Vaccine supply chain coordination using blockchain and artificial intelligence technologies.

Currently, the global spread of COVID-19 is taking a heavy toll on the lives of the global population. There is an urgent need to improve and strengthen the coordination of vaccine supply chains in response to this severe pandemic. In this study, we consider a vaccine supply chain based on a combination of artificial intelligence and blockchain technologies and model the supply chain as a two-player dynamic game with inventory level as the dynamic equation of the system. The study focuses on the applicability and effectiveness of the two technologies in the vaccine supply chain and provides management insights. The impact of the application of the technologies on environmental performance is also considered in the model. We also examine factors such as the number of people vaccinated, positive and side effects of vaccines, vaccine decay rate, revenue-sharing/cost-sharing ratio, and commission ratio. The results are as follows: the correlation between the difficulty in obtaining certified vaccines and the profit of a vaccine manufacturer is not monotonous; the vaccine manufacturer is more sensitive to changes in the vaccine attenuation rate. The study's major conclusions are as follows: First, the vaccine supply chain should estimate the level of consumers' difficulty in obtaining a certified vaccine source and the magnitude of the production planning and demand forecasting error terms before adopting the two technologies. Second, the application of artificial intelligence (AI) technology is meaningful in the vaccine supply chain when the error terms satisfy a particular interval condition.

Vaccine supply chain coordination using blockchain and artificial intelligence technologies

Currently, the global spread of COVID-19 is taking a heavy toll on the lives of the global population. There is an urgent need to improve and strengthen the coordination of vaccine supply chains in response to this severe pandemic. In this study, we consider a closed-loop vaccine supply chain based on a combination of artificial intelligence and blockchain technologies and model the supply chain as a two-player dynamic game with inventory level as the dynamic equation of the system. The study focuses on the applicability and effectiveness of the two technologies in the vaccine supply chain and provides management insights. The impact of the application of the technologies on environmental performance is also considered in the model. We also examine factors such as the number of people vaccinated, positive and side effects of vaccines, vaccine decay rate, revenue-sharing/cost-sharing ratio, and commission ratio. The results are as follows: the correlation between the difficulty in obtaining certified vaccines and the profit of a vaccine manufacturer is not monotonous;the vaccine manufacturer is more sensitive to changes in the vaccine attenuation rate. The study’s major conclusions are as follows: First, the vaccine supply chain should estimate the level of consumers’ difficulty in obtaining a certified vaccine source and the magnitude of the production planning and demand forecasting error terms before adopting the two technologies. Second, the application of artificial intelligence (AI) technology is meaningful in the vaccine supply chain when the error terms satisfy a particular interval condition.

Human ACE2 Peptide-Attached Plasmonic-Magnetic Heterostructure for Magnetic Separation, Surface Enhanced Raman Spectroscopy Identification, and Inhibition of Different Variants of SARS-CoV-2 Infections.

The emergence of Alpha, Beta, Gamma, Delta, and Omicron variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for several million deaths up to now. Because of the huge amount of vaccine escape mutations in the spike (S) protein for different variants, the design of material for combating SARS-CoV-2 is very important for our society. Herein, we report on the design of a human angiotensin converting enzyme 2 (ACE2) peptide-conjugated plasmonic-magnetic heterostructure, which has the capability for magnetic separation, identification via surface enhanced Raman spectroscopy (SERS), and inhibition of different variant SARS-CoV-2 infections. In this work, plasmonic-magnetic heterostructures were developed using the initial synthesis of polyethylenimine (PEI)-coated Fe3O4-based magnetic nanoparticles, and then gold nanoparticles (GNPs) were grown onto the surface of the magnetic nanoparticles. Experimental binding data between ACE2-conjugated plasmonic-magnetic heterostructures and spike-receptor-binding domain (RBD) show that the Omicron variant has maximum binding ability, and it follows Alpha < Beta < Gamma < Delta < Omicron. Our finding shows that, due to the high magnetic moment (specific magnetization 40 emu/g), bioconjugated heterostructures are capable of effective magnetic separation of pseudotyped SARS-CoV-2 bearing the Delta variant spike from an infected artificial nasal mucus fluid sample using a simple bar magnet. Experimental data show that due to the formation of huge "hot spots" in the presence of SARS-CoV-2, Raman intensity for the 4-aminothiolphenol (4-ATP) Raman reporter was enhanced sharply, which has been used for the identification of separated virus. Theoretical calculations using finite-difference time-domain (FDTD) simulation indicate that, due to the "hot spots" formation, a six orders of magnitude Raman enhancement can be observed. A concentration-dependent inhibition efficiency investigation using a HEK293T-human cell line indicates that ACE2 peptide-conjugated plasmonic-magnetic heterostructures have the capability of complete inhibition of entry of different variants and original SARS-CoV-2 pseudovirions into host cells.

The Neutrophil-to-Lymphocyte Ratio is Associated with the Requirement and the Duration of Invasive Mechanical Ventilation in Acute Respiratory Distress Syndrome Patients: A Retrospective Study.

Background: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality and most ARDS patients require ventilatory support. Applying appropriate ventilation strategies based on patients' individual situations has a direct impact upon patients' outcome. The neutrophil-to-lymphocyte ratio (NLR) has been shown to predict the early requirement of invasive mechanical ventilation (IMV) in patients with coronavirus disease 2019 (COVID-19). Our study aimed to investigate the relationship between baseline NLR and IMV in ARDS. Methods: A retrospective study was performed on patients who were diagnosed with ARDS using the Berlin definition and admitted to the First Affiliated Hospital of Soochow University from 2017 to 2022. Clinical data within 24 h after the ARDS diagnosis were collected from the medical record system. Based on the ventilation strategies during hospitalization, patients were divided into three groups and their clinical characteristics were compared. Furthermore, logistic regression analysis was used to screen the independent risk factors for IMV. STROBE checklist was used for this manuscript. Results: 520 ARDS patients were included and the median NLR value in IMV group was significantly higher than that of other groups (P < 0.001). NLR was significantly associated with the requirement of IMV in ARDS patients (OR, 1.042; 95% CI, 1.025-1.060; P < 0.001), other independent risk factors included PaO2/FiO2, Hb, lactate, and use of vasoactive drugs (all P < 0.05). Moreover, we found that the duration of IMV was longer in patients with high NLR (8[IQR, 3-13], 10[IQR, 6-16], respectively, P=0.025). Conclusions: Our results revealed that high baseline NLR level was significantly correlated with an increased risk of IMV in patients with ARDS. Furthermore, higher NLR was associated with prolonged duration of IMV in patients with ARDS.

Green Transformation of Anti-Epidemic Supplies in the Post-Pandemic Era: An Evolutionary Approach.

Post-pandemic, the use of medical supplies, such as masks, for epidemic prevention remains high. The explosive growth of medical waste during the COVID-19 pandemic has caused significant environmental problems. To alleviate this, environment-friendly epidemic prevention measures should be developed, used, and promoted. However, contradictions exist between governments, production enterprises, and medical institutions regarding the green transformation of anti-epidemic supplies. Consequently, this study aimed to investigate how to effectively guide the green transformation. Concerning masks, a tripartite evolutionary game model, consisting of governments, mask enterprises, and medical institutions, was established for the supervision of mask production and use, boundary conditions of evolutionary stabilization strategies and government regulations were analyzed, and a dynamic system model was used for the simulation analysis. This analysis revealed that the only tripartite evolutionary stability strategy is for governments to deregulate mask production, enterprises to increase eco-friendly mask production, and medical institutions to use these masks. From the comprehensive analysis, a few important findings are obtained. First, government regulation can promote the green transformation process of anti-epidemic supplies. Government should realize the green transformation of anti-epidemic supplies immediately in order to avoid severe reputation damage. Second, external parameter changes can significantly impact the strategy selection process of all players. Interestingly, it is further found that the cost benefit for using environmentally friendly masks has a great influence on whether green transformation can be achieved. Consequently, the government should establish a favorable marketplace for, and promote the development of, inexpensive, high-quality, and effective environmentally friendly masks in order to achieve the ultimate goal of green transformation of anti-epidemic supplies in the post-pandemic era.

Blocking SARS-CoV-2 Delta Variant (B.1.617.2) Spike Protein Receptor-Binding Domain Binding with the ACE2 Receptor of the Host Cell and Inhibiting Virus Infections Using Human Host Defense Peptide-Conjugated Graphene Quantum Dots.

The emergence of double mutation delta (B.1.617.2) variants has dropped vaccine effectiveness against SARS-CoV-2 infection. Although COVID-19 is responsible for more than 5.4 M deaths till now, more than 40% of infected individuals are asymptomatic carriers as the immune system of the human body can control the SARS-CoV-2 infection. Herein, we report for the first time that human host defense neutrophil α-defensin HNP1 and human cathelicidin LL-37 peptide-conjugated graphene quantum dots (GQDs) have the capability to prevent the delta variant virus entry into the host cells via blocking SARS-CoV-2 delta variant (B.1.617.2) spike protein receptor-binding domain (RBD) binding with host cells' angiotensin converting enzyme 2 (ACE2). Experimental data shows that due to the binding between the delta variant spike protein RBD and bioconjugate GQDs, in the presence of the delta variant spike protein, the fluorescence signal from GQDs quenched abruptly. Experimental quenching data shows a nonlinear Stern-Volmer quenching profile, which indicates multiple binding sites. Using the modified Hill equation, we have determined n = 2.6 and the effective binding affinity 9 nM, which is comparable with the ACE2-spike protein binding affinity (8 nM). Using the alpha, beta, and gamma variant spike-RBD, experimental data shows that the binding affinity for the delta B.1.617.2 variant is higher than those for the other variants. Further investigation using the HEK293T-human ACE2 cell line indicates that peptide-conjugated GQDs have the capability for completely inhibiting the entry of delta variant SARS-CoV-2 pseudovirions into host cells via blocking the ACE2-spike protein binding. Experimental data shows that the inhibition efficiency for LL-37 peptide- and HNP1 peptide-attached GQDs are much higher than that of only one type of peptide-attached GQDs.

Pandemic Deployment of a Smarthealth Technology to Improve Stress in Dementia Family Caregivers

Caregiving stress from repetitive and heavy caregiving workloads can trigger poor emotional health, such as stress, anxiety, and depression, leading to higher caregiver mortality rates. Interest in technology-based interventions for this population has increased among researchers due to availability, acceptability, and flexibility compared to in-person services, especially now, during an unprecedented pandemic. Our study focuses on in-home SmartHealth technologies for caregivers of persons with Alzheimer’s Disease and related dementias, delivered using Ecological Momentary Assessment and a novel acoustic monitoring, mood recognition, and self-learning recommendation system. The system provides mindfulness-based stress management in response to interpersonal conflict in real-time. We will report challenges and solutions of creating and deploying a SmartHealth system for older adults in their home during the COVID-19 pandemic. Potential effects of this system on caregivers' emotional health are also examined. Findings suggest SmartHealth technologies may assist caregiving populations adapt and thrive in a new, more isolated normal.

The rapid diagnosis and effective inhibition of coronavirus using spike antibody attached gold nanoparticles.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of the coronavirus disease that began in 2019 (COVID-19), has been responsible for 1.4 million deaths worldwide as of 13 November 2020. Because at the time of writing no vaccine is yet available, a rapid diagnostic assay is very urgently needed. Herein, we present the development of anti-spike antibody attached gold nanoparticles for the rapid diagnosis of specific COVID-19 viral antigen or virus via a simple colorimetric change observation within a 5 minute time period. For rapid and highly sensitive identification, surface enhanced Raman spectroscopy (SERS) was employed using 4-aminothiophenol as a reporter molecule, which is attached to the gold nanoparticle via an Au-S bond. In the presence of COVID-19 antigen or virus particles, owing to the antigen-antibody interaction, the gold nanoparticles undergo aggregation, changing color from pink to blue, which allows for the determination of the presence of antigen or virus very rapidly by the naked eye, even at concentrations of 1 nanogram (ng) per mL for COVID-19 antigen and 1000 virus particles per mL for SARS-CoV-2 spike protein pseudotyped baculovirus. Importantly, the aggregated gold nanoparticles form "hot spots" to provide very strong SERS signal enhancement from anti-spike antibody and 4-aminothiophenol attached gold nanoparticles via light-matter interactions. Finite-difference time-domain (FDTD) simulation data indicate a 4-orders-of-magnitude Raman enhancement in "hot spot" positions when gold nanoparticles form aggregates. Using a portable Raman analyzer, our reported data demonstrate that our antibody and 4-aminothiophenol attached gold nanoparticle-based SERS probe has the capability to detect COVID-19 antigen even at a concentration of 4 picograms (pg) per mL and virus at a concentration of 18 virus particles per mL within a 5 minute time period. Using HEK293T cells, which express angiotensin-converting enzyme 2 (ACE2), by which SARS-CoV-2 enters human cells, we show that anti-spike antibody attached gold nanoparticles have the capability to inhibit infection by the virus. Our reported data show that antibody attached gold nanoparticles bind to SARS-CoV-2 spike protein, thereby inhibiting the virus from binding to cell receptors, which stops virus infection and spread. It also has the capability to destroy the lipid membrane of the virus.

Aptamer Conjugated Gold Nanostar-Based Distance-Dependent Nanoparticle Surface Energy Transfer Spectroscopy for Ultrasensitive Detection and Inactivation of Corona Virus.

The ongoing outbreak of the coronavirus infection has killed more than 2 million people. Herein, we demonstrate that Rhodamine 6G (Rh-6G) dye conjugated DNA aptamer-attached gold nanostar (GNS)-based distance-dependent nanoparticle surface energy transfer (NSET) spectroscopy has the capability of rapid diagnosis of specific SARS-CoV-2 spike recombinant antigen or SARS-CoV-2 spike protein pseudotyped baculovirus within 10 min. Because Rh-6G-attached single-stand DNA aptamer wrapped the GNS, 99% dye fluorescence was quenched because of the NSET process. In the presence of spike antigen or virus, the fluorescence signal persists because of the aptamer-spike protein binding. Specifically, the limit of detection for the NSET assay has been determined to be 130 fg/mL for antigen and 8 particles/mL for virus. Finally, we have demonstrated that DNA aptamer-attached GNSs can stop virus infection by blocking the angiotensin-converting enzyme 2 (ACE2) receptor binding capability and destroying the lipid membrane of the virus.