SARS-CoV-2 N protein-induced Dicer, XPO5, SRSF3, and hnRNPA3 downregulation causes pneumonia (preprint)

Age is a major risk factor for coronavirus disease (COVID-19)-associated severe pneumonia and mortality; however, the underlying mechanism remains unclear. Herein, we investigated whether age-related deregulation of RNAi components and RNA splicing factors affects COVID-19 severity. Decreased expression of RNAi components (Dicer and XPO5) and splicing factors (SRSF3 and hnRNPA3) correlated with increased severity of COVID-19 and SARS-CoV-2 nucleocapsid (N) protein-induced pneumonia. N protein induced autophagic degradation of Dicer, XPO5, SRSF3, and hnRNPA3, repressing miRNA biogenesis and RNA splicing and inducing DNA damage, proteotoxic stress, and pneumonia. Dicer, XPO5, SRSF3, and hnRNPA3 were downregulated with age in mouse lung tissues. Older mice experienced more severe N protein-induced pneumonia than younger mice. However, treatment with a poly(ADP-ribose) polymerase inhibitor (PJ34) or aromatase inhibitor (anastrozole) relieved N protein-induced pneumonia by restoring Dicer, XPO5, SRSF3, and hnRNPA3 expression. These findings will aid in developing improved treatments for SARS-CoV-2-associated pneumonia.

Optimizing plastics recycling networks

Plastic pollution is a serious sustainability issue facing the global community. Fragments of macroplastics and microplastics pollute terrestrial and aquatic ecosystems, while nanoplastics can also degrade air quality. The recent COVID-19 pandemic also exacerbated the problem. Large-scale commercial use of plastics recycling technologies is hindered by various socio-economic barriers. In particular, cross-contamination of mixed plastic streams is prevalent due to imperfect waste segregation. The concept of Plastics Recycling Networks is introduced to facilitate planning of reverse supply chains using optimization models. In this work, basic Linear Programming and Mixed-Integer Linear Programming models are developed for matching sources of waste plastic with plastic recycling plants within Plastics Recycling Networks. These models allocate streams while considering the ability of recycling plants to tolerate contaminants. Two illustrative case studies are analyzed to demonstrate the effectiveness of the models, and policy implications for mitigation of plastic pollution are discussed. These models enable planning of networks with some tolerance for contaminants in plastic waste, and can be the basis for developing new variants to handle additional real world aspects.

Knowledge, attitude, and practices on COVID-19 prevention and diagnosis among medical workers in the radiology department: A multicenter cross-sectional study in China

Objective The aim of this study was to investigate the knowledge, attitude, and practice (KAP) of medical workers in the radiology department toward the prevention and diagnosis of COVID-19. Methods This multicenter cross-sectional study was conducted among medical workers in the radiology department of 17 hospitals between March and June 2022. Results A total of 324 medical workers were enrolled. The mean knowledge scores were 15.3 ± 3.4 (out of 23), attitude scores were 31.1 ± 5.6 (range 8–40), and practice scores were 35.1 ± 4.4 (range 8–40). Positive attitudes (OR = 1.235, 95% CI: 1.162–1.311, P < 0.001) and aged 41–50 years were independently associated with higher practice scores. Those with the better practice were more likely to be older (OR = 2.603, 95% CI: 1.242–5.452, P = 0.011), nurses (OR = 2.274, 95% CI: 1.210–4.272, P = 0.011) and with junior/intermediary/vice-senior title (OR = 2.326, 95% CI: 1.030–5.255, P = 0.042;OR = 2.847, 95% CI: 1.226–6.606, P = 0.015;OR = 4.547, 95% CI: 1.806–11.452, P = 0.001, respectively). Subgroup analysis revealed significant differences in knowledge between technicians and physicians and nurses and between staff working in tertiary hospitals and non-tertiary hospitals. Knowledge is positively correlated with attitude (β = 0.54, P < 0.001), and attitude is positively correlated with practice (β = 0.37, P < 0.001). Attitudes significantly mediated the association between knowledge and practice (β = 0.119, P < 0.001). Conclusion The radiology medical workers showed moderate knowledge but good attitudes and practices of prevention and diagnosis of COVID-19. Attitudes were found to be positively associated with better practices of prevention and diagnosis of COVID-19. Attitudes significantly mediated the association between knowledge and practice.

Knowledge, attitude, and practices on COVID-19 prevention and diagnosis among medical workers in the radiology department: A multicenter cross-sectional study in China.

Objective: The aim of this study was to investigate the knowledge, attitude, and practice (KAP) of medical workers in the radiology department toward the prevention and diagnosis of COVID-19. Methods: This multicenter cross-sectional study was conducted among medical workers in the radiology department of 17 hospitals between March and June 2022. Results: A total of 324 medical workers were enrolled. The mean knowledge scores were 15.3 ± 3.4 (out of 23), attitude scores were 31.1 ± 5.6 (range 8-40), and practice scores were 35.1 ± 4.4 (range 8-40). Positive attitudes (OR = 1.235, 95% CI: 1.162-1.311, P < 0.001) and aged 41-50 years were independently associated with higher practice scores. Those with the better practice were more likely to be older (OR = 2.603, 95% CI: 1.242-5.452, P = 0.011), nurses (OR = 2.274, 95% CI: 1.210-4.272, P = 0.011) and with junior/intermediary/vice-senior title (OR = 2.326, 95% CI: 1.030-5.255, P = 0.042; OR = 2.847, 95% CI: 1.226-6.606, P = 0.015; OR = 4.547, 95% CI: 1.806-11.452, P = 0.001, respectively). Subgroup analysis revealed significant differences in knowledge between technicians and physicians and nurses and between staff working in tertiary hospitals and non-tertiary hospitals. Knowledge is positively correlated with attitude (ß = 0.54, P < 0.001), and attitude is positively correlated with practice (ß = 0.37, P < 0.001). Attitudes significantly mediated the association between knowledge and practice (ß = 0.119, P < 0.001). Conclusion: The radiology medical workers showed moderate knowledge but good attitudes and practices of prevention and diagnosis of COVID-19. Attitudes were found to be positively associated with better practices of prevention and diagnosis of COVID-19. Attitudes significantly mediated the association between knowledge and practice.

Analysis of students' positive emotions around the green space in the university campus during the COVID-19 pandemic in China

Green space around the university campus is of paramount importance for emotional and psychological restorations in students. Positive emotions in students can be aroused when immersed in green space and naturalness. However, to what extent can perceived naturalness influence students' positive emotion remains unclear, especially in the context of COVID-19 countermeasures. This study, therefore, attempts to investigate in-depth the nature and strength of the relationships between students' positive emotion and their perceived naturalness, place attachment, and landscape preference, which are potentially varying across universities in different social and environmental contexts and different restrictions policies regarding the COVID-19 pandemic. A course of questionnaire-based surveys was administered on two university campuses in Heilongjiang and Hunan Provinces, China, resulting in 474 effective samples. Structural equation modeling was used to explore the hypothetical conceptual framework of latent variables and the indicators. The findings indicate that the higher students' perceived naturalness results in greater positive emotion. Students' perceived naturalness in green spaces of campus has a positive effect on their place attachment and landscape preference. Moreover, the difference between mediate effects of place attachment and landscape preference were addressed, which verifies the contextual influences.

Edge Computing and Lightning Network Empowered Secure Food Supply Management

The recent COVID-19 pandemic has highlighted the importance of food safety and supply chain governance. In other words, we need to ensure traceability along the supply chain and support high-frequency transactions, effective data collections, etc. Thus, we posit the potential of using a lightning network, which is a decentralized traceable paradigm for achieving high-frequency transactions in blockchain-based systems. In addition, we also utilize edge computing to help facilitate data collection. However, a key challenge in securing food supplies is determining the optimal global transaction path in the lightning network while achieving efficiency and meeting the dynamic nature of food supply management. Thus, we propose a blockchain-edge scheme that utilizes our proposed dynamic programming to produce optimal solutions for selecting global transaction paths. Specifically, our scheme optimizes routing fees under existing constraints (e.g., transmission cost, computing resource consumption, and lightning network balance). The findings from our evaluations demonstrate the utility of our proposed approach in facilitating food safety management.

SrTiO3 /CuNi-Heterostructure-Based Thermopile for Sensitive Human Radiation Detection and Noncontact Human-Machine Interaction.

Noncontact interactive technology provides an intelligent solution to mitigate public health risks from cross-infection in the era of COVID-19. The utilization of human radiation as a stimulus source is conducive to the implementation of low-power, robust noncontact human-machine interaction. However, the low radiation intensity emitted by humans puts forward a high demand for photodetection performance. Here, a SrTiO3-x /CuNi-heterostructure-based thermopile is constructed, which features the combination of high thermoelectric performance and near-unity long-wave infrared absorption, to realize the self-powered detection of human radiation. The response level of this thermopile to human radiation is orders of magnitude higher than those of low-dimensional-materials-based photothermoelectric detectors and even commercial thermopiles. Furthermore, a touchless input device based on the thermopile array is developed, which can recognize hand gestures, numbers, and letters in real-time. This work offers a reliable strategy to integrate the spontaneous human radiation into noncontact human-machine interaction systems.

The Impact of Blockchain Application on the Qualification Rate and Circulation Efficiency of Agricultural Products: A Simulation Analysis with Agent-Based Modelling.

In the context of COVID-19, the circulation of agricultural products is increasingly important for the nutrition and health of people. With the changing needs of society and the advancement of technology, the agricultural product circulation system needs to undergo corresponding changes to adapt to the modern fast-paced social system. Blockchain technology couples with the circulation of agricultural products, as its technical features, such as immutability and a distributed ledger database, ensures the speed and stability of the key information circulation process of agricultural products. The research goal of this paper was to clarify the influence of blockchain technology on the qualification rate and circulation efficiency for agricultural products. Based on the main characteristics of blockchain technology and a summary of domestic and foreign theoretical research, this paper simulated the impacts of blockchain technology on the agricultural product circulation system. The results revealed that blockchain technology can improve the qualification rate of agricultural products and thereby ensure their quality and safety. The introduction of blockchain increased the qualification rate by nearly 30%. Moreover, blockchain technology significantly enhanced the efficiency of the agricultural product circulation system, thereby greatly promoting economic benefits. The introduction of blockchain increased circulation efficiency by nearly 15%. Finally, the introduction of blockchain technology can effectively promote the governance level and reduce the supervision costs of the agricultural product circulation system. Through simulation analysis, we found that blockchain technology has a positive impact on both the qualification rate and circulation efficiency for agricultural products. These findings enrich research into the application of blockchain technology in the management and circulation of modern agricultural products.

Minimize food loss and waste to prevent crises

The article reports that Russia's invasion of Ukraine and the associated economic and trade consequences have added to the global food security disruptions caused by the COVID-19 pandemic and invasion has led to increased demand for these important sources of fertilizer macronutrients.

Developing a Health-Spatial Indicator System for a Healthy City in Small and Midsized Cities.

A recent examination of the significant role of public health has prompted calls to re-investigate how the urban environment affects public health. A vital part of the solution includes Healthy City initiatives that have been the subject of extensive policies, implications, and practices globally. However, the existing literature mainly focuses on big cities and metropolitan areas, while investigations into small and midsized cities (SMCs) are lacking, and thus reflect the underlying issues of health inequity. This study develops an indicator system for evaluating Healthy City initiatives in SMCs, linking urban design and public health, supported by the analyzed opinions from experts collected using both questionnaires and interviews. The indicator system includes six primary dimensions and 37 variables: urban form and transportation (UFT); health-friendly service (HFS); environmental quality and governance (EQG); community and facility (CF); green and open space (GOS); and ecological construction and biodiversity (ECB). A fuzzy synthetic evaluation technique was used to assess the relative importance of factors, emphasizing the importance of UFT, HFS, and EQG, with importance indexes of 0.175, 0.174, and 0.174, respectively. This indicator system is helpful for SMCs seeking to construct a Healthy City in the future, and is based on urban design and governance inputs and for enhancing the Healthy City knowledge base of cities of varied scales.

A stochastic programming model for emergency supplies pre-positioning, transshipment and procurement in a regional healthcare coalition.

A regional healthcare coalition enables its member hospitals to conduct an integrated emergency supply management, which is seldom addressed in the existing literature. In this work, we propose a two-stage stochastic emergency supply planning model to facilitate cooperation and coordination in a regional healthcare coalition. Our model integrates pre-disaster emergency supplies pre-positioning and post-disaster emergency supplies transshipment and procurement and considers two planning goals, i.e., minimizing the expected total cost and the maximum supply shortage rate. With some comparison models and a case study on the West China Hospital coalition of Sichuan Province, China, under the background of the COVID-19 epidemic, we demonstrate the effectiveness and benefits of our model and obtain various managerial insights and policy suggestions for practice. We highlight the importance of conducting integrated management of emergency supplies pre-positioning, transshipment and procurement in the regional healthcare coalition for better preparation and responding to future potential disasters.

Elastase Inhibitor Cyclotheonellazole A: Total Synthesis and In Vivo Biological Evaluation for Acute Lung Injury.

Acute lung injury/acute respiratory distress syndrome (ALI/ARDS) is one of the most common complications in COVID-19. Elastase has been recognized as an important target to prevent ALI/ARDS in the patient of COVID-19. Cyclotheonellazole A (CTL-A) is a natural macrocyclic peptide reported to be a potent elastase inhibitor. Herein, we completed the first total synthesis of CTL-A in 24 linear steps. The key reactions include three-component MAC reactions and two late-stage oxidations. We also provided seven CTL-A analogues and elucidated preliminary structure-activity relationships. The in vivo ALI mouse model further suggested that CTL-A alleviated acute lung injury with reductions in lung edema and pathological deterioration, which is better than sivelestat, one approved elastase inhibitor. The activity of CTL-A against elastase, along with its cellular safety and well-established synthetic route, warrants further investigation of CTL-A as a candidate against COVID-19 pathogeneses.

Systematic investigation of cytokine signaling activity at the tissue and single-cell levels.

Cytokines are critical for intercellular communication in human health and disease, but the investigation of cytokine signaling activity has remained challenging due to the short half-lives of cytokines and the complexity/redundancy of cytokine functions. To address these challenges, we developed the Cytokine Signaling Analyzer (CytoSig; https://cytosig.ccr.cancer.gov/ ), providing both a database of target genes modulated by cytokines and a predictive model of cytokine signaling cascades from transcriptomic profiles. We collected 20,591 transcriptome profiles for human cytokine, chemokine and growth factor responses. This atlas of transcriptional patterns induced by cytokines enabled the reliable prediction of signaling activities in distinct cell populations in infectious diseases, chronic inflammation and cancer using bulk and single-cell transcriptomic data. CytoSig revealed previously unidentified roles of many cytokines, such as BMP6 as an anti-inflammatory factor, and identified candidate therapeutic targets in human inflammatory diseases, such as CXCL8 for severe coronavirus disease 2019.

COVID-19 pandemics Stage II - Energy and environmental impacts of vaccination.

The COVID-19 pandemic developed the severest public health event in recent history. The first stage for defence has already been documented. This paper moves forward to contribute to the second stage for offensive by assessing the energy and environmental impacts related to vaccination. The vaccination campaign is a multidisciplinary topic incorporating policies, population behaviour, planning, manufacturing, materials supporting, cold-chain logistics and waste treatment. The vaccination for pandemic control in the current phase is prioritised over other decisions, including energy and environmental issues. This study documents that vaccination should be implemented in maximum sustainable ways. The energy and related emissions of a single vaccination are not massive; however, the vast numbers related to the worldwide production, logistics, disinfection, implementation and waste treatment are reaching significant figures. The preliminary assessment indicates that the energy is at the scale of ~1.08 × 1010 kWh and related emissions of ~5.13 × 1012 gCO2eq when embedding for the envisaged 1.56 × 1010 vaccine doses. The cold supply chain is estimated to constitute 69.8% of energy consumption of the vaccination life cycle, with an interval of 26-99% depending on haul distance. A sustainable supply chain model that responds to an emergency arrangement, considering equality as well, should be emphasised to mitigate vaccination's environmental footprint. This effort plays a critical role in preparing for future pandemics, both environmentally and socially. Research in exploring sustainable single-use or reusable materials is also suggested to be a part of the plans. Diversified options could offer higher flexibility in mitigating environmental footprint even during the emergency and minimise the potential impact of material disruption or dependency.

Energy, environmental, economic and social equity (4E) pressures of COVID-19 vaccination mismanagement: A global perspective.

Vaccination now offers a way to resolve the COVID-19 pandemic. However, it is critical to recognise the full energy, environmental, economic and social equity (4E) impacts of the vaccination life cycle. The full 4E impacts include the design and trials, order management, material preparation, manufacturing, cold chain logistics, low-temperature storage, crowd management and end-of-life waste management. A life cycle perspective is necessary for sustainable vaccination management because a prolonged immunisation campaign for COVID-19 is likely. The impacts are geographically dispersed across sectors and regions, creating real and virtual 4E footprints that occur at different timescales. Decision-makers in industry and governments have to act, unify, resolve, and work together to implement more sustainable COVID-19 vaccination management globally and locally to minimise the 4E footprints. Potential practices include using renewable energy in production, storage, transportation and waste treatment, using better product design for packaging, using the Internet of Things (IoT) and big data analytics for better logistics, using real-time database management for better tracking of deliveries and public vaccination programmes, and using coordination platforms for more equitable vaccine access. These practices raise global challenges but suggest solutions with a 4E perspective, which could mitigate the impacts of global vaccination campaigns and prepare sustainably for future pandemics and global warming.

Toward a Coronavirus Knowledge Graph.

This study builds a coronavirus knowledge graph (KG) by merging two information sources. The first source is Analytical Graph (AG), which integrates more than 20 different public datasets related to drug discovery. The second source is CORD-19, a collection of published scientific articles related to COVID-19. We combined both chemo genomic entities in AG with entities extracted from CORD-19 to expand knowledge in the COVID-19 domain. Before populating KG with those entities, we perform entity disambiguation on CORD-19 collections using Wikidata. Our newly built KG contains at least 21,700 genes, 2500 diseases, 94,000 phenotypes, and other biological entities (e.g., compound, species, and cell lines). We define 27 relationship types and use them to label each edge in our KG. This research presents two cases to evaluate the KG's usability: analyzing a subgraph (ego-centered network) from the angiotensin-converting enzyme (ACE) and revealing paths between biological entities (hydroxychloroquine and IL-6 receptor; chloroquine and STAT1). The ego-centered network captured information related to COVID-19. We also found significant COVID-19-related information in top-ranked paths with a depth of three based on our path evaluation.

More Is Not Enough: A Deeper Understanding of the COVID-19 Impacts on Healthcare, Energy and Environment Is Crucial.

The coronavirus disease 2019 (COVID-19) pandemic has magnified the insufficient readiness of humans in dealing with such an unexpected occurrence. During the pandemic, sustainable development goals have been hindered severely. Various observations and lessons have been highlighted to emphasise local impacts on a single region or single sector, whilst the holistic and coupling impacts are rarely investigated. This study overviews the structural changes and spatial heterogeneities of changes in healthcare, energy and environment, and offers perspectives for the in-depth understanding of the COVID-19 impacts on the three sectors, in particular the cross-sections of them. Practical observations are summarised through the broad overview. A novel concept of the healthcare-energy-environment nexus under climate change constraints is proposed and discussed, to illustrate the relationships amongst the three sectors and further analyse the dynamics of the attention to healthcare, energy and environment in view of decision-makers. The society is still on the way to understanding the impacts of the whole episode of COVID-19 on healthcare, energy, environment and beyond. The raised nexus thinking could contribute to understanding the complicated COVID-19 impacts and guiding sustainable future planning.

Impacts of COVID-19 on energy demand and consumption: Challenges, lessons and emerging opportunities.

COVID-19 has caused great challenges to the energy industry. Potential new practices and social forms being facilitated by the pandemics are having impacts on energy demand and consumption. Spatial and temporal heterogeneities of impacts appear gradually due to the dynamics of pandemics and mitigation measures. This paper overviews the impacts and challenges of COVID-19 pandemics on energy demand and consumption and highlights energy-related lessons and emerging opportunities. The discussion on energy-related issues is divided into four main sections: emergency situation and its impacts, environmental impacts and stabilising energy demand, recovering energy demand, and lessons and emerging opportunities. The changes in energy requirements are compared and analysed from multiple perspectives according to available data and information. In general, although the overall energy demand declines, the spatial and temporal variations are complicated. The energy intensity has presented apparent changes, the extra energy for COVID-19 fighting is non-negligible for stabilising energy demand, and the energy recovery in different regions presents significant differences. A crucial issue has been to allocate and find energy-related emerging opportunities for the post pandemics. This study could offer a direction in opening new avenues for increasing energy efficiency and promoting energy saving.