PF-D-Trimer, a protective SARS-CoV-2 subunit vaccine: immunogenicity and application.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has had and continues to have a significant impact on global public health. One of the characteristics of SARS-CoV-2 is a surface homotrimeric spike protein, which is primarily responsible for the host immune response upon infection. Here we present the preclinical studies of a broadly protective SARS-CoV-2 subunit vaccine developed from our trimer domain platform using the Delta spike protein, from antigen design through purification, vaccine evaluation and manufacturability. The pre-fusion trimerized Delta spike protein, PF-D-Trimer, was highly expressed in Chinese hamster ovary (CHO) cells, purified by a rapid one-step anti-Trimer Domain monoclonal antibody immunoaffinity process and prepared as a vaccine formulation with an adjuvant. Immunogenicity studies have shown that this vaccine candidate induces robust immune responses in mouse, rat and Syrian hamster models. It also protects K18-hACE2 transgenic mice in a homologous viral challenge. Neutralizing antibodies induced by this vaccine show cross-reactivity against the ancestral WA1, Delta and several Omicrons, including BA.5.2. The formulated PF-D Trimer is stable for up to six months without refrigeration. The Trimer Domain platform was proven to be a key technology in the rapid production of PF-D-Trimer vaccine and may be crucial to accelerate the development and accessibility of updated versions of SARS-CoV-2 vaccines.

Impact of Challenging Behavior Online Modules on Korean Parents of Children With Developmental Disabilities: A Randomized Controlled Trial

Challenging behavior exhibited by young children with neurodevelopmental disabilities is known to negatively affect their optimal development and families? quality of life. Although some support exists for English-speaking parents of children with autism who live in high-resource countries, it is scarce for others. Such disparity may also be heightened during the coronavirus disease 2019 (COVID-19) pandemic with its various societal restrictions. To mitigate the treatment gap, we developed and adapted a series of online training modules on behavioral principles and examined its effectiveness with 88 South Korean parents using a randomized controlled trial. We found significant interaction effects on increasing parents? knowledge of behavioral principles, increasing positive parenting practices, and decreasing parental stress. Qualitative social validity data also indicated that parents were highly satisfied with the goals, procedures, and outcomes and that the program positively affected their parenting styles.

Energy-food nexus scarcity risk and the synergic impact of climate policy: A global production network perspective

Carbon neutrality has been a global consensus to navigate away from catastrophic climate change. In particular, such climate changes also generate inevitable influences on economic securities, such as energy security and food security, through energy structure transformation etc. Energy and food are essential elements for human beings, and they are naturally linked to sustainable development. Usually, emergency events, such as the COVID-19 pandemic, may threaten energy security or food security in a region, the risk of which would be amplified due to the energy-food nexus effect. This is no doubt also a challenge and an opportunity for countries to achieve carbon neutrality. To realize the stable pathways to carbon neutrality, it is important to analyze the energy scarcity risk and food scarcity risk of each industry and country as well as the nexus effect between energy and food. In this paper, we combine multi-regional input-output (MRIO) analysis with network control analysis (NCA) to investigate the dependence degree of each country and region on energy and food resources as well as the risk transmission network of the energy-food scarcity nexus. Base on this, the impact of climate policy on energy-food nexus scarcity risk is analyzed. We found some interesting conclusions. First, regarding the risk transmission network of the energy-food scarcity nexus, China, Germany and the US are the main generators, and the main receptors are Taiwan, Mexico and the Netherlands. These results imply that international trade transfers energy/food scarcity to geographically distant regions via the international supply chain. Second, as for the scarcity risk per unit of output, small economies that rely heavily on imported energy or food (such as Cyprus and Luxemburg) have the highest scarcity risk and are among the top receptors of transmitted risks. We suggest collaborative conservation and management of energy and food resources. Third, the analyses that assess the emission intensity and scarcity risk find that implementation of emission control policies could significantly decrease initial energy scarcity risk and energy-food nexus scarcity risk. This implies that besides emission reduction achievement, climate policies bring co-benefits of energy-food nexus security. Moreover, the co-benefit of energy and food nexus security for low income economies associated with climate policy is much higher than that for high income economies.

Optimization of Multisource Dynamic Model in TBO

When extracting flight data from airport terminal area, there are matters such as large volume, unclear features, and similar trend in time series. In order to deal with the related issues and to optimize the description, by combining with the TBO (Trajectory-Based Operation), an application proposed by the ICAO (International Civil Aviation Organization) in ASBU (Aviation System Block Upgrade), using multisource dynamic model to establish 4DDW (4D dynamic warping) algorithm, the multisource modeling integrated with evaluation system is proposed to realize the flight path optimization with time series characteristics and accord with the interval concept. The calculation results show that 4DDW can obtain the optimal solution for multiprofile calculation of TBO by comparing the composite trajectory deviation values and time dimension planning using the buffer and threshold values recommended by ICAO in airspace planning and flight procedure design. The results meet the requirements of high accuracy and convergence features of spatial waypoints and can improve the airport operation standards and terminal area capacity.

Knowledge, Attitude, and Perceived Barriers of Newly Graduated Registered Nurses Undergoing Standardized Training in Intensive Care Unit Toward Early Mobilization of Mechanically Ventilated Patients: A Qualitative Study in Shanghai

Aim: To explore the knowledge and attitudes of newly graduated registered nurses, who have undergone standardized training in the intensive care unit, about the early mobilization of mechanically ventilated patients and identify perceived barriers to the application of early mobilization. Background: Early mobilization of mechanically ventilated patients has been gradually gaining attention, and its safety and effectiveness have also been verified. Nurses in intensive care units are the implementers of early mobilization, and the quality of their care is closely related to patient prognosis. However, the knowledge and attitude of newly graduated registered nurses undergoing standardized training, in intensive care units, on the early mobilization of mechanically ventilated patients and the obstacles they face in clinical implementation are still unclear. Methods: This qualitative study utilized the phenomenological method to explore the experiences of 15 newly graduated registered nurses undergoing standardized training in intensive care units in a 3rd hospital in Shanghai, China. Semi-structured face-to-face interviews were conducted in June 2020. The Colaizzi seven-step framework was used for data analysis. Findings: A total of 15 new nurses comprised the final sample after data saturation. Three main themes emerged from the analysis and seven subthemes: perceived importance, low implementation rate, and perceived barriers. Conclusions: Newly graduated registered nurses undergoing standardized training in intensive care units have a high level of awareness of the importance of early mobilization of mechanically ventilated patients and are willing to implement it. However, there is a lack of relevant knowledge and other obstacles that restrict clinical implementation. Early mobilization should be included in the standardized training of new nurses in intensive care units.

Development and Validation of a New Prognostic Scoring System for COVID-19.

This study aimed to develop and validate a bedside risk analysis system for predicting the clinical severity and prognosis of patients with coronavirus disease 2019 (COVID-19). In total, 444 COVID-19 patients were included and randomly assigned in a 2:1 ratio to 2 groups: derivation group and validation group. The new scoring system comprised of the following 8 variables: history of malignant diseases, history of diabetes mellitus, dyspnea, respiratory rate >24 breaths/min, C-reactive protein level >14 mg/L, white blood cell count >8×109/L, platelets count <180 × 1012/L, and lymphocyte count <1 × 109/L. The sensitivity analysis revealed that this new scoring system was more efficient than the sequential organ failure assessment scoring system on the first day of admission. The receiver characteristic curve analysis revealed that the new risk scoring predicted the severe cases of COVID-19 infection with an area under the curve of 0.831 (95% confidence interval [CI]: 0.783-0.879) and 0.798 (95% CI: 0.727-0.869) in the derivation and validation groups, respectively. This proposed risk score system is a fairly reliable and robust tool for evaluating the severity and prognosis of patients with COVID-19. This may help in the early identification of severe COVID-19 patients with poor prognosis, requiring more intense interventions.

Impact of lipid nanoparticle size on mRNA vaccine immunogenicity.

Lipid nanoparticles (LNP) are effective delivery vehicles for messenger RNA (mRNA) and have shown promise for vaccine applications. Yet there are no published reports detailing how LNP biophysical properties can impact vaccine performance. In our hands, a retrospective analysis of mRNA LNP vaccine in vivo studies revealed a relationship between LNP particle size and immunogenicity in mice using LNPs of various compositions. To further investigate this, we designed a series of studies to systematically change LNP particle size without altering lipid composition and evaluated biophysical properties and immunogenicity of the resulting LNPs. While small diameter LNPs were substantially less immunogenic in mice, all particle sizes tested yielded a robust immune response in non-human primates (NHP).

Switching to electric vehicles can lead to significant reductions of PM2.5 and NO2 across China

Summary Transportation contributes to around one-fifth of global greenhouse gas emissions, while also causing severe air pollution. The conversion to electric vehicles (EVs) represents a major path to decarbonize the transport sector, with potentially significant co-benefits for human health. However, the scale of such co-benefits largely remains an empirical question and lacks observational evidence. The full lockdown in China during the coronavirus disease 2019 (COVID-19) pandemic provides an unprecedented real-world experiment to evaluate emission reduction potentials of a large-scale transition to EVs. Here, we utilize ground and satellite observations of air quality during the full lockdown to constrain predictions of a comprehensive chemical transport model and find that the substantial traffic reductions are near-linearly linked to reductions of PM2.5 (particles with an aerodynamic diameter ≤2.5 μm) and NO2. A further extrapolation of a full conversion to EVs shows a significant reduction of PM2.5 (30%–70%) and NO2 (30%–80%) in most of China. Our findings provide fact-based evidence of potential environmental benefits generated by fully switching to EVs.

Distinguishing between COVID-19 and influenza during the early stages by measurement of peripheral blood parameters.

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 infection. This study aims to examine the changes in peripheral blood parameters during the early stages of COVID-19 and influenza. We analyzed the peripheral blood parameters of 169 COVID-19 patients and 131 influenza patients during the early-onset stage. Results from the patients with COVID-19 were compared with those from healthy controls and influenza patients. In addition, results from patients with common and severe COVID-19 were further compared. There were significant differences between COVID-19 and influenza patients in terms of age, white blood cell count, platelet count, percentage of neutrophils, percentage of lymphocytes, percentage of monocytes, percentage of eosinophils, percentage of basophils, neutrophil, count and monocyte count. Two parameters (monocyte count and percentage of basophils) were combined to clarify the diagnostic efficacy of COVID-19 and influenza and the area under the curve was found to be 0.772. Comparison of peripheral blood parameters from common COVID-19, severe COVID-19, and influenza patients revealed many differences during the early disease stages. The diagnostic formula developed by this study will be of benefit for physicians in the differentiation of COVID-19 and influenza.

Development and validation of an individualized nomogram for early prediction of the duration of SARS-CoV-2 shedding in COVID-19 patients with non-severe disease.

With the number of cases of coronavirus disease-2019 (COVID-19) increasing rapidly, the World Health Organization (WHO) has recommended that patients with mild or moderate symptoms could be released from quarantine without nucleic acid retesting, and self-isolate in the community. This may pose a potential virus transmission risk. We aimed to develop a nomogram to predict the duration of viral shedding for individual COVID-19 patients. This retrospective multicentric study enrolled 135 patients as a training cohort and 102 patients as a validation cohort. Significant factors associated with the duration of viral shedding were identified by multivariate Cox modeling in the training cohort and combined to develop a nomogram to predict the probability of viral shedding at 9, 13, 17, and 21 d after admission. The nomogram was validated in the validation cohort and evaluated by concordance index (C-index), area under the curve (AUC), and calibration curve. A higher absolute lymphocyte count (P=0.001) and lymphocyte-to-monocyte ratio (P=0.013) were correlated with a shorter duration of viral shedding, while a longer activated partial thromboplastin time (P=0.007) prolonged the viral shedding duration. The C-indices of the nomogram were 0.732 (95% confidence interval (CI): 0.685‒0.777) in the training cohort and 0.703 (95% CI: 0.642‒0.764) in the validation cohort. The AUC showed a good discriminative ability (training cohort: 0.879, 0.762, 0.738, and 0.715 for 9, 13, 17, and 21 d; validation cohort: 0.855, 0.758, 0.728, and 0.706 for 9, 13, 17, and 21 d), and calibration curves were consistent between outcomes and predictions in both cohorts. A predictive nomogram for viral shedding duration based on three easily accessible factors was developed to help estimate appropriate self-isolation time for patients with mild or moderate symptoms, and to control virus transmission.

A nomogram to early predict isolation length for non-severe COVID-19 patients based on laboratory investigation: A multicenter retrospective study in Zhejiang Province, China.

BACKGROUND: Majority coronavirus disease 2019 (COVID-19) patients are classified as mild and moderate (non-severe) diseases. We aim to develop a model to predict isolation length for non-severe patients. METHODS: Among 188 non-severe patients, 96 patients were enrolled as training cohort to identify factors associated with isolation length via Cox regression model and develop a nomogram. Other 92 patients formed as validation cohort to validate nomogram. Concordance index (C-index), area under the curve (AUC) and calibration curves were used to evaluated nomogram. RESULTS: Increasing absolute eosinophil count (AEC) after admission was correlated with shorter isolation length (P = 0.02). Baseline activated partial thromboplastin time (APTT) > 30 s was correlated with longer isolation length (P = 0.03). A nomogram to predict isolation probability at 11-, 16- and 21-day was developed and validated. The C-indices of training and validation cohort were 0.604 and 0.682 respectively. Both cohorts showed a good discriminative ability (AUC, 11-day: 0.646 vs 0.730; 16-day: 0.663 vs 0.750; 21-day: 0.711 vs 0.783; respectively) and calibration power. CONCLUSIONS: Baseline APTT and dynamic change of AEC were two significant factors associated with isolation length of non-severe patients. Nomogram could predict isolation probability for each patient to estimate appropriate quarantine length.

Relationship Between Psychological Responses and the Appraisal of Risk Communication During the Early Phase of the COVID-19 Pandemic: A Two-Wave Study of Community Residents in China.

The novel coronavirus disease (COVID-19) has affected hundreds of millions of people worldwide. Data collection in the ascending phase is crucial to address a rapidly evolving crisis by helping us understand the uncertain relationship between risk communication and psychological responses. Data were collected from 26 January 26, 2020, until February 17, 2020, with a mean test-retest interval of 16 days. A total of 846 adults from four residential communities in high-risk areas (Wuhan city) and low-risk areas (Zhengzhou city) were invited to complete a set of Internet-based questionnaires measuring the adoption of preventive behaviors, appraisal of risk communication, anxiety level, and susceptibility to emotional contagion. At the baseline assessment (Wave 1), 58 withdrew from the study, and 788 (433 females) completed the questionnaires. At the Wave 2 survey, 318 (185 females) adults from Wave 1 were retained. The results from cross-lagged models demonstrated reciprocal negative associations between anxiety and risk communication and between the appraisal of risk communication and the adoption of preventive behaviors. In addition, a higher appraisal of risk communication in the initial period of the outbreak mitigated the respondents' susceptibility to emotional contagion later on. Susceptibility to emotional contagion was positively associated with preventive behaviors taken. Furthermore, multiple-group structural equation modeling suggested that risk communication was more likely to affect the susceptibility to emotional contagion of people on the frontline of the outbreak than people living in low-risk areas. This study demonstrated the importance of risk communication aimed at encouraging appropriate countermeasures against virus outbreaks.

Unexpected rise of ozone in urban and rural areas, and sulfur dioxide in rural areas during the coronavirus city lockdown in Hangzhou, China: implications for air quality.

The outbreak of coronavirus named COVID-19, initially identified in Wuhan, China in December 2019, has spread rapidly at the global scale. Most countries have rapidly stopped almost all activities including industry, services and transportation of goods and people, thus decreasing air pollution in an unprecedented way, and providing a unique opportunity to study air pollutants. While satellite data have provided visual evidence for the global reduction in air pollution such as nitrogen dioxide (NO2) worldwide, precise and quantitative information is missing at the local scale. Here we studied changes in particulate matter (PM2.5, PM10), carbon monoxide (CO), NO2, sulfur dioxide (SO2) and ozone (O3) at 10 urban sites in Hangzhou, a city of 7.03 million inhabitants, and at 1 rural site, before city lockdown, January 1-23, during city lockdown, January 24-February 15, and during resumption, February 16-28, in 2020. Results show that city lockdown induced a sharp decrease in PM2.5, PM10, CO, and NO2 concentrations at both urban and rural sites. The NO2 decrease is explained by reduction in traffic emissions in the urban areas, and by lower regional transport in rural areas during lockdown, as expected. SO2 concentrations decreased from 6.3 to 5.3 µg m-3 in the city, but increased surprisingly from 4.7 to 5.8 µg m-3 at the rural site: this increase is attributed both to higher coal consumption for heating and emissions from traditional fireworks of the Spring Eve and Lantern Festivals during lockdown. Unexpectedly, O3 concentrations increased by 145% from 24.6 to 60.6 µg m-3 in the urban area, and from 42.0 to 62.9 µg m-3 in the rural area during the lockdown. This finding is explained by the weakening of chemical titration of O3 by NO due to reductions of NOx fresh emissions during the non-photochemical reaction period from 20:00 PM to 9:00 AM (local time). During the lockdown, compared to the same period in 2019, the daily average concentrations in the city decreased by 42.7% for PM2.5, 47.9% for PM10, 28.6% for SO2, 22.3% for CO and 58.4% for NO2, which is obviously explained by the absence of city activities. Overall, we observed not only the expected reduction in some atmospheric pollutants (PM, SO2, CO, NO2), but also unexpected increases in SO2 in the rural areas and of ozone (O3) in both urban and rural areas, the latter being paradoxically due to the reduction in nitrogen oxide levels. In other words, the city lockdown has improved air quality by reducing PM2.5, PM10, CO, and NO2, but has also decreased air quality by augmenting O3 and SO2.