Enabling mRNA medicine for brain tumors

mRNA is a new class of drugs that has the potential to revolutionize the treatment of brain tumors. Thanks to the COVID-19 mRNA vaccines and numerous therapy-based clinical trials, it is now clear that lipid nanoparticles (LNPs) are a clinically viable means to deliver RNA therapeutics. However, LNP-mediated mRNA delivery to brain tumors remains elusive. Over the past decade, numerous studies have shown that tumor cells communicate with each other via small extracellular vesicles, which are around 100 nm in diameter and consist of lipid bilayer membrane similar to synthetic lipidbased nanocarriers. We hypothesized that rationally designed LNPs based on extracellular vesicle mimicry would enable efficient delivery of RNA therapeutics to brain tumors without undue toxicity. We synthesized LNPs using four components similar to the formulation used in the mRNA COVID19 vaccines (Moderna and Pfizer): ionizable lipid, cholesterol, helper lipid and polyethylene glycol (PEG)-lipid. For the in vitro screen, we tested ten classes of helper lipids based on their abundance in extracellular vesicle membranes, commercial availability, and large-scale production feasibility while keeping rest of the LNP components unchanged. The transfection kinetics of GFP mRNA encapsulated in LNPs and doped with 16 mol% of helper lipids was tested using GL261, U87 and SIM-A9 cell lines. Several LNP formations resulted in stable transfection (upto 5 days) of GFP mRNA in all the cell lines tested in vitro. The successful LNP candidates (enabling >80% transfection efficacy) were then tested in vivo to deliver luciferase mRNA to brain tumors via intrathecal administration in a syngeneic glioblastoma (GBM) mouse model, which confirmed luciferase expression in brain tumors in the cortex. LNPs were then tested to deliver Cre recombinase mRNA in syngeneic GBM mouse model genetically modified to express tdTomato under LoxP marker cassette that enabled identification of LNP targeted cells. mRNA was successfully delivered to tumor cells (70-80% transfected) and a range of different cells in the tumor microenvironment, including tumor-associated macrophages (80-90% transfected), neurons (31- 40% transfected), neural stem cells (39-62% transfected), oligodendrocytes (70-80% transfected) and astrocytes (44-76% transfected). Then, LNP formulations were assessed for delivering Cas9 mRNA and CD81 sgRNA (model protein) in murine syngeneic GBM model to enable gene editing in brain tumor cells. Sanger sequencing showed that CRISPR-Cas9 editing was successful in ~94% of brain tumor cells in vivo. In conclusion, we have developed a library of safe LNPs that can transfect GBM cells in vivo with high efficacy. This technology can potentially be used to develop novel mRNA therapies for GBM by delivering single or multiple mRNAs and holds great potential as a tool to study brain tumor biology.

Information Systems Resilience: The Role of Flexibility and Stability

This paper contributes to conceptualization of information system resilience. By building upon and extending the framework of Heeks and Ospina (2019), we argue that an information system's ability to be resilient lies in its balance between stability and flexibility. Based on empirical findings we suggest that a stable core and flexibility to change is crucial when a digital system is faced with unforeseen adversities. We hope to contribute to more theorizing of the information system resilience and inspire further research on this subject. The paper may also have practical value for stakeholders working with implementation of national information systems in the health sector. This is a qualitative case study conducted together with the Health Information Systems Programme (HISP) at the Institute of Informatics, University of Oslo. Our findings are based on empirical insights related to the DHIS2 software during the Covid-19 response. © 2022 Owner/Author.

Prediction of Stable Angina for Coronary Artery Diseases using Boosting Algorithm

Narrowed arteries block the blood flow to the heart muscle and other parts of the body, which can cause chest pain. Coronary arteries disease (CAD) can weaken the heart muscle causing heart failure, in which the heart cannot pump blood. A person with underlying diseases is more prone to get highly affected by COVID-19 because of the decreased immunity. Cardiovascular disease and coronary heart disease have been associated with worsened outcomes of COVID-19 patients. Thus, detecting CAD at a proper stage is crucial to avoid any further serious issues. This paper is an empirical analysis to predict stable angina for CAD using Histogram gradient boosting (HGB) and Adaboost (ADB) classifier algorithm and compared the performance with traditional Naïve Bayes (NB) algorithm. © 2023 IEEE.

Production and characterisation of a SARSCoV-2 S-protein RBD homodimer with increased avidity for specific antibodies.

Monitoring of the proportion of immune individuals and the effectiveness of vaccination in a population involves evaluation of several important parameters, including the level of virus-neutralising antibodies. In order to combat the COVID-19 pandemic, it is essential to develop approaches to detecting SARS-CoV-2 neutralising antibodies by safe, simple and rapid methods that do not require live viruses. To develop a test system for enzyme-linked immunosorbent assay (ELISA) that detects potential neutralising antibodies, it is necessary to obtain a highly purified recombinant receptor-binding domain (RBD) of the spike (S) protein with high avidity for specific antibodies. The aim of the study was to obtain and characterise a SARSCoV-2 S-protein RBD homodimer and a recombinant RBD-expressing cell line, as well as to create an ELISA system for detecting potential neutralising antibodies. Material(s) and Method(s): the genetic construct was designed in silico. To generate a stable producer cell line, the authors transfected CHO-S cells, subjected them to antibiotic pressure, and selected the optimal clone. To isolate monomeric and homodimeric RBD forms, the authors purified the recombinant RBD by chromatographic methods. Further, they analysed the activity of the RBD forms by Western blotting, bio-layer interferometry, and indirect ELISA. The analysis involved monoclonal antibodies GamXRH19, GamP2C5, and h6g3, as well as serum samples from volunteers vaccinated with Gam-COVID-Vac (Sputnik V) and unvaccinated ones. Result(s): the authors produced the CHO-S cell line for stable expression of the recombinant SARS-CoV-2 S-protein RBD. The study demonstrated the recombinant RBD's ability to homodimerise after fed-batch cultivation of the cell line for more than 7 days due to the presence of unpaired cysteines. The purified recombinant RBD yield from culture broth was 30-50 mg/L. Monomeric and homodimeric RBD forms were separated using gel-filtration chromatography and characterised by their ability to interact with specific monoclonal antibodies, as well as with serum samples from vaccinated volunteers. The homodimeric recombinant RBD showed increased avidity for both monoclonal and immune sera antibodies. Conclusion(s): the homodimeric recombinant RBD may be more preferable for the analysis of levels of antibodies to the receptor-binding domain of the SARS-CoV-2 S protein.Copyright © 2023 Authors. All rights reserved.

Production and characterisation of a SARSCoV-2 S-protein RBD homodimer with increased avidity for specific antibodies

Monitoring of the proportion of immune individuals and the effectiveness of vaccination in a population involves evaluation of several important parameters, including the level of virus-neutralising antibodies. In order to combat the COVID-19 pandemic, it is essential to develop approaches to detecting SARS-CoV-2 neutralising antibodies by safe, simple and rapid methods that do not require live viruses. To develop a test system for enzyme-linked immunosorbent assay (ELISA) that detects potential neutralising antibodies, it is necessary to obtain a highly purified recombinant receptor-binding domain (RBD) of the spike (S) protein with high avidity for specific antibodies. The aim of the study was to obtain and characterise a SARSCoV-2 S-protein RBD homodimer and a recombinant RBD-expressing cell line, as well as to create an ELISA system for detecting potential neutralising antibodies. Material(s) and Method(s): the genetic construct was designed in silico. To generate a stable producer cell line, the authors transfected CHO-S cells, subjected them to antibiotic pressure, and selected the optimal clone. To isolate monomeric and homodimeric RBD forms, the authors purified the recombinant RBD by chromatographic methods. Further, they analysed the activity of the RBD forms by Western blotting, bio-layer interferometry, and indirect ELISA. The analysis involved monoclonal antibodies GamXRH19, GamP2C5, and h6g3, as well as serum samples from volunteers vaccinated with Gam-COVID-Vac (Sputnik V) and unvaccinated ones. Result(s): the authors produced the CHO-S cell line for stable expression of the recombinant SARS-CoV-2 S-protein RBD. The study demonstrated the recombinant RBD's ability to homodimerise after fed-batch cultivation of the cell line for more than 7 days due to the presence of unpaired cysteines. The purified recombinant RBD yield from culture broth was 30-50 mg/L. Monomeric and homodimeric RBD forms were separated using gel-filtration chromatography and characterised by their ability to interact with specific monoclonal antibodies, as well as with serum samples from vaccinated volunteers. The homodimeric recombinant RBD showed increased avidity for both monoclonal and immune sera antibodies. Conclusion(s): the homodimeric recombinant RBD may be more preferable for the analysis of levels of antibodies to the receptor-binding domain of the SARS-CoV-2 S protein.Copyright © 2023 Authors. All rights reserved.

The Effects of the COVID-19 Pandemic on the Coworking Spaces in Poland

The chapter deals with the changes occurring during the COVID-19 pandemic in the coworking sector. We have collected data and information from primary and secondary sources. The latter include in-depth interviews, covert participant observations and computer-assisted telephone interviews (CATI). We analysed the changes of the number of coworking spaces (CSs) and main mechanisms behind them. The findings reveal the relatively limited scale of decrease in the number of coworking spaces and illustrate how the pandemic outbreak influenced the effects of CS operations, especially on the real estate market. It is argued that independently-run CSs suffered the most, whereas corporate CSs with a stable core of corporate clients, central location and limited competition have been more resilient. With regard to the changes generated by the COVID-19 pandemic, the most significant transformations are seen in the decreasing number of non-virtual events organised by CSs, whereas the scale of the other impacts of CSs on the local milieu decreased slightly. © 2023, The Author(s).

Production and characterisation of a SARSCoV-2 S-protein RBD homodimer with increased avidity for specific antibodies.

Monitoring of the proportion of immune individuals and the effectiveness of vaccination in a population involves evaluation of several important parameters, including the level of virus-neutralising antibodies. In order to combat the COVID-19 pandemic, it is essential to develop approaches to detecting SARS-CoV-2 neutralising antibodies by safe, simple and rapid methods that do not require live viruses. To develop a test system for enzyme-linked immunosorbent assay (ELISA) that detects potential neutralising antibodies, it is necessary to obtain a highly purified recombinant receptor-binding domain (RBD) of the spike (S) protein with high avidity for specific antibodies. The aim of the study was to obtain and characterise a SARSCoV-2 S-protein RBD homodimer and a recombinant RBD-expressing cell line, as well as to create an ELISA system for detecting potential neutralising antibodies. Material(s) and Method(s): the genetic construct was designed in silico. To generate a stable producer cell line, the authors transfected CHO-S cells, subjected them to antibiotic pressure, and selected the optimal clone. To isolate monomeric and homodimeric RBD forms, the authors purified the recombinant RBD by chromatographic methods. Further, they analysed the activity of the RBD forms by Western blotting, bio-layer interferometry, and indirect ELISA. The analysis involved monoclonal antibodies GamXRH19, GamP2C5, and h6g3, as well as serum samples from volunteers vaccinated with Gam-COVID-Vac (Sputnik V) and unvaccinated ones. Result(s): the authors produced the CHO-S cell line for stable expression of the recombinant SARS-CoV-2 S-protein RBD. The study demonstrated the recombinant RBD's ability to homodimerise after fed-batch cultivation of the cell line for more than 7 days due to the presence of unpaired cysteines. The purified recombinant RBD yield from culture broth was 30-50 mg/L. Monomeric and homodimeric RBD forms were separated using gel-filtration chromatography and characterised by their ability to interact with specific monoclonal antibodies, as well as with serum samples from vaccinated volunteers. The homodimeric recombinant RBD showed increased avidity for both monoclonal and immune sera antibodies. Conclusion(s): the homodimeric recombinant RBD may be more preferable for the analysis of levels of antibodies to the receptor-binding domain of the SARS-CoV-2 S protein.Copyright © 2023 Authors. All rights reserved.

A rapid procedure to generate stably transfected HEK293 suspension cells for recombinant protein manufacturing: Yield improvements, bioreactor production and downstream processing.

The human cell line HEK293 is one of the preferred choices for manufacturing therapeutic proteins and viral vectors for human applications. Despite its increased use, it is still considered in disadvantage in production aspects compared to cell lines such as the CHO cell line. We provide here a simple workflow for the rapid generation of stably transfected HEK293 cells expressing an engineered variant of the SARS-CoV-2 Receptor Binding Domain (RBD) carrying a coupling domain for linkage to VLPs through a bacterial transpeptidase-sortase (SrtA). To generate stable suspension cells expressing the RBD-SrtA, a single two plasmids transfection was performed, with hygromycin selection. The suspension HEK293 were grown in adherent conditions, with 20% FBS supplementation. These transfection conditions increased cell survival, allowing the selection of stable cell pools, which was otherwise not possible with standard procedures in suspension. Six pools were isolated, expanded and successfully re-adapted to suspension with a gradual increase of serum-free media and agitation. The complete process lasted four weeks. Stable expression with viability over 98% was verified for over two months in culture, with cell passages every 4-5 days. With process intensification, RBD-SrtA yields reached 6.4 µg/mL and 13.4 µg/mL in fed-batch and perfusion-like cultures, respectively. RBD-SrtA was further produced in fed-batch stirred tank 1L-bioreactors, reaching 10-fold higher yields than perfusion flasks. The trimeric antigen displayed the conformational structure and functionality expected. This work provides a series of steps for stable cell pool development using suspension HEK293 cells aimed at the scalable production of recombinant proteins.

The YOPP Final Summit: Assessing Past and Forecasting Future Polar Prediction Research

The successes of YOPP from the presentations and keynote presentations included * a better understanding of the impact of key polar measurements (radiosondes and space-based instruments such as microwave radiometers), and recent advancements in the current NWP observing system, achieved through coordinated OSEs in both polar regions (e.g., Sandu et al. 2021);* enhanced understanding of the linkages between Arctic and midlatitude weather (e.g., Day et al. 2019);* advancements in the atmosphere–ocean–sea ice and atmosphere–land–cryosphere coupling in NWP, and in assessing and recognizing the added value of coupling in Earth system models (e.g., Bauer et al. 2016);* deployment of tailored polar observation campaigns to address yet-unresolved polar processes (e.g., Renfrew et al. 2019);* progress in verification and forecasting techniques for sea ice, including a novel headline score (e.g., Goessling and Jung 2018);* advances in process understanding and process-based evaluation with the establishment of the YOPPsiteMIP framework and tools (Svensson 2020);* better understanding of emerging societal and stakeholder needs in the Arctic and Antarctic (e.g., Dawson et al. 2017);and * innovative transdisciplinary methodologies for coproducing salient information services for various user groups (Jeuring and Lamers 2021). The YOPP Final Summit identified a number of areas worthy of prioritized research in the area of environmental prediction and services for the polar regions: * coupled atmosphere, sea ice, and ocean models with an emphasis on advanced parameterizations and enhanced resolution at which critical phenomena start to be resolved (e.g., ocean eddies);* improved definition and representation of stable boundary layer processes, including mixed-phase clouds and aerosols;incorporation of wave–ice–ocean interactions;* radiance assimilation over sea ice, land ice, and ice sheets;understanding of linkages between polar regions and lower latitudes from a prediction perspective;* exploring the limits of predictability of the atmosphere–cryosphere–ocean system;* an examination of the observational representativeness over land, sea ice, and ocean;better representation of the hydrological cycle;and * transdisciplinary work with the social science community around the use of forecasting services and operational decision-making to name but a few. The presentations and discussions at the YOPP Final Summit identified the major legacy elements of YOPP: the YOPPsiteMIP approach to enable easy comparison of collocated multivariate model and observational outputs with the aim of enhancing process understanding, the development of an international and multi-institutional community across many disciplines investigating aspects of polar prediction and services, the YOPP Data Portal3 (https://yopp.met.no/), and the education and training delivered to early-career polar researchers. Next steps Logistical issues, the COVID-19 pandemic, but also new scientific questions (e.g., the value of targeted observations in the Southern Hemisphere), as well as technical issues emerging toward the end of the YOPP Consolidation Phase, resulted in the decision to continue the following three YOPP activities to the end of 2023: (i) YOPP Southern Hemisphere (YOPP-SH);(ii) Model Intercomparison and Improvement Project (MIIP);of which YOPPSiteMIP is a critical element;and (iii) the Societal, Economics and Research Applications (PPP-SERA) Task Team.

Synthesis and crystal characteristics of nirmatrelvir

Several synthetic routes of nirmatrelvir (the ingredient of a new drug to treat COVID-19 made by Pfizer) have been reported. We focused on a second route to improve the synthetic method of nirmatrelvir with a methodology that included different steps. The first step was an analysis of reaction byproducts using acetonitrile as a solvent of the condensation reaction to improve the inversion rate. Then, we used isobutyl acetate as a crystalline solvent to obtain the key intermediate as a solvate, which was a stable crystal product with high purity. Complementarily, we also used trifluoroacetic anhydride as the primary-amide dehydrating agent, and 2-methyl tetrahydrofuran as the solvent to prepare nirmatrelvir, which led to an overall yield of 48% via four steps and a purity of 99.5% according to high-performance liquid chromatography. We also investigated the crystal form of nirmatrelvir: the single-crystal features and transformation from a crystal form to nirmatrelvir were dependent upon temperature. Our data have great value for study of the synthetic method and crystal stability of nirmatrelvir. © 2023 The Royal Society of Chemistry.

Modeling dynamic VaR and CVaR of cryptocurrency returns with alpha-stable innovations

We employ alpha-stable distribution to dynamically compute risk exposure measures for the five most traded cryptocurrencies. Returns are jointly modeled with an ARMA-GARCH approach for their conditional mean and variance processes with alpha-stable innovations. We use the MLE method to estimate the parameters of this distribution, along with those of conditional mean and variance. Our results show that the dynamic approach is superior to the static method. We also find out that these risk measures of five cryptocurrencies do not offer the same pattern of behavior across subperiods (i.e., pre-, during- and post-COVID pandemic). © 2023 Elsevier Inc.

Using the basis-a profile as a predictor of sex offender treatment outcomes including assessed risk in an outpatient setting

This study aimed to understand the usefulness of the Basic Adlerian Scales for Interpersonal Success - Adult Form (BASIS-A) profile scores in the risk assessment of individuals convicted of a sexual criminal offense. Specifically, this study attempted to determine if a correlation existed between an individual's level of social interest and the difference in that individual's level of risk over time as measured by the STABLE-2007 and the Sex Offender Treatment Intervention and Progress Scale (SOTIPS) dynamic risk assessments. Due to the COVID-19 pandemic, the study was adapted to a hybrid of both in-person and virtual participation involving six total participants recruited from a private practice in suburban Illinois. Results of the partial correlation were not significant and deemed inconclusive due to low study participation. The impact of the pandemic on the study's outcome and the study's contribution to practice-oriented research as well as recommendations for future research regarding the BASIS-A, risk assessment, and practice-oriented research are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Mathematical Model and Analysis on the Impacts of Vaccination and Treatment in the Control of the COVID-19 Pandemic with Optimal Control

In this study, a nonlinear deterministic mathematical model that evaluates two important therapeutic measures of the COVID-19 pandemic: vaccination of susceptible and treatment for infected people who are in quarantine, is formulated and rigorously analyzed. Some of the fundamental properties of the model system including existence and uniqueness, positivity, and invariant region of solutions are proved under a certain meaningful set. The model exhibits two equilibrium points: disease-free and endemic equilibrium points under certain conditions. The basic reproduction number, R0, is derived via the next-generation matrix approach, and the dynamical behavior of the model is explored in detail. The analytical analysis reveals that the disease-free equilibrium solution is locally as well as globally asymptotically stable when the associated basic reproduction number is less than unity which indicates that COVID-19 dies out in the population. Also, the endemic equilibrium point is globally asymptotically stable whenever the associated basic reproduction number exceeds a unity which implies that COVID-19 establishes itself in the population. The sensitivity analysis of the basic reproduction number is computed to identify the most dominant parameters for the spreading out as well as control of infection and should be targeted by intervention strategies. Furthermore, we extended the considered model to optimal control problem system by introducing two time-dependent variables that represent the educational campaign to susceptibles and continuous treatment for quarantined individuals. Finally, some numerical results are illustrated to supplement the analytical results of the model using MATLAB ode45. © 2023 Alemzewde Ayalew et al.

Recent advances in optimization strategies and applications of plant bioreactors

Plant bioreactors have been the central part of molecular pharming. Vaccines, antibodies and functional foods produced by plant bioreactors with the benefits of cost-effectiveness, high scalability, rapid production, enabling post-translational modification, and no harmful pathogens contamination are increasingly accepted by the public. In February 2022, Health Canada approved the world's first plant-derived human vaccine Covifenz® for the prevention and treatment of COVID-19, marking the advent of the era of molecular pharming represented by plant bioreactors. This paper elaborates the development history of plant bioreactors, with the main host species representatives of leafy plants and seed plants, the stable and transient expression systems construction for various applications, as well as the enhancement strategies through promoter and codon optimization, "humanization” of glycosylation process, inhibition of gene silencing and protease activity, and also summarize the application of plant-derived protein products, which aim to provide a theoretical and application basis for the development of plant bioreactors. © 2023, China Biotechnology Press. All rights reserved.

Stability and Bifurcation Analysis of the Caputo Fractional-Order Asymptomatic COVID-19 Model with Multiple Time-Delays

Throughout the last few decades, fractional-order models have been used in many fields of science and engineering, applied mathematics, and biotechnology. Fractional-order differential equations are beneficial for incorporating memory and hereditary properties into systems. Our paper proposes an asymptomatic COVID-19 model with three delay terms τ1,τ2,τ3 and fractional-order α. Multiple constant time delays are included in the model to account for the latency of infection in a vector. We study the necessary and sufficient criteria for stability of steady states and Hopf bifurcations based on the three constant time-delays, τ1, τ2, and τ3. Hopf bifurcation occurs in the addressed model at the estimated bifurcation points τ10, τ20, τ30, and τ10*. The numerical simulations fit to real observations proving the effectiveness of the theoretical results. Fractional-order and time-delays successfully enhance the dynamics and strengthen the stability condition of the asymptomatic COVID-19 model. © 2023 World Scientific Publishing Company.

Stability analysis of a fractional-order SEIR epidemic model with general incidence rate and time delay

In this paper, we investigate the qualitative behavior of a class of fractional SEIR epidemic models with a more general incidence rate function and time delay to incorporate latent infected individuals. We first prove positivity and boundedness of solutions of the system. The basic reproduction number (Formula presented.) of the model is computed using the method of next generation matrix, and we prove that if (Formula presented.), the healthy equilibrium is locally asymptotically stable, and when (Formula presented.), the system admits a unique endemic equilibrium which is locally asymptotically stable. Moreover, using a suitable Lyapunov function and some results about the theory of stability of differential equations of delayed fractional-order type, we give a complete study of global stability for both healthy and endemic steady states. The model is used to describe the COVID-19 outbreak in Algeria at its beginning in February 2020. A numerical scheme, based on Adams–Bashforth–Moulton method, is used to run the numerical simulations and shows that the number of new infected individuals will peak around late July 2020. Further, numerical simulations show that around 90% of the population in Algeria will be infected. Compared with the WHO data, our results are much more close to real data. Our model with fractional derivative and delay can then better fit the data of Algeria at the beginning of infection and before the lock and isolation measures. The model we propose is a generalization of several SEIR other models with fractional derivative and delay in literature. © 2023 John Wiley & Sons, Ltd.

A Single-Administration Microneedle Skin Patch for Multi-Burst Release of Vaccine against SARS-CoV-2.

The necessity for multiple injections and cold-chain storage has contributed to suboptimal vaccine utilization, especially in pandemic situations. Thermally-stable and single-administration vaccines hold a great potential to revolutionize the global immunization process. Here, a new approach to thermally stabilize protein-based antigens is presented and a new high-throughput antigen-loading process is devised to create a single-administration, pulsatile-release microneedle (MN) patch which can deliver a recombinant SARS-CoV-2 S1-RBD protein-a model for the COVID-19 vaccine. Nearly 100% of the protein antigen could be stabilized at temperatures up to 100 °C for at least 1 h and at an average human body temperature (37 °C) for up to 4 months. Arrays of the stabilized S1-RBD formulations can be loaded into the MN shells via a single-alignment assembly step. The fabricated MNs are administered at a single time into the skin of rats and induce antibody response which could neutralize authentic SARS-CoV-2 viruses, providing similar immunogenic effect to that induced by multiple bolus injections of the same antigen stored in conventional cold-chain conditions. The MN system presented herein could offer the key solution to global immunization campaigns by avoiding low patient compliance, the requirement for cold-chain storage, and the need for multiple booster injections.

Pathway through which COVID-19 exacerbates energy poverty and proposed relief measures.

Increased residential energy consumption and reduced income caused by the lockdown measures invoked to combat the COVID-19 pandemic have deepened energy poverty, particularly in vulnerable communities. In this context, the pathway through which COVID-19 impacts energy poverty is constructed, and six relief measures are proposed: consistent financing of energy suppliers and consumers, developing various forms of socio-economic aids, leveraging fiscal stimuli to promote renewable energy transition, identifying vulnerable populations to improve policy effectiveness, designing equitable resource allocation mechanisms, and rethinking socio-economic transition in the post-pandemic era.

A simplified protocol for Agrobacterium-mediated transformation of cell suspension cultures of the model species Medicago truncatula A17.

This manuscript describes a unique protocol for the rapid transformation of Medicago truncatula A17 cell suspension cultures mediated by Agrobacterium tumefaciens. Medicago cells were collected on day 7 of the growth curve, which corresponded to the beginning of the exponential phase. They were then co-cultured with Agrobacterium for 3 days before being spread onto a petri dish with appropriate antibiotic selection. The Receptor Binding Domain of the Spike protein of SARS-CoV-2 was used as a model to develop this protocol. The presence of the transgene was assessed using PCR, and the integrity of the product was evaluated by SDS-PAGE and Western-blotting.

Model analysis of smart supply chain finance of platform-based enterprises under government supervision.

The COVID-19 pandemic has made it more difficult and expensive for medium-sized enterprises (SMEs) to finance. In this context, relying on the network platform, smart supply chain finance effectively solves financing problems for small and SMEs. However, in the development of smart supply chain finance, there are still some problems such as unstable willingness of SMEs to participate in financing, difficulty in determining the optimal development mode of platform-based core enterprises and lack of appropriate regulatory measures. Based on whether the network platform can use its own capitals for lending, this study introduces two smart supply chain financial models (the dominant and cooperation models of platform-based core enterprises) to solve the above problems. In this study, we construct two evolutionary game models: the tripartite model, including government, platform-based core enterprises, and SMEs, and the quadrilateral model, including government, financial institutions, platform-based core enterprises, and SMEs. This study presents the evolution and stability strategies of each participant under different modes. In addition, we discuss the willingness of platforms to choose different modes and corresponding government supervision measures. This study offers several important conclusions. (1) Core enterprises that do not have the conditions to build a highly intelligent platform choose the cooperation model; otherwise, they will preferentially choose the dominant mode. (2) Under the dominant mode, the stable development of smart supply chain finance must rely on strict government supervision. (3) By adjusting the scope of tax rates and subsidies, the government can control the trend of mutual transformation of the two modes, so that the dominant mode and the cooperative mode can develop in a balanced way in the market.