Trend of research on the medical use of molecular hydrogen: a bibliometric analysis.

The medical use of molecular hydrogen, including hydrogen-rich water and hydrogen gas, has been extensively explored since 2007. This article aimed to demonstrate the trend in medical research on molecular hydrogen. A total of 1126 publications on hydrogen therapy were retrieved from the PubMed database until July 30, 2021. From 2007 to 2020, the number of publications in this field had been on an upward trend. Medical Gas Research, Scientific Report and Shock have contributed the largest number of publications on this topic. Researchers by the name of Xue-Jun Sun, Ke-Liang Xie and Yong-Hao Yu published the most studies in the field. Analysis of the co-occurrence of key words indicated that the key words "molecular hydrogen," "hydrogen-rich water," "oxidative stress," "hydrogen gas," and "inflammation" occurred most frequently in these articles. "Gut microbiota," "pyroptosis," and "COVID-19" occurred the most recently among the keywords. In summary, the therapeutic application of molecular hydrogen had attracted much attention in these years. The advance in this field could be caught up by subscribing to relevant journals or following experienced scholars. Oxidative stress and inflammation were the most important research directions currently, and gut microbiota, pyroptosis, and coronavirus disease 2019 might become hotspots in the future.

Advances in research on 3C-like protease (3CLpro) inhibitors against SARS-CoV-2 since 2020.

COVID-19 caused by SARS-CoV-2 in late 2019 is still threatening global human health. Although some vaccines and drugs are available in the market, controlling the spread of the SARS-CoV-2 virus remains a huge challenge. 3C-like protease (3CLpro) is a highly conserved key protease for SARS-CoV-2 replication, and no relevant homologous protein with a similar cleavage site to 3CLpro has been identified in humans, highlighting that development of 3CLpro inhibitors exhibits great promise for treatment of COVID-19. In this review, the authors describe the structure and function of 3CLpro. To better understand the characteristics of SARS-CoV-2 3CLpro inhibitors, the SARS-CoV-2 3CLpro inhibitors reported since 2020 are classified into peptidomimetic covalent inhibitors, non-peptidomimetic covalent inhibitors and non-covalent small molecule inhibitors, and the representative inhibitors, their biological activities and binding models are highlighted. Collectively, we hope that all the information presented here will provide new insights into the design and development of more effective 3CLpro inhibitors against SARS-CoV-2 as novel anti-coronavirus drugs.

Computational modeling of hypercoagulability in COVID-19.

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has infected more than 100 million people worldwide and claimed millions of lives. While the leading cause of mortality in COVID-19 patients is the hypoxic respiratory failure from acute respiratory distress syndrome, there is accumulating evidence that shows excessive coagulation also increases the fatalities in COVID-19. Thus, there is a pressing demand to understand the association between COVID-19-induced hypercoagulability and the extent of formation of undesired blood clots. Mathematical modeling of coagulation has been used as an important tool to identify novel reaction mechanisms and to identify targets for new drugs. Here, we employ the coagulation factor data of COVID-19 patients reported from published studies as inputs for two mathematical models of coagulation to identify how the concentrations of coagulation factors change in these patients. Our simulation results show that while the levels of many of the abnormal coagulation factors measured in COVID-19 patients promote the generation of thrombin and fibrin, two key components of blood clots, the increased level of fibrinogen and then the reduced level of antithrombin are the factors most responsible for boosting the level of fibrin and thrombin, respectively. Altogether, our study demonstrates the potential of mathematical modeling to identify coagulation factors responsible for the increased clot formation in COVID-19 patients where clinical data is scarce.

Prospects for Plant-Based Meat: Current Standing, Consumer Perceptions, and Shifting Trends.

Dietary habits have a substantial influence on both planet and individual health. High intake of animal products has significant negative effects on the environment and on human health; hence, a reduction in meat consumption is necessary. The transition towards plant-based meat (PBM) is one of the potential solutions for environmental and health issues. To achieve this goal, it is important to understand the dietary habits and demands of consumers. This review was designed with a focus on PBM alternatives, dietary shifts during the COVID-19 pandemic, the drivers of consumers' perceptions in various countries, and the measures that can promote the shift towards PBM. The PBM market is predicted to grow with rising awareness, familiarity, and knowledge in the coming years. Companies must focus on the categories of anticipated benefits to aid consumers in making the switch to a diet higher in PBM alternatives if they want to win over the target market.

Chest computed tomography and pulmonary function analysis of coronavirus disease 2019 survivors in 1 month follow-up period after cure and discharge

OBJECTIVE: The objective is to explore the chest computed tomography (CT) and pulmonary function findings of coronavirus disease 2019 (COVID-19) survivors 1 month after discharge. METHODS: We retrospectively analyzed the chest CT and pulmonary function findings of 158 (COVID-19) survivors who were discharged and followed up at Wuhan Red Cross Hospital from April 9 to May 10, 2020. RESULTS: Follow-up chest CT revealed that pulmonary lesions in all patients were clearly absorbed and dissipated. One month after discharge, 125 (79.1%) patients had residual imaging abnormalities, mainly light ground-glass opacities (44.9%) and light patchy shadows (38.6%). Other features included fibrous cord lesions in 90 cases (57.0%), pulmonary nodules in 46 cases (29.1%), pleural thickening in 44 cases (27.8%), and mediastinal lymphadenopathy in 81 cases (51.3%). Among 158 COVID-19 survivors, 124 were tested for pulmonary function. Pulmonary function tests revealed pulmonary function impairment in 10 patients (8.1%), restrictive ventilation dysfunction in 16 (12.9%), and pulmonary diffusion dysfunction in 48 (38.7%). Residual lung lesions and pleural thickening were negatively correlated with DLCO% (P < 0.05). CONCLUSION: COVID-19 patients have characteristic findings on chest CT and pulmonary function testing. Identifying these findings is helpful to dynamically monitor the disease prognosis.

Immunogenicity of inactivated COVID-19 vaccine in patients with autoimmune inflammatory rheumatic diseases.

Progress has been made in COVID-19 vaccine development, with encouraging safety and efficacy data. The purpose of this study was to investigate the immunogenicity of inactivated COVID-19 vaccine in patients with autoimmune inflammatory rheumatic diseases (AIIRD). Patients with AIIRD (n = 101) were included in this study. All patients received 2 doses of inactivated COVID-19 vaccine. Serum anti-S1/RBD protein IgG was detected 2-16 weeks after the second vaccination. Seropositivity was defined as IgG ≥ 1.00 bound antibody unit S/CO. Immunogenicity of inactivated COVID-19 vaccine was assessed by seropositivity rate and the levels of serum IgG antibody against anti-S1/RBD protein, compared with the general population (n = 46). There was no difference by statistical significance in the seropositivity rate between patients with AIIRD (82.2%) and SLE (86.1%) and the control group (93.5%), p > 0.05. The level of anti-S1/RBD protein IgG antibodies in patients with AIIRD (median [IQR], 8.8 [2.2-17.3]) and SLE (median [IQR], 9.6 [2.4-20.4]) was comparable to that in the control group (median [IQR], 7.2 [3.1-14.2]), p > 0.05. Patients treated with glucocorticoids(GCs) (median dose, [IQR]: 2.5 mg/day [IQR 2.5-5.0]) or hydroxychloroquine(HCQ) or GCs + HCQ without other immunomodulatory medications, had an appropriate immunogenic response(88.1%) with high levels of anti-S1/RBD protein IgG(median [IQR], 12.1 [6.5-20.4]). Neither of patients treated with rituximab had positive serum antibodies, which was statistically significant, compared with the control group (p < 0.01). Compared with the control group, methotrexate(MTX) and iguratimod(IGU) was significantly reduced the level of anti-S1/RBD protein IgG antibodies. Inactivated COVID-19 vaccine had appropriate immunogenicity in patients with AIIRD. Immunogenicity of inactivated COVID-19 vaccine was severely impaired by rituximab, and also suppressed by MTX and IGU, while low doses of GC and HCQ had negligible effect.

Can Subsidy Policies Reduce Vaccine Hesitancy Under Social Learning?

Vaccine hesitancy refers to a delay in getting or refusing vaccinations for efficacy reviews from early vaccinated individuals (e.g., social learning). However, no reviews occur if everyone delays. To overcome vaccine hesitancy, we first introduce social learning to characterize this undesirable behavior in two-period vaccine market (composed of a government, a manufacturer, and individuals). Then, designing subsidy policies are in three aspects: subsidy recipients (who should be subsidized, individuals or manufacturer), subsidy times (when subsidy policies should be set, preannounced or responsive), and subsidy paths (how the subsidy level should be adjusted over two periods, increasing or decreasing). Some results are yielded. First, if subsidy recipients are individuals, sales subsidies occur, and their equilibrium subsidy paths hinge on subsidy times. When sales subsidies are preannounced in the first period, a decreasing path is always optimal. In contrast, when these subsidies are responsive in two periods, an increasing path may be optimal. Second, these optimal sales subsidies can counter vaccine hesitancy and, further, utilize social learning to enhance vaccine coverage with different levels. Their differences are affected by two factors (government budgets and uncertain vaccine efficacy levels) that have asymmetric roles. Finally, if subsidy recipients are shifted from individuals to the manufacturer, cost subsidy occurs but it fails to overcome vaccine hesitancy.

Circulating cell clusters aggravate the hemorheological abnormalities in COVID-19.

Microthrombi and circulating cell clusters are common microscopic findings in patients with coronavirus disease 2019 (COVID-19) at different stages in the disease course, implying that they may function as the primary drivers in disease progression. Inspired by a recent flow imaging cytometry study of the blood samples from patients with COVID-19, we perform computational simulations to investigate the dynamics of different types of circulating cell clusters, namely white blood cell (WBC) clusters, platelet clusters, and red blood cell clusters, over a range of shear flows and quantify their impact on the viscosity of the blood. Our simulation results indicate that the increased level of fibrinogen in patients with COVID-19 can promote the formation of red blood cell clusters at relatively low shear rates, thereby elevating the blood viscosity, a mechanism that also leads to an increase in viscosity in other blood diseases, such as sickle cell disease and type 2 diabetes mellitus. We further discover that the presence of WBC clusters could also aggravate the abnormalities of local blood rheology. In particular, the extent of elevation of the local blood viscosity is enlarged as the size of the WBC clusters grows. On the other hand, the impact of platelet clusters on the local rheology is found to be negligible, which is likely due to the smaller size of the platelets. The difference in the impact of WBC and platelet clusters on local hemorheology provides a compelling explanation for the clinical finding that the number of WBC clusters is significantly correlated with thrombotic events in COVID-19 whereas platelet clusters are not. Overall, our study demonstrates that our computational models based on dissipative particle dynamics can serve as a powerful tool to conduct quantitative investigation of the mechanism causing the pathological alterations of hemorheology and explore their connections to the clinical manifestations in COVID-19.

Estimation of Broadleaf Tree Canopy Height of Wolong Nature Reserve Based on InSAR and Machine Learning Methods

Tree height is an important parameter for calculating forest carbon sink and assessing forest carbon cycle. In order to obtain forest tree height over a large area both efficiently and at a low cost, this study proposed an Interferometric Synthetic Aperture Radar (InSAR) combined with a machine learning method to estimate the tree canopy height. The forest height in the study area was obtained using Unmanned Aerial Vehicle (UAV) photogrammetry, which was considered to be the true canopy height. Two machine learning methods (Random Forest, Multi-layer perceptron) were used to establish the relationship between phase center height calculated by InSAR DEM differential interference method and coherent amplitude method with true canopy height. The topographic factor, backward scattering coefficient and coherence coefficient were introduced into the relationship model. It was found that the accuracy of tree height estimation using random forest and two InSAR methods can reach 0.95 and 0.94. The root-mean-square error was 1.76 m, 1.86 m, respectively. The accuracy of tree height estimation using multi-layer perceptron and two InSAR methods was 0.25 and 0.2. The root-mean-square error was 3.96 m and 4.13 m. The results indicated that the combination of InSAR and machine learning can estimate canopy height efficiently and at a low cost. Moreover, the integrated learning algorithm random forest demonstrated better stability and higher accuracy than the single learning algorithm multi-layer perceptron.

Dust events affect the occurrence of influenza: A case-crossover study in an arid city of China (preprint)

Background Air aerosol is believed to be an important pathway for infectious disease transmission like COVID-19 as well as influenza. Therefore, we hypothesized that there might be a strong association between dust events and influenza, especially in semi-arid areas. This study aims to explore the effects of ambient particulate matter (PM) and dust events on laboratory-confirmed influenza cases in a semi-arid city.Methods A descriptive analysis of daily laboratory-confirmed influenza (influenza) cases, PM (PM10 and PM2.5), meteorological parameters and dust events were conducted from 2014 to 2019 in Lanzhou, China. The Case-crossover design combined with conditional Poisson regression models was used to estimate the lagging effects of PM and dust events on influenza. In addition, a hierarchical model was used to quantitatively evaluate the interactive effect of PM with ambient temperature and absolute humidity on influenza.Results We found that PM and dust events had a significant effect on influenza. The effects of PM10 and PM2.5 on influenza became stronger as the cumulative lag days increased, the greatest estimated relative risks (RRs) were 1.018 (1.011,1.024) and 1.06 1(1.034,1.087), respectively. Compared with the non-dust days, the effects of dust events with duration ≥ 1 day and with duration ≥ 2 days on influenza were the strongest at lag0 day, with the estimated RRs of 1.245 (95% CI: 1.061–1.463) and 1.483 (95% CI: 1.232–1.784), respectively. Subgroup analysis showed that pre-school children and school-aged children were more sensitive to PM and dust events exposure. Besides, we also found the low humidity and temperature had an interaction with PM, which could aggravate the risk of influenza.Conclusions Ambient PM and dust events exposure may increase the risk of laboratory-confirmed influenza, and the risk of laboratory-confirmed influenza increased with the dust events duration. These findings will provide additional epidemiological evidence for future influenza prevention and environmental protection.

Multiphysics and multiscale modeling of microthrombosis in COVID-19.

Emerging clinical evidence suggests that thrombosis in the microvasculature of patients with Coronavirus disease 2019 (COVID-19) plays an essential role in dictating the disease progression. Because of the infectious nature of SARS-CoV-2, patients' fresh blood samples are limited to access for in vitro experimental investigations. Herein, we employ a novel multiscale and multiphysics computational framework to perform predictive modeling of the pathological thrombus formation in the microvasculature using data from patients with COVID-19. This framework seamlessly integrates the key components in the process of blood clotting, including hemodynamics, transport of coagulation factors and coagulation kinetics, blood cell mechanics and adhesive dynamics, and thus allows us to quantify the contributions of many prothrombotic factors reported in the literature, such as stasis, the derangement in blood coagulation factor levels and activities, inflammatory responses of endothelial cells and leukocytes to the microthrombus formation in COVID-19. Our simulation results show that among the coagulation factors considered, antithrombin and factor V play more prominent roles in promoting thrombosis. Our simulations also suggest that recruitment of WBCs to the endothelial cells exacerbates thrombogenesis and contributes to the blockage of the blood flow. Additionally, we show that the recent identification of flowing blood cell clusters could be a result of detachment of WBCs from thrombogenic sites, which may serve as a nidus for new clot formation. These findings point to potential targets that should be further evaluated, and prioritized in the anti-thrombotic treatment of patients with COVID-19. Altogether, our computational framework provides a powerful tool for quantitative understanding of the mechanism of pathological thrombus formation and offers insights into new therapeutic approaches for treating COVID-19 associated thrombosis.

Stigma toward Wuhan people during the COVID-19 epidemic: an exploratory study based on social media.

BACKGROUND: Stigma associated with infectious diseases is common and causes various negative effects on stigmatized people. With Wuhan as the center of the COVID-19 outbreak in China, its people were likely to be the target of stigmatization. To evaluate the severity of stigmatization toward Wuhan people and provide necessary information for stigma mitigation, this study aimed to identify the stigmatizing attitudes toward Wuhan people and trace their changes as COVID-19 progresses in China by analyzing related posts on social media. METHODS: We collected 19,780 Weibo posts containing the keyword 'Wuhan people' and performed a content analysis to identify stigmatizing attitudes in the posts. Then, we divided our observation time into three periods and performed repeated-measures ANOVA to compare the differences in attitudes during the three periods. RESULTS: The results showed that stigma was mild, with 2.46% of related posts being stigmatizing. The percentages of stigmatizing posts differed significantly during the three periods. The percentages of 'Infectious' posts and 'Stupid' posts were significantly different for the three periods. The percentage of 'Irresponsible' posts was not significantly different for the three periods. After government interventions, stigma did not decrease significantly, and stigma with the 'Infectious' attitude even increased. It was not until the government interventions took effect that stigma significantly reduced. CONCLUSIONS: This study found that stigma toward Wuhan people included diverse attitudes and changed at different periods. After government interventions but before they took effect, stigma with the 'Infectious' attitude increased. After government interventions took effect, general stigma and stigmas with 'Infectious' and 'Stupid' attitudes decreased. This study constituted an important endeavor to understand the stigma toward Wuhan people in China during the COVID-19 epidemic. Implications for stigma reduction and improvement of the public's perception during different periods of epidemic control are discussed.

Immunomodulatory effects of selenium-enriched peptides from soybean in cyclophosphamide-induced immunosuppressed mice.

In this study, selenium-enriched soybean peptides (<3 kDa, named Se-SPep) was isolated and purified from the selenium-enriched soybean protein (Se-SPro) hydrolysate by ultrafiltration. The in-vivo immunomodulatory effects of Se-SPep were investigated in cyclophosphamide-induced immunosuppressed mice. Se-SPep treatment could alleviate the atrophy of immune organs and weight loss observed in immunosuppressive mice. Besides, Se-SPep administration could dramatically improve total protein, albumin, white blood cell, immunoglobulin (Ig) M, IgG, and IgA levels in blood. Moreover, Se-SPep strongly stimulated interleukin-2 (IL-2), interferon-gamma (IFN-γ), nitric oxide (NO), and cyclic guanosine monophosphate productions by up-regulating mRNA expressions of IL-2, IFN-γ, and inducible NO synthase in spleen tissue. Furthermore, Se-SPep exhibits more effective immunomodulatory activity compared to Se-SPro and SPep. In conclusion, Se-SPep could effectively enhance the immune capacity of immunosuppressive mice. These findings confirm Se-SPep is an effective immunomodulator with potential application in functional foods or dietary supplements.

Mitigating COVID-19 In Public Spaces

What can the hospitality industry do to reduce the risk of transmission of COVID-19? Part is recognizing that HVAC systems play a role in mitigating the risk of airborne transmission of COVID-19.1 At the beginning of the pandemic, hospitality facilities, including hotels and restaurants, quickly aligned with guidance from the CDC,2,3 WHO4 and other credible organizations such as ASHRAE5,6 by adjusting operating guidelines to increase outdoor air dilution and improve filtration, where possible, while maintaining guest and associate comfort. This article discusses a comprehensive study recently conducted by the authors to investigate the efficacy of portable air purifiers to improve air quality in public spaces.

COVID-19 associated anxiety enhances tinnitus

To investigate if the anxiety associated with coronavirus disease 2019 (COVID-19) is a promoting factor to tinnitus. A retrospective research design collected from 188 tinnitus patients, was used to compare the clinical characteristics of tinnitus between the patients in 2020 under pandemic pressure and those from the matching period in 2019. While anxiety was quantified using the Zung's Self-rating Anxiety Scale (SAS), tinnitus severity was evaluated using the Tinnitus Handicap Inventory (THI) questionnaire and the test of tinnitus loudness (TL). The assessments were repeated after the sound therapy plus educational counselling (STEC) for 38 patients in 2020 and 58 patients in 2019 and compared with EC alone therapy for 42 patients in 2020 and 17 patients in 2019. A large increase in anxiety was evident in 2020 in both case rate and SAS. The treatment of both methods was less effective in 2020. SAS, THI and TL were all deteriorated after the EC alone treatment in 2020, while an improvement was seen in 2019. This suggests that EC alone could not counteract the stress by COVID-19 at all, and the stress, if not managed well, can significantly increase the severity of tinnitus and associated anxiety. By using the EC subgroup in virtual control, we conclude that anxiety can serve as a promoting factor to tinnitus. We believe that this is the first study report that confirm the causative/promotive role of anxiety on tinnitus during COVID-19 pandemic.

Systematic profiling of SARS-CoV-2-specific IgG responses elicited by an inactivated virus vaccine identifies peptides and proteins for predicting vaccination efficacy.

One of the best ways to control COVID-19 is vaccination. Among the various SARS-CoV-2 vaccines, inactivated virus vaccines have been widely applied in China and many other countries. To understand the underlying protective mechanism of these vaccines, it is necessary to systematically analyze the humoral responses that are triggered. By utilizing a SARS-CoV-2 microarray with 21 proteins and 197 peptides that fully cover the spike protein, antibody response profiles of 59 serum samples collected from 32 volunteers immunized with the inactivated virus vaccine BBIBP-CorV were generated. For this set of samples, the microarray results correlated with the neutralization titers of the authentic virus, and two peptides (S1-5 and S2-22) were identified as potential biomarkers for assessing the effectiveness of vaccination. Moreover, by comparing immunized volunteers to convalescent and hospitalized COVID-19 patients, the N protein, NSP7, and S2-78 were identified as potential biomarkers for differentiating COVID-19 patients from individuals vaccinated with the inactivated SARS-CoV-2 vaccine. The comprehensive profile of humoral responses against the inactivated SARS-CoV-2 vaccine will facilitate a deeper understanding of the vaccine and provide potential biomarkers for inactivated virus vaccine-related applications.

Application of Portable Air Purifiers for Mitigating COVID-19 in Large Public Spaces

This study investigated, using validated computational fluid dynamics techniques, the actual performance of portable air purifiers for reducing the infection risks of airborne respiratory diseases such as COVID-19, by properly installing air purifiers in complicated large public spaces of primary concern, such as restaurants and ballrooms. The research results reveal that portable air purifiers with HEPA filtration provide an effective solution to help mitigate virus-carrying particles/droplets in large spaces where the central air conditioning system with HEPA filtration may not provide adequate dilution and/or effective ventilation. Deploying portable air purifier changes the local flow directions, and thus, reduces the cross-table airflows that may enhance the possibility of cross-infection. A field experiment was further conducted in a restaurant and a ballroom to verify the on-site performance. This study indicates that each space is unique in furniture, occupant and system layouts and capacities, and thus, requires individualized investigation of appropriate purifier number, capacities, and locations. Flexible solutions such as portable air purifiers are important and low-cost supplements to more elaborate solutions installed in central air systems.

Distributed probability of infection risk of airborne respiratory diseases

Infection risk is commonly used to predict potential health impacts of airborne respiratory diseases such as ?severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)' and associated environment conditions and mitigation measures. The assumption of perfect air-mixing in spaces is widely applied in prediction, which projects a single mean risk of infection in the space. Detailed distribution of infection risk, especially for large spaces such as large lecture hall, indoor stadium and ballroom, will be highly desired for evaluating indoor risks and improvement performance of mitigating strategies. This study developed new formulae for calculating the spatial distribution of infection risk, stemming from the original Wells?Riley model but integrating the spatial distribution of pathogen concentrations. Case studies were presented for two typical large public spaces (i.e. restaurant and ballroom). Distributed infection risks were predicted with and without mitigation measures, upon which critical parameters of portable air cleaners can be optimized. The method can be employed for estimating local infection risks of airborne respiratory diseases using either measured or simulated pathogen concentration.