DRAVP: A Comprehensive Database of Antiviral Peptides and Proteins.

Viruses with rapid replication and easy mutation can become resistant to antiviral drug treatment. With novel viral infections emerging, such as the recent COVID-19 pandemic, novel antiviral therapies are urgently needed. Antiviral proteins, such as interferon, have been used for treating chronic hepatitis C infections for decades. Natural-origin antimicrobial peptides, such as defensins, have also been identified as possessing antiviral activities, including direct antiviral effects and the ability to induce indirect immune responses to viruses. To promote the development of antiviral drugs, we constructed a data repository of antiviral peptides and proteins (DRAVP). The database provides general information, antiviral activity, structure information, physicochemical information, and literature information for peptides and proteins. Because most of the proteins and peptides lack experimentally determined structures, AlphaFold was used to predict each antiviral peptide's structure. A free website for users (http://dravp.cpu-bioinfor.org/, accessed on 30 August 2022) was constructed to facilitate data retrieval and sequence analysis. Additionally, all the data can be accessed from the web interface. The DRAVP database aims to be a useful resource for developing antiviral drugs.

One-Step Formation of Targeted Liposomes in a Versatile Microfluidic Mixing Device.

Targeted liposomes, as a promising carrier, have received tremendous attention in COVID-19 vaccines, molecular imaging, and cancer treatment, due to their enhanced cellular uptake and payload accumulation at target sites. However, the conventional methods for preparing targeted liposomes still suffer from limitations, including complex operation, time-consuming, and poor reproducibility. Herein, a facile and scalable strategy is developed for one-step construction of targeted liposomes using a versatile microfluidic mixing device (MMD). The engineered MMD provides an advanced synthesis platform for multifunctional liposome with high production rate and controllability. To validate the method, a programmed death-ligand 1 (PD-L1)-targeting aptamer modified indocyanine green (ICG)-liposome (Apt-ICG@Lip) is successfully constructed via the MMD. ICG and the PD-L1-targeting aptamer are used as model drug and targeting moiety, respectively. The Apt-ICG@Lip has high encapsulation efficiency (89.9 ± 1.4%) and small mean diameter (129.16 ± 5.48 nm). In vivo studies (PD-L1-expressing tumor models) show that Apt-ICG@Lip can realize PD-L1 targeted photoacoustic imaging, fluorescence imaging, and photothermal therapy. To verify the versatility of this approach, various targeted liposomes with different functions are further prepared and investigated. These experimental results demonstrate that this method is concise, efficient, and scalable to prepare multifunctional targeted liposomal nanoplatforms for molecular imaging and disease theranostics.

Impacts of the COVID-19 disruption on the language and literacy development of monolingual and heritage bilingual children in the United States.

Children who speak one language at home and a different language at school may be at higher risk of falling behind in their academic achievement when schooling is disrupted. The present study examined the effects of COVID-19-related school disruptions on English language and literacy development among monolingual and bilingual children in the US. All children attended English-only schools that implemented varied forms of virtual and hybrid schooling during the pandemic. Pre-COVID-19 and during-COVID-19 examinations were conducted with 237 children (M(SD) age = 7.78 (1.54) at Time 1) from relatively high SES homes, including 95 monolinguals, 75 Spanish-English and 67 Chinese-English bilinguals. The findings revealed different impacts of COVID-19 school disruptions on the present bilingual and monolingual participants. Specifically, between Time 1 and Time 2, monolingual children made age-appropriate improvements in all literacy measurements. Relative to monolinguals, both bilingual groups showed greater gains in vocabulary but lower gains in reading comprehension. Moreover, across groups, children's independent reading practices during COVID-19 were positively associated with children's literacy growth during the pandemic-related schooling disruptions. Taken together, these findings inform theoretical perspectives on learning to read in linguistically diverse children experiencing COVID-19-related schooling disruptions. Supplementary Information: The online version contains supplementary material available at 10.1007/s11145-022-10388-x.

Systematic characterization of components of Makyo-kanseki-to granule and serum metabolomics for exploring its protective mechanism against acute lung injury in lipopolysaccharide-induced rats.

Makyo-kanseki-to has been used for the treatment of pneumonia, becoming a basic formula for coronavirus disease 2019. However, the chemical profile of Makyo-kanseki-to granule and its possible mechanism against acute lung injury from terminal metabolic regulation have been unclear. The aim of this study was to characterize the constituents in Makyo-kanseki-to granule and reveal the potential related mechanism of Makyo-kanseki-to granule treatment for acute lung injury using a rat model of lipopolysaccharide-induced acute lung injury. Totally, 78 constituents were characterized based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Makyo-kanseki-to granule could alleviate acute lung injury through modulating rectal temperature, pulmonary edema, histopathology, and processes of inflammatory and oxidative stress. Twenty-two potential biomarkers in acute lung injury rats were identified by metabolomics based on ultra-performance liquid chromatography coupled with quadrupole exactive high-field mass spectrometry. They were mainly involved in amino acids and glycerophospholipid metabolism, which were regulated by Makyo-kanseki-to granule. The present results not only increase the understanding of the chemical profile and molecular mechanism of Makyo-kanseki-to granule mediated protection against acute lung injury but also provide an experimental basis and new ideas for further development and clinical application of Makyo-kanseki-to granule.

Efficacy and safety of chinese herbal medicine for treating mild or moderate COVID-19: A systematic review and meta-analysis of randomized controlled trials and observational studies.

Background: The coronavirus disease 2019 (COVID-19) is still a pandemic globally, about 80% of patients infected with COVID-19 were mild and moderate. Chinese herbal medicine (CHM) has played a positive role in the treatment of COVID-19, with a certain number of primary studies focused on CHM in managing COVID-19 published. This study aims to systematically review the currently published randomized controlled trials (RCTs) and observational studies (OBs), and summarize the effectiveness and safety of CHM in the treatment of mild/moderate COVID-19 patients. Methods: We searched 9 databases up to 19 March 2022. Pairs of reviewers independently screened literature, extracted data and assessed risk of bias. For overall effect, we calculated the absolute risk difference (ARD) of weighted averages of different estimates, and certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) system. Results: We included 35 RCTs and 24 OBs enrolling 16,580 mild/moderate patients. The certainty of evidence was very low to low. Compared with usual supportive treatments, most effect estimates of CHM treatments were consistent in direction. CHMs presented significant benefits in reducing rate of conversion to severe cases (ARD = 99 less per 1000 patients in RCTs and 131 less per 1000 patients in OBs, baseline risk: 16.52%) and mortality (ARD = 3 less per 1000 patients in RCTs and OBs, baseline risk: 0.40%); shortening time to symptom resolution (3.35 days in RCTs and 2.94 days in OBs), length of hospital stay (2.36 days in RCTs and 2.12 days in OBs) and time to viral clearance (2.64 days in RCTs and 4.46 days in OBs); increasing rate of nucleic acid conversion (ARD = 73 more per 1000 patients in OBs, baseline risk: 16.30%). No serious adverse reactions were found and the differences between CHM and usual supportive care were insignificant. Conclusion: Encouraging evidence showed that CHMs were beneficial in treating mild or moderate patients. CHMs have been proved to possess a safety profile that is comparable to that of usual supportive treatment alone. More rigorously designed clinical trials and mechanism studies are still warranted to further confirm the present findings.

The Characteristics of Light-Duty Passenger Vehicle Mileage and Impact Analysis in China from a Big Data Perspective

Vehicle mileage is one of the key parameters for accurately evaluating vehicle emissions and energy consumption. With the support of the national annual vehicle emission inspection networked platform in China, this study used big data methods to analyze the activity level characteristics of the light-duty passenger vehicle fleet with the highest ownership proportion. We found that the annual mileage of vehicles does not decay significantly with the increase in vehicle age, and the mileage of vehicles is relatively low in the first few years due to the run-in period, among other reasons. This study indicated that the average mileage of the private passenger car fleet is 10,300 km/yr and that of the taxi fleet was 80,000 km/yr in China in 2019, and the annual mileage dropped by 22% in 2020 due to the pandemic. Based on the vehicle mileage characteristics, the emission inventory of major pollutants from light-duty passenger vehicles in China for 2010–2020 was able to be updated, which will provide important data support for more accurate environmental and climate benefit assessments in the future. [ FROM AUTHOR]

Mobile Phone-Based Population Flow Data for the COVID-19 Outbreak in Mainland China

Background Human migration is one of the driving forces for amplifying localized infectious disease outbreaks into widespread epidemics. During the outbreak of COVID-19 in China, the travels of the population from Wuhan have furthered the spread of the virus as the period coincided with the world's largest population movement to celebrate the Chinese New Year. Methods We have collected and made public an anonymous and aggregated mobility dataset extracted from mobile phones at the national level, describing the outflows of population travel from Wuhan. We evaluated the correlation between population movements and the virus spread by the dates when the number of diagnosed cases was documented. Results From Jan 1 to Jan 22 of 2020, a total of 20.2 million movements of at-risk population occurred from Wuhan to other regions in China. A large proportion of these movements occurred within Hubei province (84.5%), and a substantial increase of travels was observed even before the beginning of the official Chinese Spring Festival Travel. The outbound flows from Wuhan before the lockdown were found strongly correlated with the number of diagnosed cases in the destination cities (log-transformed). Conclusions The regions with the highest volume of receiving at-risk populations were identified. The movements of the at-risk population were strongly associated with the virus spread. These results together with province-by-province reports have been provided to governmental authorities to aid policy decisions at both the state and provincial levels. We believe that the effort in making this data available is extremely important for COVID-19 modelling and prediction.

Predicting willingness to donate blood based on machine learning: two blood donor recruitments during COVID-19 outbreaks.

Machine learning methods are a novel way to predict and rank donors' willingness to donate blood and to achieve precision recruitment, which can improve the recruitment efficiency and meet the challenge of blood shortage. We collected information about experienced blood donors via short message service (SMS) recruitment and developed 7 machine learning-based recruitment models using PyCharm-Python Environment and 13 features which were described as a method for ranking and predicting donors' intentions to donate blood with a floating number between 0 and 1. Performance of the prediction models was assessed by the Area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and F1 score in the full dataset, and by the accuracy in the four sub-datasets. The developed models were applied to prospective validations of recruiting experienced blood donors during two COVID-19 pandemics, while the routine method was used as a control. Overall, a total of 95,476 recruitments via SMS and their donation results were enrolled in our modelling study. The strongest predictor features for the donation of experienced donors were blood donation interval, age, and donation frequency. Among the seven baseline models, the eXtreme Gradient Boosting (XGBoost) and Support vector machine models (SVM) achieved the best performance: mean (95%CI) with the highest AUC: 0.809 (0.806-0.811), accuracy: 0.815 (0.812-0.818), precision: 0.840 (0.835-0.845), and F1 score of XGBoost: 0.843 (0.840-0.845) and recall of SVM: 0.991 (0.988-0.994). The hit rate of the XGBoost model alone and the combined XGBoost and SVM models were 1.25 and 1.80 times higher than that of the conventional method as a control in 2 recruitments respectively, and the hit rate of the high willingness to donate group was 1.96 times higher than that of the low willingness to donate group. Our results suggested that the machine learning models could predict and determine the experienced donors with a strong willingness to donate blood by a ranking score based on personalized donation data and demographical details, significantly improve the recruitment rate of blood donors and help blood agencies to maintain the blood supply in emergencies.

Efficacy and safety of chinese herbal medicine for treating mild or moderate COVID-19: A systematic review and meta-analysis of randomized controlled trials and observational studies

Background: The coronavirus disease 2019 (COVID-19) is still a pandemic globally, about 80% of patients infected with COVID-19 were mild and moderate. Chinese herbal medicine (CHM) has played a positive role in the treatment of COVID-19, with a certain number of primary studies focused on CHM in managing COVID-19 published. This study aims to systematically review the currently published randomized controlled trials (RCTs) and observational studies (OBs), and summarize the effectiveness and safety of CHM in the treatment of mild/moderate COVID-19 patients. Methods: We searched 9 databases up to 19 March 2022. Pairs of reviewers independently screened literature, extracted data and assessed risk of bias. For overall effect, we calculated the absolute risk difference (ARD) of weighted averages of different estimates, and certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) system. Results: We included 35 RCTs and 24 OBs enrolling 16,580 mild/moderate patients. The certainty of evidence was very low to low. Compared with usual supportive treatments, most effect estimates of CHM treatments were consistent in direction. CHMs presented significant benefits in reducing rate of conversion to severe cases (ARD = 99 less per 1000 patients in RCTs and 131 less per 1000 patients in OBs, baseline risk: 16.52%) and mortality (ARD = 3 less per 1000 patients in RCTs and OBs, baseline risk: 0.40%);shortening time to symptom resolution (3.35 days in RCTs and 2.94 days in OBs), length of hospital stay (2.36 days in RCTs and 2.12 days in OBs) and time to viral clearance (2.64 days in RCTs and 4.46 days in OBs);increasing rate of nucleic acid conversion (ARD = 73 more per 1000 patients in OBs, baseline risk: 16.30%). No serious adverse reactions were found and the differences between CHM and usual supportive care were insignificant. Conclusion: Encouraging evidence showed that CHMs were beneficial in treating mild or moderate patients. CHMs have been proved to possess a safety profile that is comparable to that of usual supportive treatment alone. More rigorously designed clinical trials and mechanism studies are still warranted to further confirm the present findings.

The evolution of structural resilience of global oil and gas resources trade network

This paper establishes anetwork resilience evaluation framework of the global oil and gas resourcetrade network in 2010, 2015 and 2020. The results are as follows: The links of the oil trade network present a gradually shrinking trend, and the gas tradenetwork presents a trend of close connection first and then reduced. In termsof network density, network centrality, network connectivity and network size, the structural resilience of the oil and gas resource trade network displays ashrinking trend, and the gas trade network is superior. Concerninginvulnerability and recovery, the resilience of the oil trade network issuperior to the natural gas trade network. In simulated attacks, the oil tradenetwork reveals a higher resilience towards intentional attacks, and the gastrade network shows a higher resilience towards random attacks. The Strait ofHormuz and the Strait of Malacca are critical chokepoints in the networks.

Role of Traditional Chinese Medicine in Treating Severe or Critical COVID-19: A Systematic Review of Randomized Controlled Trials and Observational Studies.

Background: The coronavirus disease 2019 (COVID-19) continues to spread globally. Due to the higher risk of mortality, the treatment of severe or critical patients is a top priority. Traditional Chinese medicine (TCM) treatment has played an extremely important role in the fight against COVID-19 in China; a timely evidence summary on TCM in managing COVID-19 is crucial to update the knowledge of healthcare for better clinical management of COVID-19. This study aimed to assess the effects and safety of TCM treatments for severe/critical COVID-19 patients by systematically collecting and synthesizing evidence from randomized controlled trials (RCTs) and observational studies (e.g., cohort). Methods: We searched nine databases up to 19th March 2022 and the reference lists of relevant publications. Pairs of reviewers independently screened studies, extracted data of interest, and assessed risk of bias. We performed qualitative systematic analysis with visual presentation of results and compared the direction and distribution of effect estimates for each patient's important outcome. We performed sensitivity analyses to observe the robustness of results by restricting analysis to studies with low risk of bias. Results: The search yielded 217,761 records, and 21 studies (6 RCTs and 15 observational studies) proved eligible. A total of 21 studies enrolled 12,981 severe/critical COVID-19 patients with a mean age of 57.21 years and a mean proportion of men of 47.91%. Compared with usual supportive treatments, the effect estimates of TCM treatments were consistent in direction, illustrating that TCM treatments could reduce the risk of mortality, rate of conversion to critical cases, and mechanical ventilation, and showed significant advantages in shortening the length of hospital stay, time to viral clearance, and symptom resolution. The results were similar when we restricted analyses to low-risk-bias studies. No serious adverse events were reported with TCM treatments, and no significant differences were observed between groups. Conclusion: Encouraging evidence suggests that TCM presents substantial advantages in treating severe/critical COVID-19 patients. TCM has a safety profile that is comparable to that of conventional treatment alone. TCMs have played an important role in China's prevention and treatment of COVID-19, which sets an example of using traditional medicine in preventing and treating COVID-19 worldwide.

Analysis of Spatial and Temporal Changes of AQI in Wuhan City under the Urban Blockade of COVID-19 Pandemic.

Wuhan was the primary city in the world to adopt lockdown measures during the Coronavirus Disease 2019 pandemic. The influence of the abrupt halt of human activities on the air quality of Wuhan is a subject of considerable attention. This study is based on air quality data from 21 monitoring stations in Wuhan from 2016 to 2020. The lag effect and seasonal factors of AQI were taken into account to analyze the changes in air quality in Wuhan under the influence of the pandemic blockade. The results showed the following during the city closure: (1) A lagging effect is observed in air quality changes, with the change point occurring on the 14th day after the city closure; (2) the air quality index is substantially decreased, demonstrating a reduction in spatial differences; (3) NO2, PM10, and PM2.5 significantly decreased whilst O3 increased, and SO2 and CO did not change significantly; (4) except for the insignificant changes in spatial differences of PM10, all pollutants demonstrated a changing pattern of decreasing geographical differences. This paper provides a reference for studying the influence of human activities on the natural environment.

Influence factors analysis of COVID-19 Prevention behavior of chinese Citizens: a path analysis based on the hypothetical model.

BACKGROUND: Under the outbreak of Coronavirus disease 2019 (COVID-19), a structural equation model was established to determine the causality of important factors that affect Chinese citizens' COVID-19 prevention behavior. METHODS: The survey in Qingdao covered several communities in 10 districts and used the method of cluster random sampling. The research instrument used in this study is a self-compiled Chinese version of the questionnaire. Of the 1215 questionnaires, 1188 were included in our analysis. We use the rank sum test, which is a non-parametric test, to test the influence of citizens'basic sociodemographic variables on prevention behavior, and the rank correlation test to analyze the influencing factors of prevention behavior. IBM AMOS 24.0 was used for path analysis, including estimating regression coefficients and evaluating the statistical fits of the structural model, to further explore the causal relationships between variables. RESULTS: The result showed that the score in the prevention behavior of all citizens is a median of 5 and a quartile spacing of 0.31. The final structural equation model showed that the external support for fighting the epidemic, the demand level of health information, the cognition of (COVID-19) and the negative emotions after the outbreak had direct effects on the COVID-19 prevention behavior, and that negative emotions and information needs served as mediating variables. CONCLUSIONS: The study provided a basis for relevant departments to further adopt epidemic prevention and control strategies.

The roles of inactivated vaccines in older patients with infection of Delta variant in Nanjing, China.

BACKGROUND: The coronavirus disease 2019 (COVID-19) is spreading around the world. The COVID-19 vaccines may improve concerns about the pandemic. However, the roles of inactivated vaccines in older patients (aged ≥60 years) with infection of Delta variant were less studied. METHODS: We classified the older patients with infection of Delta variant into three groups based on the vaccination status: no vaccination (group A, n = 113), one dose of vaccination (group B, n = 46), and two doses of vaccination (group C, n = 22). Two inactivated COVID-19 vaccines (BBIBP-CorV or CoronaVac) were evaluated in this study. The demographic data, laboratory parameters, and clinical severity were recorded. RESULTS: A total of 181 older patients with infection of Delta variant were enrolled. 111 (61.3%) patients had one or more co-morbidities. The days of "turn negative" and hospital stay in Group C were lower than those in the other groups (P < 0.05). The incidences of multiple organ dysfunction syndrome (MODS), septic shock, acute respiratory distress syndrome (ARDS), acute kidney injury, and cardiac injury in Group A were higher than those in the other groups (P < 0.05). The MV-free days and ICU-free days during 28 days in Group A were also lower than those in the other groups (P < 0.05). In patients with co-morbidities, vaccinated cases had lower incidences of MODS (P = 0.015), septic shock (P = 0.015), and ARDS (P = 0.008). CONCLUSIONS: The inactivated COVID-19 vaccines were effective in improving the clinical severity of older patients with infection of Delta variant.

Influence of Hospital Outdoor Rest Space on the Eye Movement Measures and Self-Rating Restoration of Staff.

Objective: To investigate the effect of hospital outdoor rest space on the eye movement measures and self-rating restoration of staff. Background: Relieving the pressure of hospital staff through exposure to hospital outdoor rest space is essential, but there is a scarcity of research on the impact of hospital outdoor rest space on the eye movement measures and self-rating restoration of staff, especially for large Chinese hospitals. Methods: Cross-analysis was conducted based on the eye movement measures of 76 staff members obtained by eye movement tracking equipment in combination with the self-rating restoration scale and hospital outdoor rest space picture attributes (element proportion and position, brightness and saturation). Results: The differences in eye movement measures of different staff attributes (occupation, age, and gender) were identified, and the effects of hospital outdoor rest space picture attributes on the eye movement measures and self-rating restoration scale of staff were summarized. A number of proposals were also formulated: hospital outdoor rest space should be set up close to the working area of the group of medical staff; attention should be paid to the actual needs of senior staff members and the work pressure of junior nurses; the exposure to natural environment should be increased and the proportion of hard artificial elements should be reduced; the natural environment should be placed in the visual center; the saturation and brightness of hospital outdoor rest space should be increased; and staff members should have access to the sky environment in a variety of ways. Conclusion: The present study is an empirical study of evidence-based design on hospital outdoor rest space in China, and the results reveal the effects of hospital outdoor rest space on the eye movement measures and self-rating restoration of staff.

The Impact of Consumer Purchase Behavior Changes on the Business Model Design of Consumer Services Companies Over the Course of COVID-19.

The COVID-19 pandemic has had a profound psychological and behavioral impact on people around the world. Consumer purchase behaviors have thus changed greatly, and consumer services companies need to adjust their business models to adapt to this change. From the perspective of consumer psychology, this paper explores the impact of consumer purchase behavior changes over the course of the pandemic on the business model design of consumer services companies using a representative survey of 1,742 individuals. Our results show that changes in consumer purchase behavior have a significant impact on the design of consumer services firms' business models. Specifically, changes in consumers' purchase object, motive, and timeframe are more likely to spark a novelty-centered business model design, whereas changes in purchase method tend to inspire an efficiency-centered one. Our findings provide a theoretical reference for consumer services companies in designing business models when faced with unexpected crises.

Increased Peripheral Blood Neutrophil Activation Phenotypes and Neutrophil Extracellular Trap Formation in Critically Ill Coronavirus Disease 2019 (COVID-19) Patients: A Case Series and Review of the Literature.

BACKGROUND: Increased inflammation has been well defined in coronavirus disease 2019 (COVID-19), while definitive pathways driving severe forms of this disease remain uncertain. Neutrophils are known to contribute to immunopathology in infections, inflammatory diseases, and acute respiratory distress syndrome, a primary cause of morbidity and mortality in COVID-19. Changes in neutrophil function in COVID-19 may give insight into disease pathogenesis and identify therapeutic targets. METHODS: Blood was obtained serially from critically ill COVID-19 patients for 11 days. Neutrophil extracellular trap formation (NETosis), oxidative burst, phagocytosis, and cytokine levels were assessed. Lung tissue was obtained immediately postmortem for immunostaining. PubMed searches for neutrophils, lung, and COVID-19 yielded 10 peer-reviewed research articles in English. RESULTS: Elevations in neutrophil-associated cytokines interleukin 8 (IL-8) and interleukin 6, and general inflammatory cytokines IFN-inducible protien-19, granulocyte macrophage colony-stimulating factor (GM-CSF), interleukin 1ß, interleukin 10, and tumor necrosis factor, were identified both at first measurement and across hospitalization (P < .0001). COVID-19 neutrophils had exaggerated oxidative burst (P < .0001), NETosis (P < .0001), and phagocytosis (P < .0001) relative to controls. Increased NETosis correlated with leukocytosis and neutrophilia, and neutrophils and NETs were identified within airways and alveoli in lung parenchyma of 40% of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected lungs available for examination (2 of 5). While elevations in IL-8 and absolute neutrophil count correlated with disease severity, plasma IL-8 levels alone correlated with death. CONCLUSIONS: Literature to date demonstrates compelling evidence of increased neutrophils in the circulation and lungs of COVID-19 patients. Importantly, neutrophil quantity and activation correlates with severity of disease. Similarly, our data show that circulating neutrophils in COVID-19 exhibit an activated phenotype with enhanced NETosis and oxidative burst.

Modeling potential impact of COVID-19 pandemic on global electric vehicle supply chain.

The on-going COVID-19 pandemic and consequent lockdowns cast significant impacts on global economy in the short run. Their impact on stability of global electric vehicles (EVs) supply chain and thus our climate ambition in the long run, however, remains hitherto largely unexplored. We aim to address this gap based on an integrated model framework, including assessing supply risks of 17 selected core commodities throughout the EV supply chain and further applying the supply constraints to project future EV sales until 2030. Our model results under three pandemic development scenarios indicate that if the pandemic is effectively contained before 2024, the global EV industry will recover without fundamentally scathed and thus can maintain the same growth trend as in the no-pandemic scenario by 2030. We suggest that fiscal stimulus in the postpandemic era should be directed more toward upgrading the quality of battery products, rather than expanding the production capacity.

Nanobody-Functionalized Cellulose for Capturing SARS-CoV-2.

The highly transmissible severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 253 million people, claiming ∼5.1 million lives to date. Although mandatory quarantines, lockdowns, and vaccinations help curb viral transmission, there is a pressing need for cost-effective systems to mitigate the viral spread. Here, we present a generic strategy for capturing SARS-CoV-2 through functionalized cellulose materials. Specifically, we developed a bifunctional fusion protein consisting of a cellulose-binding domain and a nanobody (Nb) targeting the receptor-binding domain of SARS-CoV-2. The immobilization of the fusion proteins on cellulose substrates enhanced the capture efficiency of Nbs against SARS-CoV-2 pseudoviruses of the wild type and the D614G variant, the latter of which has been shown to confer higher infectivity. Furthermore, the fusion protein was integrated into a customizable chromatography with highly porous cellulose to capture viruses from complex fluids in a continuous fashion. By capturing and containing viruses through the Nb-functionalized cellulose, our work may find utilities in virus sampling and filtration through the development of paper-based diagnostics, environmental tracking of viral spread, and reducing the viral load from infected individuals. IMPORTANCE The ongoing efforts to address the COVID-19 pandemic center around the development of diagnostics, preventative measures, and therapeutic strategies. In comparison to existing work, we have provided a complementary strategy to capture SARS-CoV-2 by functionalized cellulose materials through paper-based diagnostics as well as virus filtration in perishable samples. Specifically, we developed a bifunctional fusion protein consisting of both a cellulose-binding domain and a nanobody specific for the receptor-binding domain of SARS-CoV-2. As a proof of concept, the fusion protein-coated cellulose substrates exhibited enhanced capture efficiency against SARS-CoV-2 pseudovirus of both the wild type and the D614G variant, the latter of which has been shown to confer higher infectivity. Furthermore, the fusion protein was integrated into a customizable chromatography for binding viruses from complex biological fluids in a highly continuous and cost-effective manner. Such antigen-specific capture can potentially immobilize viruses of interest for viral detection and removal, which contrasts with the common size- or affinity-based filtration devices that bind a broad range of bacteria, viruses, fungi, and cytokines present in blood (https://clinicaltrials.gov/ct2/show/NCT04413955). Additionally, since our work focuses on capturing and concentrating viruses from surfaces and fluids as a means to improve detection, it can serve as an "add-on" technology to complement existing viral detection methods, many of which have been largely focusing on improving intrinsic sensitivities.

A census of the lung: CellCards from LungMAP.

The human lung plays vital roles in respiration, host defense, and basic physiology. Recent technological advancements such as single-cell RNA sequencing and genetic lineage tracing have revealed novel cell types and enriched functional properties of existing cell types in lung. The time has come to take a new census. Initiated by members of the NHLBI-funded LungMAP Consortium and aided by experts in the lung biology community, we synthesized current data into a comprehensive and practical cellular census of the lung. Identities of cell types in the normal lung are captured in individual cell cards with delineation of function, markers, developmental lineages, heterogeneity, regenerative potential, disease links, and key experimental tools. This publication will serve as the starting point of a live, up-to-date guide for lung research at https://www.lungmap.net/cell-cards/. We hope that Lung CellCards will promote the community-wide effort to establish, maintain, and restore respiratory health.