Nanosponges: As a Dynamic Drug Delivery Approach for Targeted Delivery

Recent advancements in nanotechnology have resulted in improved medicine delivery to the target site. Nanosponges are three-dimensional drug delivery systems that are nanoscale in size and created by cross-linking polymers. The introduction of Nanosponges has been a significant step toward overcoming issues such as drug toxicity, low bioavailability, and predictable medication release. Using a new way of nanotechnology, nanosponges, which are porous with small sponges (below one microm) flowing throughout the body, have demonstrated excellent results in delivering drugs. As a result, they reach the target place, attach to the skin's surface, and slowly release the medicine. Nanosponges can be used to encapsulate a wide range of medicines, including both hydrophilic and lipophilic pharmaceuticals. The medication delivery method using nanosponges is one of the most promising fields in pharmacy. It can be used as a biocatalyst carrier for vaccines, antibodies, enzymes, and proteins to be released. The existing study enlightens on the preparation method, evaluation, and prospective application in a medication delivery system and also focuses on patents filed in the field of nanosponges.Copyright © 2023 The Authors.

Optimization and Characterization of Quercetin Vitamin C Nano-Phytosome Formulation

Objective: To design an optimal formulation for quercetin and vitamin C nano-phytosome. Method(s): Nano-phytosomes are prepared by the thin layer hydration technique using a 2-level-5-factor design experimental. A total of 32 experimental formulas were used for data analysis. The ratio of quercetin: soy lecithin (X1), the ratio of quercetin: cholesterol (X2), stirring speed (X3), stirring temperature (X4), and stirring time (X5) were used as independent factors, while globule size as a dependent factor. Data analysis was carried out by Design Expert12 application. Characterization of the optimal formula included physicochemical evaluation, globule size analysis, zeta potential, polydispersity index, entrapment efficiency, Transition Electron Microscopy (TEM) analysis, and FTIR analysis. Result(s): The optimal formula consisted of quercetin: vitamin C: lecithin: cholesterol ratio of 1: 1: 1.046: 0.105 mol;stirring speed 763.986 rpm;stirring time of 59 min, at temperature 51.73 degreeC which produced 59.26 nm average globule size, PDI value 0.66;zeta potential value-35.93+/-0.95 mV and average SPAN value 0.61. This formulation showed entrapment efficiency of quercetin 91.69+/-0.18 % and vitamin C 90.82+/-0.13 %. The TEM and FITR analysis showed the morphological of the globules and interactions between the drugs, soy lecithin, and cholesterol to form nano-phytosomes. Conclusion(s): The conditions to obtain the optimal formula for quercetin vitamin C nano-phytosome consisted of quercetin: vitamin C: lecithin: cholesterol ratio of 1: 1: 1.046: 0.105 mol;stirring speed 763.986 rpm;stirring time of 59 min, and at temperature 51.73 degreeC.Copyright © 2023 The Authors.

Allergic reactions of COVID-19 vaccine based on mRNA-LNP and its pharmacokinetics in vivo.

Vaccination has been proved to be the most effective strategy to prevent the Corona Virus Disease 2019 (COVID-19). The mRNA vaccine based on nano drug delivery system (NDDS) - lipid nanoparticles (LNP) has been widely used because of its high effectiveness and safety. Although there have been reports of severe allergic reactions caused by mRNA-LNP vaccines, the mechanism and components of anaphylaxis have not been completely clarified yet. This review focuses on two mRNA-LNP vaccines, BNT162b2 and mRNA-1273. After summarizing the structural characteristics, potential allergens, possible allergic reaction mechanism, and pharmacokinetics of mRNA and LNP in vivo, this article then reviews the evaluation methods for patients with allergic history, as well as the regulations of different countries and regions on people who should not be vaccinated, in order to promote more safe injection of vaccines. LNP has become a recognized highly customizable nucleic acid delivery vector, which not only shows its value in mRNA vaccines, but also has great potential in treating rare diseases, cancers and other broad fields in the future. At the moment when mRNA-LNP vaccines open a new era of nano medicine, it is expected to provide some inspiration for safety research in the process of research, development and evaluation of more nano delivery drugs, and promote more nano drugs successfully to market.Copyright © 2023, Chinese Pharmaceutical Association. All rights reserved.

Exosomes/EVs: BIOXOME: A NATURAL LIPOSOME MIMETIC AS DRUG DELIVERY SYSTEM

Background & Aim: Liposomes are spherical-shaped vesicles composed of one or more lipid bilayers. The ability of liposomes to encapsulate hydro- or lipophilic drugs allowed these vesicles to become a useful drug delivery system. Natural cell membranes, such as Bioxome, have newly emerged as new source of materials for molecular delivery systems. Bioxome are biocompatible and GMP-compliant liposome-like membrane that can be produced from more than 200 cell types. Bioxome self-assemble, with in-process self-loading capacity and can be loaded with a variety of therapeutic compounds. Once close to the target tissue, Bioxome naturally fuse with the cell membrane and release the inner compound. Orgenesis is interested in evaluating the potential of Bioxome as new drug delivery system for treatment of several diseases, including skin repair, local tumour or COVID19. Methods, Results & Conclusion(s): Bioxome were obtained from adipose- derived Mesenchymal Stem Cells, with a process of organic- solvent lipid extraction, followed by lyophilization and sonication assemblage. During the sonication process, Bioxome were charged or not with several cargos. Size distribution of empty Bioxome was detected by Particle Size Analyzer (NanoSight). Electron Microscopy (EM) was performed to assess Bioxome morphology. Lipid content was evaluated by electrospray ionization system. Dose response in vitro test on human lung fibroblasts treated or not with Bioxome encapsulating a specific cargo (API) against COVID19 were performed. NanoSight analysis showed that nanoparticle size in Bioxome samples ranged between 170+/-50 nm, with a concentration ranging between 109-1010+/-106 particles/mL. EM clearly showed the double phospholipid layers that composes the Bioxome. Stability study demonstrated that Bioxome are stable in size and concentration up to 90 days at +4Cdegree or even at RT. No change in size between encapsulated Bioxome with small size (~340 Da) cargo vs empty Bioxome was observed up to 30 days storage. Lipidomic analysis approach revealed that the yield of lipids and their composition are satisfactory for a therapeutic product using Bioxome. Lastly, in the in vitro model of COVID19, Bioxome encapsulating API effectively saved cells from death (20x vs untreated cells) and at lower doses of API than these of non-encapsulated cargo (0.005 microM vs 0.1 microM). Bioxome seems to be an excellent candidate for liposome mimetic tool as drug delivery system for targeting specific organs and diseases treatment.Copyright © 2023 International Society for Cell & Gene Therapy

Rapid protocols to support COVID-19 clinical diagnosis based on hematological parameters

Purpose: In December 2019, the Covid-19 pandemic began in the world. To reduce mortality, in addiction to mass vaccination, it is necessary to massify and accelerate clinical diagnosis, as well as creating new ways of monitoring patients that can help in the construction of specific treatments for the disease. Objective: In this work, we propose rapid protocols for clinical diagnosis of COVID-19 through the automatic analysis of hematological parameters using evolutionary computing and machine learning. These hematological parameters are obtained from blood tests common in clinical practice. Method: We investigated the best classifier architectures. Then, we applied the particle swarm optimization algorithm (PSO) to select the most relevant attributes: serum glucose, troponin, partial thromboplastin time, ferritin, D-dimer, lactic dehydrogenase, and indirect bilirubin. Then, we assessed again the best classifier architectures, but now using the reduced set of features. Finally, we used decision trees to build four rapid protocols for Covid-19 clinical diagnosis by assessing the impact of each selected feature. The proposed system was used to support clinical diagnosis and assessment of disease severity in patients admitted to intensive and semi-intensive care units as a case study in the city of Paudalho, Brazil. Results: We developed a web system for Covid-19 diagnosis support. Using a 100-tree random forest, we obtained results for accuracy, sensitivity, and specificity superior to 99%. After feature selection, results were similar. The four empirical clinical protocols returned accuracies, sensitivities and specificities superior to 98%. Conclusion: By using a reduced set of hematological parameters common in clinical practice, it was possible to achieve results of accuracy, sensitivity, and specificity comparable to those obtained with RT-PCR. It was also possible to automatically generate clinical decision protocols, allowing relatively accurate clinical diagnosis even without the aid of the web decision support system. © 2023, The Author(s), under exclusive licence to The Brazilian Society of Biomedical Engineering.

Detecting Ransomware Attacks in Cloud Environment Using Machine Learning-Based Intelligence System in COVID-19 Chaos

2020-2022 provided nearly ideal circumstances for cybercriminals, with confusion and uncertainty dominating the planet due to COVID-19. Our way of life was altered by the COVID-19 pandemic, which also sparked a widespread shift to digital media. However, this change also increased people's susceptibility to cybercrime. As a result, taking advantage of the COVID-19 events' exceedingly unusual circumstances, cybercriminals launched widespread Phishing, Identity theft, Spyware, Trojan-horse, and Ransomware attacks. Attackers choose their victims with the intention of stealing their information, money, or both. Therefore, if we wish to safeguard people from these frauds at a time when millions have already fallen into poverty and the remaining are trying to survive, it is imperative that we put an end to these attacks and assailants. This manuscript proposes an intelligence system for identifying ransomware attacks using nature-inspired and machine-learning algorithms. To classify the network traffic in less time and with enhanced accuracy, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), two widely used algorithms are coupled in the proposed approach for Feature Selection (FS). Random Forest (RF) approach is used for classification. The system's effectiveness is assessed using the latest ransomware-oriented dataset of CIC-MalMem-2022. The performance is evaluated in terms of accuracy, model building, and testing time and it is found that the proposed method is a suitable solution to detect ransomware attacks. © 2022 IEEE.

Soft Ionization: Improving Indoor Air Quality

In this paper we report two applications of a subcategory of air cleaning devices based on soft ionization that do not cause molecular fragmentation. A system that includes two unipolar ionizing modules has been used to simultaneously produce positive and negative ions in the air. In one set of experiments a large chamber (28 m3) was used to study the effect of ions on reducing PM1.0 particles produced by a research grade calibrated cigarette. The data presented in this paper were obtained using a carbon-brush-based bipolar ionizer and a MERV 10 filter with electret media in a recirculating HVAC system. Significant improvement in removal rate of fine and ultrafine particles was achieved when using the bipolar ionizer in conjunction with the MERV 10 filter. The second set of experiments were conducted using a 36 m3 chamber, following BSL-3 standards, to study the effect of ions on aerosolized SARS-CoV-2. Results of these investigations reveal the inactivation rate of SARS-CoV-2 are enhanced when ions are introduced in the air;inactivation rates were increased by more than 60%and 90%for ion densities of 10,000/cc and 18,000/cc. IEEE

Inhalation Vaccine Development

Numerous advantages to inhalation vaccines Vaccines delivered via inhalation enable targeting of the respiratory tract mucosa and generation of both humoral and cell-mediated immunity, according to Pierre A. Morgon, executive vice president. [...]inhaled vaccines delivered as liquids using nebulizers can potentially be administered with lower requirement for extensive healthcare infrastructure or as many trained healthcare personnel within an immunization centre (2). Researchers at McMaster University, for instance, have shown inhalation of a tuberculosis vaccine to be more effective than delivery via nasal sprays, because the vaccine penetrates much deeper into the airway (8). Because inhaled vaccines provide local immunity to the respiratory tract, they are seen to be ideal solutions for interrupting the spread of viruses with high transmission rates and the potential to lead to global pandemics (9). Beyond these two approaches, there are inhalation vaccines under development based on attenuated influenza virus, parainfluenza virus (PIV) 5, lentiviruses, Newcastle disease virus (NDV), and vesicular stomatitis virus (VSV);bacterium vectors, nucleic acids (messenger RNA, DNA), and protein subunits (3).

Preface

The tenth international symposium on "Large TPCs for low-energy rare event detection” was held in Paris from 15th to 17th of December 2021 at the Institute of Astroparticle physics of the University of Paris. The 2020 issue of this conference series was cancelled due to the Covid pandemic. The symposium was organized in a hybrid mode, which allowed about 40 people to attend in-person among a total of 131 registered participants. Very strict sanitary measures were taken to keep the meeting safe.As in previous events the program included neutrino physics, dark matter and axion searches, related detector R&D and theoretical aspects.To celebrate the tenth edition of the symposium the conference was held on three full days. Special speakers were invited to give a historical overview related to our field. David Nygren shared his memories of the invention and development of the Time Projection Chamber. François Vannucci revealed to us the invisible world of neutrinos. Ioannis Giomataris pointed out various innovative ideas that emerged during presentations and discussions in the last two decades. Jean Iliopoulos retraced the concept and development of the Standard Model and shared his personal vision on the future of particle physics.We wish to thank the many people who contributed to the success of the conference and especially the conveners of the sessions, who allowed for a smooth running of the meeting. We particularly acknowledge the APC management for providing the nice Buffon auditorium and infrastructure. We also thank DSM-Irfu, the University of Zaragoza, the European Research Council and ACAV Ile de France for their valuable support.The organizersList of Organizing Committee is available in this Pdf.

Enhancing immune protection against MERS-CoV: the synergistic effect of proteolytic cleavage sites and the fusion peptide and RBD domain targeting VLP immunization.

Introduction: The Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is a zoonotic infectious virus that has caused significant outbreaks in the Middle East and beyond. Due to a highly mortality rate, easy transmission, and rapid spread of the MERS-CoV, it remains as a significant public health treat. There is currently no licensed vaccine available to protect against MERS-CoV. Methods: In this study, we investigated whether the proteolytic cleavage sites and fusion peptide domain of the MERS-CoV spike (S) protein could be a vaccine target to elicit the MERS-CoV S protein-specific antibody responses and confer immune protection against MERS-CoV infection. Our results demonstrate that immunization of the proteolytic cleavage sites and the fusion peptide domain using virus-like particle (VLP) induced the MERS-CoV S protein-specific IgG antibodies with capacity to neutralize pseudotyped MERS-CoV infection in vitro. Moreover, proteolytic cleavage sites and the fusion peptide VLP immunization showed a synergistic effect on the immune protection against MERS-CoV infection elicited by immunization with VLP expressing the receptor binding domain (RBD) of the S protein. Additionally, immune evasion of MERS-CoV RBD variants from anti-RBD sera was significantly controlled by anti-proteolytic cleavage sites and the fusion peptide sera. Conclusion and discussion: Our study demonstrates the potential of VLP immunization targeting the proteolytic cleavage sites and the fusion peptide and RBD domains of the MERS-CoV S protein for the development of effective treatments and vaccines against MERS-CoV and related variants.

Studying how administration route and dose regulates antibody generation against LNPs for mRNA delivery with single-particle resolution.

Following the recent approval of both siRNA- and mRNA-based therapeutics, nucleic acid therapies are considered a game changer in medicine. Their envisioned widespread use for many therapeutic applications with an array of cellular target sites means that various administration routes will be employed. Concerns exist regarding adverse reactions against the lipid nanoparticles (LNPs) used for mRNA delivery, as PEG coatings on nanoparticles can induce severe antibody-mediated immune reactions, potentially being boosted by the inherently immunogenic nucleic acid cargo. While exhaustive information is available on how physicochemical features of nanoparticles affects immunogenicity, it remains unexplored how the fundamental choice of administration route regulates anti-particle immunity. Here, we directly compared antibody generation against PEGylated mRNA-carrying LNPs administered by the intravenous, intramuscular, or subcutaneous route, using a novel sophisticated assay capable of measuring antibody binding to authentic LNP surfaces with single-particle resolution. Intramuscular injections in mice were found to generate overall low and dose-independent levels of anti-LNP antibodies, while both intravenous and subcutaneous LNP injections generated substantial and highly dose-dependent levels. These findings demonstrate that before LNP-based mRNA medicines can be safely applied to new therapeutic applications, it will be crucial to carefully consider the choice of administration route.

Spinal fusion is an aerosol generating procedure.

BACKGROUND: Transmission of severe acute respiratory syndrome coronavirus 2 can occur during aerosol generating procedures. Several steps in spinal fusion may aerosolize blood but little data exists to quantify the risk this may confer upon surgeons. Aerosolized particles containing infectious coronavirus are typically 0.5-8.0 µm. AIM: To measure the generation of aerosols during spinal fusion using a handheld optical particle sizer (OPS). METHODS: We quantified airborne particle counts during five posterior spinal instrumentation and fusions (9/22/2020-10/15/2020) using an OPS near the surgical field. Data were analyzed by 3 particle size groups: 0.3-0.5 µm/m3, 1.0-5.0 µm/m3, and 10.0 µm/m3. We used hierarchical logistic regression to model the odds of a spike in aerosolized particle counts based on the step in progress. A spike was defined as a > 3 standard deviation increase from average baseline levels. RESULTS: Upon univariate analysis, bovie (P < 0.0001), high speed pneumatic burring (P = 0.009), and ultrasonic bone scalpel (P = 0.002) were associated with increased 0.3-0.5 µm/m3 particle counts relative to baseline. Bovie (P < 0.0001) and burring (P < 0.0001) were also associated with increased 1-5 µm/m3 and 10 µm/m3 particle counts. Pedicle drilling was not associated with increased particle counts in any of the size ranges measured. Our logistic regression model demonstrated that bovie (OR = 10.2, P < 0.001), burring (OR = 10.9, P < 0.001), and bone scalpel (OR = 5.9, P < 0.001) had higher odds of a spike in 0.3-0.5 µm/m3 particle counts. Bovie (OR = 2.6, P < 0.001), burring (OR = 5.8, P < 0.001), and bone scalpel (OR = 4.3, P = 0.005) had higher odds of a spike in 1-5 µm/m3 particle counts. Bovie (OR = 0.3, P < 0.001) and drilling (OR = 0.2, P = 0.011) had significantly lower odds of a spike in 10 µm/m3 particle counts relative to baseline. CONCLUSION: Several steps in spinal fusion are associated with increased airborne particle counts in the aerosol size range. Further research is warranted to determine if such particles have the potential to contain infectious viruses. Previous research has shown that electrocautery smoke may be an inhalation hazard for surgeons but here we show that usage of the bone scalpel and high-speed burr also have the potential to aerosolize blood.

Aerosol Particle Size Influences the Infectious Dose and Disease Severity in a Golden Syrian Hamster Model of Inhalational COVID-19.

Background: Significant evidence suggests that SARS-CoV-2 can be transmitted via respiratory aerosols, which are known to vary as a function of respiratory activity. Most animal models examine disease presentation following inhalation of small-particle aerosols similar to those generated during quiet breathing or speaking. However, despite evidence that particle size can influence dose-infectivity relationships and disease presentation for other microorganisms, no studies have examined the infectivity of SARS-CoV-2 contained in larger particle aerosols similar to those produced during coughing, singing, or talking. Therefore, the aim of the present study was to assess the influence of aerodynamic diameter on the infectivity and virulence of aerosols containing SARS-CoV-2 in a hamster model of inhalational COVID-19. Methods: Dose-response relationships were assessed for two different aerosol particle size distributions, with mass median aerodynamic diameters (MMADs) of 1.3 and 5.2 µm in groups of Syrian hamsters exposed to aerosols containing SARS-CoV-2. Results: Disease was characterized by viral shedding in oropharyngeal swabs, increased respiratory rate, decreased activity, and decreased weight gain. Aerosol particle size significantly influenced the median doses to induce seroconversion and viral shedding, with both increasing ∼30-fold when the MMAD was increased. In addition, disease presentation was dose-dependent, with seroconversion and viral shedding occurring at lower doses than symptomatic disease characterized by increased respiratory rate and decreased activity. Conclusions: These results suggest that aerosol particle size may be an important factor influencing the risk of COVID-19 transmission and needs to be considered when developing animal models of disease. This result agrees with numerous previous studies with other microorganisms and animal species, suggesting that it would be generally translatable across different species. However, it should be noted that the absolute magnitude of the observed shifts in the median doses obtained with the specific particle sizes utilized herein may not be directly applicable to other species.

Integrating local and neighboring area influences into vulnerability modeling of infectious diseases in Singapore

Infectious disease spreading is a spatial interaction process. Assessing community vulnerability to infectious diseases thus requires not only information on local demographic and built environmental conditions, but also insights into human activity interactions with neighboring areas that can lead to the transition of vulnerability from locations to locations. This study presented an analytical framework based on the Particle Swarm Optimization model to estimate the weights of the factors for vulnerability modeling, and a local proportional parameter for use in the integration of the local and neighboring area risks. A country model and five cross-region validation models were developed for the case study of Singapore to assess the vulnerability to COVID-19. The results showed that the identified weights for the factors were robust throughout the optimization process and across various models. The local proportional parameter could be set slightly higher in between 0.6 and 0.8 (out of 1), signifying that the local effect was higher than the neighboring effect. Computation of the weights from the optimal solutions for the integrated vulnerability index showed that the factors of human activity intensity and accessibility to amenities had much higher weights, at 0.5 and 0.3, respectively. Conversely, the weights of population density, elderly population, social economic status and land use diversity were much lower. These findings underscored the importance of considering non-equal weights for factors and incorporating spatial interactions between local and neighboring areas for vulnerability modeling, to provide to a more comprehensive assessment of vulnerability to infectious diseases.

The size distribution of SARS-CoV-2 genetic material in airborne particles sampled in hospital and home care environments occupied by COVID-19 positive subjects.

Characterizing the size distribution of airborne particles carrying SARS-CoV-2 virus is essential for understanding and predicting airborne transmission and spreading of COVID-19 disease in hospitals as well as public and home indoor settings. Nonetheless, few data are currently available on virus-laden particle size distribution. Thus, the aim of this study is reporting the total concentrations and size distributions of SARS-CoV-2- genetic material in airborne particles sampled in hospital and home environments. A nanoMOUDI R122 cascade impactor (TSI, USA) was used to collect size-segregated aerosol down to the sub-micron range in home and in three different hospital environments in presence of infected patients in order to provide the concentration of airborne SARS-CoV-2 genetic material for each particle size range at different sampling locations. Providing one of the largest datasets of detailed size-fractionated airborne SARS-CoV-2 RNA to date, we found that 45.2 % of the total sub- and super-micrometric fractions were positive for SARS-CoV-2 with its genetic material being present in 17.7 % of sub-micrometric (0.18-1 µm) and 81.9 % of super-micrometric (>1 µm) fractions. The highest concentration of SARS-CoV-2 genetic material in total suspended particles (5.6 ± 3.4 RNA copies m-3) was detected in the room occupied with patients with more severe COVID-19 symptoms collected during the patients' high flow nasal oxygen therapy. The highest concentration at certain particle size fraction strongly depends on the sampling environment. However, the contribution of SARS-CoV-2 genetic material was in favour of super-micrometric compared to sub-micrometric particle size range. The evaluation of the individual risk of infection was carried out on the basis of the obtained data considering a hypothetical exposure scenario. The obtained results indicate the necessity of the protective masks in presence of infected subjects, especially while staying for longer period of time in the hospital environments.

Visual prediction and parameter optimization of viral dynamics in the mucus milieu of the upper airway based on CFPD-HCD analysis.

BACKGROUND AND OBJECTIVE: Respiratory diseases caused by viruses are a major human health problem. To better control the infection and understand the pathogenesis of these diseases, this paper studied SARS-CoV-2, a novel coronavirus outbreak, as an example. METHODS: Based on coupled computational fluid and particle dynamics (CFPD) and host-cell dynamics (HCD) analyses, we studied the viral dynamics in the mucus layer of the human nasal cavity-nasopharynx. To reproduce the effect of mucociliary movement on the diffusive and convective transport of viruses in the mucus layer, a 3D-shell model was constructed using CT data of the upper respiratory tract (URT) of volunteers. Considering the mucus environment, the HCD model was established by coupling the target cell-limited model with the convection-diffusion term. Parameter optimization of the HCD model is the key problem in the simulation. Therefore, this study focused on the parameter optimization of the viral dynamics model, divided the geometric model into multiple compartments, and used Monolix to perform the nonlinear mixed effects (NLME) of pharmacometrics to discuss the influence of factors such as the number of mucus layers, number of compartments, diffusion rate, and mucus flow velocity on the prediction results. RESULTS: The findings showed that sufficient experimental data can be used to estimate the corresponding parameters of the HCD model. The optimized convection-diffusion case with a two-layer multi-compartment low-velocity model could accurately predict the viral dynamics. CONCLUSIONS: Its visualization process could explain the symptoms of the disease in the nose and contribute to the prevention and targeted treatment of respiratory diseases.

Insisting with mask or demanding for more: Plights of the transmission of airborne diseases

Airborne transmission is worldwide popular topic with numerous discussion and researches since influenza pandemic could cost the global economy a lot. In this part of research, we mainly focus on the mechanisms of airborne transmission, together with some determinant factors that influence the spread of aerosols like temperature, humidity and particle size. Finally with several existed cases, insisting masks wearing, especially with three-layer masks wearing are necessary in nowadays for efficiently preventing the transmission of airborne diseases up to 90%. Other possible infection control measures like 2m social distancing are also needed as hygiene measures. © 2023 SPIE.

Effects of various respiratory activities on human aerosol emissions: experimental design and preliminary results

This study combines particle measurements and acoustic measurements to study aerosols generated in breathing, speaking, singing and coughing. Particle measurements are carried out using a portable measurement chamber designed specially for the study. Acoustic measurements of voice production are conduced to standardize measurements in human aerosol emission and to reveal possible reasons for the individual differences in particle generation. Understanding mechanisms of human aerosol generation is important in trying to understand how the airborne transmission of pathogens takes place and furthermore in assessing how to minimize the risk of transmission. The results can be used in the context of all airborne diseases. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Allergic reactions of COVID-19 vaccine based on mRNA-LNP and its pharmacokinetics in vivo

Vaccination has been proved to be the most effective strategy to prevent the Corona Virus Disease 2019 (COVID-19). The mRNA vaccine based on nano drug delivery system (NDDS) - lipid nanoparticles (LNP) has been widely used because of its high effectiveness and safety. Although there have been reports of severe allergic reactions caused by mRNA-LNP vaccines, the mechanism and components of anaphylaxis have not been completely clarified yet. This review focuses on two mRNA-LNP vaccines, BNT162b2 and mRNA-1273. After summarizing the structural characteristics, potential allergens, possible allergic reaction mechanism, and pharmacokinetics of mRNA and LNP in vivo, this article then reviews the evaluation methods for patients with allergic history, as well as the regulations of different countries and regions on people who should not be vaccinated, in order to promote more safe injection of vaccines. LNP has become a recognized highly customizable nucleic acid delivery vector, which not only shows its value in mRNA vaccines, but also has great potential in treating rare diseases, cancers and other broad fields in the future. At the moment when mRNA-LNP vaccines open a new era of nano medicine, it is expected to provide some inspiration for safety research in the process of research, development and evaluation of more nano delivery drugs, and promote more nano drugs successfully to market.Copyright © 2023, Chinese Pharmaceutical Association. All rights reserved.

Dual-stage day-ahead optimized performance of renewable-based microgrids

In distributed networks, wind turbine generators (WTGs) are to be optimally sized and positioned for cost-effective and efficient network service. Various meta-heuristic algorithms have been proposed to allocate WTGs within microgrids. However, the ability of these optimizers might not be guaranteed with uncertainty loads and wind generations. This paper presents novel meta-heuristic optimizers to mitigate extreme voltage drops and the total costs associated with WTGs allocation within microgrids. Arithmetic optimization algorithm (AOA), coronavirus herd immunity optimizer, and chimp optimization algorithm (ChOA) are proposed to manipulate these aspects. The trialed optimizers are developed and analyzed via Matlab, and fair comparison with the grey wolf optimization, particle swarm optimization, and the mature genetic algorithm are introduced. Numerical results for a large-scale 295-bus system (composed of IEEE 141-bus, IEEE 85-bus, IEEE 69-bus subsystems) results illustrate the AOA and the ChOA outperform the other optimizers in terms of satisfying the objective functions, convergence, and execution time. The voltage profile is substantially improved at all buses with the penetration of the WTG with satisfactory power losses through the transmission lines. Day-ahead is considered generic and efficient in terms of total costs. The AOA records costs of 16.575M$/year with a reduction of 31% compared to particle swarm optimization. © 2023 The Authors. IET Renewable Power Generation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.