Computational design and experimental analysis of a novel visor for COVID-19 patients receiving high-flow nasal oxygen therapy

The Covid-19 global pandemic has reshaped the requirements of healthcare sectors worldwide. Following the exposure risks associated with Covid-19, this paper aims to design, optimise, and validate a wearable medical device that reduces the risk of transmission of contagious droplets from infected patients in a hospital setting. This study specifically focuses on those receiving high-flow nasal oxygen therapy. The design process consisted of optimising the geometry of the visor to ensure that the maximum possible percentage of harmful droplets exhaled by the patient can be successfully captured by a vacuum tube attached to the visor. This has been completed by deriving a number of concept designs and assessing their effectiveness, based on numerical analysis, computational fluid dynamics (CFD) simulations and experimental testing. The CFD results are validated using various experimental methods such as Schlieren imaging, particle measurement testing and laser sheet visualisation. Droplet capturing efficiency of the visor was measured through CFD and validated through experimental particle measurement testing. The results presented a 5% deviation between CFD and experimental results. Also, the modifications based on the validated CFD results improved the visor effectiveness by 47% and 38% for breathing and coughing events, respectively © 2022 The Author(s)

Unreachable The physical impossibility of digital displays

"Unreachable" is an artwork that explores the feelings caused by the absence of human closeness and social gathering, and the forced distancing imposed by the spread of the highly contagious virus COVID-19. Digital technologies allowed the continuity of some activities adapted to this new reality. Nevertheless, although we can see and hear through them, they do not fulfill the human need for touch nor replace the sensations of being physically close to other people and of live cultural and leisure moments. Through the display of images and videos that avoid the participants when they cross the minimum safety distance, this artwork addresses the feelings of the impossibility of physically reaching something important and meaningful through digital devices, even though these may simulate a sense of closeness. © 2021 Copyright held by the owner/author(s).

Nucleic acid delivery of immune-focused SARS-CoV-2 nanoparticles drives rapid and potent immunogenicity capable of single-dose protection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines may target epitopes that reduce durability or increase the potential for escape from vaccine-induced immunity. Using synthetic vaccinology, we have developed rationally immune-focused SARS-CoV-2 Spike-based vaccines. Glycans can be employed to alter antibody responses to infection and vaccines. Utilizing computational modeling and in vitro screening, we have incorporated glycans into the receptor-binding domain (RBD) and assessed antigenic profiles. We demonstrate that glycan-coated RBD immunogens elicit stronger neutralizing antibodies and have engineered seven multivalent configurations. Advanced DNA delivery of engineered nanoparticle vaccines rapidly elicits potent neutralizing antibodies in guinea pigs, hamsters, and multiple mouse models, including human ACE2 and human antibody repertoire transgenics. RBD nanoparticles induce high levels of cross-neutralizing antibodies against variants of concern with durable titers beyond 6 months. Single, low-dose immunization protects against a lethal SARS-CoV-2 challenge. Single-dose coronavirus vaccines via DNA-launched nanoparticles provide a platform for rapid clinical translation of potent and durable coronavirus vaccines.

Engineered ACE2 receptor traps potently neutralize SARS-CoV-2.

An essential mechanism for severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection begins with the viral spike protein binding to the human receptor protein angiotensin-converting enzyme II (ACE2). Here, we describe a stepwise engineering approach to generate a set of affinity optimized, enzymatically inactivated ACE2 variants that potently block SARS-CoV-2 infection of cells. These optimized receptor traps tightly bind the receptor binding domain (RBD) of the viral spike protein and prevent entry into host cells. We first computationally designed the ACE2-RBD interface using a two-stage flexible protein backbone design process that improved affinity for the RBD by up to 12-fold. These designed receptor variants were affinity matured an additional 14-fold by random mutagenesis and selection using yeast surface display. The highest-affinity variant contained seven amino acid changes and bound to the RBD 170-fold more tightly than wild-type ACE2. With the addition of the natural ACE2 collectrin domain and fusion to a human immunoglobulin crystallizable fragment (Fc) domain for increased stabilization and avidity, the most optimal ACE2 receptor traps neutralized SARS-CoV-2-pseudotyped lentivirus and authentic SARS-CoV-2 virus with half-maximal inhibitory concentrations (IC50s) in the 10- to 100-ng/mL range. Engineered ACE2 receptor traps offer a promising route to fighting infections by SARS-CoV-2 and other ACE2-using coronaviruses, with the key advantage that viral resistance would also likely impair viral entry. Moreover, such traps can be predesigned for viruses with known entry receptors for faster therapeutic response without the need for neutralizing antibodies isolated from convalescent patients.

Fuzzy logic programming and adaptable design of medical products for the COVID-19 anti-epidemic normalization.

BACKGROUND: The COVID-19 prevention and control constantly affects lives worldwide. In this paper, household medical products were analyzed using fuzzy logic. Considering the household anti-epidemic status, economic and environmental benefits, the adaptable design method of anti-epidemic products in the vestibule was proposed. The measure of adaptable design method still have shortcomings. Therefore, an improved method that is based on fuzzy logic programming is required. METHOD: Firstly, common medical product types used in vestibules and household anti-epidemic products were identified and summarized into product sets. Then matching degree matrix was obtained by functional configuration decomposition and matching calculations. Secondly, experts were invited to evaluate the paired comparative probability matrices and linguistic variables, and the evaluation data were converted by trapezoidal membership functions, fuzzy numbers and the defuzzification method to obtain the usage probability values (PR) for product functions. Finally, the matching degree value (P) and the product function (PF) were calculated by adaptability measure formula, and product function, the adaptability factor and the adaptability (A) were obtained. RESULTS AND DISCUSSION: Our results show that the degree of adaptability of each product function in the product set from PF1 to PF10can be evaluated. Based on the principles of sorting of values from high to low, the top five PF (n = 10) for P value is PF10, PF5, PF6, PF8 and PF1; The top five PF for P value is PF2, PF1, PF3, PF7 and PF8; The top five PF for A value is PF2(0.242), PF1(0.232), PF5(0.225), PF8(0.222) and PF3(0.221). These values allow us to summarize and draw visual charts according to the above data sorting mode. The higher the value of the product function, the more it can be prioritized for design development with functional cost savings, simplification or clustering. CONCLUSION: This study proposes an adaptable design method based on fuzzy logic programming. The data results in this study can guide the development and programming of the vestibule anti-epidemic products. The higher adaptability value of a product function indicates that it is more capable of being simplified, clustered, and adapting to changes in the product set.