop a humanistic model of corporate social responsibility in e-commerce, relying on high technology in an artificial intelligence economy. The research is based on the experience of the top 30 publicly traded e-commerce companies, the 16 most responsible companies in the retail industry in the USA, and the leading global and Russian e-commerce business structures in 2020-2021. Based on econometric modeling, it is substantiated that the humanization (qualitative criterion) of jobs provides an increase in revenues of e-commerce businesses to a greater extent than an increase in the number (quantitative criterion) of jobs. The high technology of the artificial intelligence economy (AI economy) makes it possible to maximize the contribution of responsible HRM of the e-commerce business in increasing its revenues. For this purpose, a humanistic model of corporate social responsibility in e-commerce based on high technology in the AI economy has been developed. The theoretical significance lies in proving the need to humanize jobs in e-commerce and revealing the essence of this process. The practical significance lies in the fact that the developed humanistic model will increase the profitability and, consequently, the resilience of businesses to future economic crises that arise against the backdrop of the COVID-19 pandemic.

Multiplex Lithographic SERS Aptasensor for Detection of Several Respiratory Viruses in One Pot.

Rapid and reliable techniques for virus identification are required in light of recurring epidemics and pandemics throughout the world. Several techniques have been distributed for testing the flow of patients. Polymerase chain reaction with reverse transcription is a reliable and sensitive, though not rapid, tool. The antibody-based strip is a rapid, though not reliable, and sensitive tool. A set of alternative tools is being developed to meet all the needs of the customer. Surface-enhanced Raman spectroscopy (SERS) provides the possibility of single molecule detection taking several minutes. Here, a multiplex lithographic SERS aptasensor was developed aiming at the detection of several respiratory viruses in one pot within 17 min. The four labeled aptamers were anchored onto the metal surface of four SERS zones; the caught viruses affect the SERS signals of the labels, providing changes in the analytical signals. The sensor was able to decode mixes of SARS-CoV-2 (severe acute respiratory syndrome coronavirus two), influenza A virus, respiratory syncytial virus, and adenovirus within a single experiment through a one-stage recognition process.

Lithographic SERS Aptasensor for Ultrasensitive Detection of SARS-CoV-2 in Biological Fluids.

In this paper, we propose a technology for the rapid and sensitive detection of the whole viral particles of SARS-CoV-2 using double-labeled DNA aptamers as recognition elements together with the SERS method for detecting the optical response. We report on the development of a SERS-aptasensor based on a reproducible lithographic SERS substrate, featuring the combination of high speed, specificity, and ultrasensitive quantitative detection of SARS-CoV-2 virions. The sensor makes it possible to identify SARS-CoV-2 in very low concentrations (the limit of detection was 100 copies/mL), demonstrating a sensitivity level comparable to the existing diagnostic golden standard-the reverse transcription polymerase chain reaction.

Model of the SARS-CoV-2 Virus for Development of a DNA-Modified, Surface-Enhanced Raman Spectroscopy Sensor with a Novel Hybrid Plasmonic Platform in Sandwich Mode.

The recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has posed a great challenge for the development of ultra-fast methods for virus identification based on sensor principles. We created a structure modeling surface and size of the SARS-CoV-2 virus and used it in comparison with the standard antigen SARS-CoV-2-the receptor-binding domain (RBD) of the S-protein of the envelope of the SARS-CoV-2 virus from the Wuhan strain-for the development of detection of coronaviruses using a DNA-modified, surface-enhanced Raman scattering (SERS)-based aptasensor in sandwich mode: a primary aptamer attached to the plasmonic surface-RBD-covered Ag nanoparticle-the Cy3-labeled secondary aptamer. Fabricated novel hybrid plasmonic structures based on "Ag mirror-SiO2-nanostructured Ag" demonstrate sensitivity for the detection of investigated analytes due to the combination of localized surface plasmons in nanostructured silver surface and the gap surface plasmons in a thin dielectric layer of SiO2 between silver layers. A specific SERS signal has been obtained from SERS-active compounds with RBD-specific DNA aptamers that selectively bind to the S protein of synthetic virion (dissociation constants of DNA-aptamer complexes with protein in the range of 10 nM). The purpose of the study is to systematically analyze the combination of components in an aptamer-based sandwich system. A developed virus size simulating silver particles adsorbed on an aptamer-coated sensor provided a signal different from free RBD. The data obtained are consistent with the theory of signal amplification depending on the distance of the active compound from the amplifying surface and the nature of such a compound. The ability to detect the target virus due to specific interaction with such DNA is quantitatively controlled by the degree of the quenching SERS signal from the labeled compound. Developed indicator sandwich-type systems demonstrate high stability. Such a platform does not require special permissions to work with viruses. Therefore, our approach creates the promising basis for fostering the practical application of ultra-fast, amplification-free methods for detecting coronaviruses based on SARS-CoV-2.

A Combination of Membrane Filtration and Raman-Active DNA Ligand Greatly Enhances Sensitivity of SERS-Based Aptasensors for Influenza A Virus.

Biosensors combining the ultrahigh sensitivity of surface-enhanced Raman scattering (SERS) and the specificity of nucleic acid aptamers have recently drawn attention in the detection of respiratory viruses. The most sensitive SERS-based aptasensors allow determining as low as 104 virus particles per mL that is 100-fold lower than any antibody-based lateral flow tests but 10-100-times higher than a routine polymerase chain reaction with reversed transcription (RT-PCR). Sensitivity of RT-PCR has not been achieved in SERS-based aptasensors despite the usage of sophisticated SERS-active substrates. Here, we proposed a novel design of a SERS-based aptasensor with the limit of detection of just 103 particles per ml of the influenza A virus that approaches closely to RT-PCR sensitivity. The sensor utilizes silver nanoparticles with the simplest preparation instead of sophisticated SERS-active surfaces. The analytical signal is provided by a unique Raman-active dye that competes with the virus for the binding to the G-quadruplex core of the aptamer. The aptasensor functions even with aliquots of the biological fluids due to separation of the off-target molecules by pre-filtration through a polymeric membrane. The aptasensor detects influenza viruses in the range of 1·103-5·1010 virus particles per ml.

Glycosylation of Receptor Binding Domain of SARS-CoV-2 S-Protein Influences on Binding to Immobilized DNA Aptamers.

Nucleic acid aptamers specific to S-protein and its receptor binding domain (RBD) of SARS-CoV-2 (severe acute respiratory syndrome-related coronavirus 2) virions are of high interest as potential inhibitors of viral infection and recognizing elements in biosensors. Development of specific therapy and biosensors is complicated by an emergence of new viral strains bearing amino acid substitutions and probable differences in glycosylation sites. Here, we studied affinity of a set of aptamers to two Wuhan-type RBD of S-protein expressed in Chinese hamster ovary cell line and Pichia pastoris that differ in glycosylation patterns. The expression system for the RBD protein has significant effects, both on values of dissociation constants and relative efficacy of the aptamer binding. We propose glycosylation of the RBD as the main force for observed differences. Moreover, affinity of a several aptamers was affected by a site of biotinylation. Thus, the robustness of modified aptamers toward new virus variants should be carefully tested.

SERS-Based Aptasensor for Rapid Quantitative Detection of SARS-CoV-2.

During the COVID-19 pandemic, the development of sensitive and rapid techniques for detection of viruses have become vital. Surface-enhanced Raman scattering (SERS) is an appropriate tool for new techniques due to its high sensitivity. SERS materials modified with short-structured oligonucleotides (DNA aptamers) provide specificity for SERS biosensors. Existing SERS-based aptasensors for rapid virus detection are either inapplicable for quantitative determination or have sophisticated and expensive construction and implementation. In this paper, we provide a SERS-aptasensor based on colloidal solutions which combines rapidity and specificity in quantitative determination of SARS-CoV-2 virus, discriminating it from the other respiratory viruses.