The UK National Health Service's migration infrastructure in times of Brexit and COVID-19: Disjunctures, continuities and innovations.

The COVID-19 pandemic and Brexit were separate yet inter-related developments which affected the British National Health Service (NHS). The UK's state-funded health sector had historically relied on migrant labour and depended on a migration infrastructure designed to solve its nursing labour shortages. The analysis of primary qualitative and secondary quantitative data shows that the NHS migration infrastructure increased its orientation towards Asia to compensate for the effects of Brexit. The paper reveals how the persistent use of temporary visas along with conditional contractual arrangements has led to various exclusions for migrant nurses and midwives. These data also demonstrate how international travel restrictions associated with COVID-19 created temporary obstacles for nurses' inflows. Alongside Brexit, this has also resulted in an increase in outflows amongst EU health workers. The article identifies the development of migrant support infrastructure amongst Filipino and Indian nurses as a major COVID-19 linked innovation.

Spatiotemporal characteristics and socioeconomic factors of PM2.5 heterogeneity in mainland China during the COVID-19 epidemic.

Spatiotemporal variation of PM2.5 in 2018 and 2020 were compared to analyze the impacts of COVID-19, the spatial heterogeneity of PM2.5, and meteorological and socioeconomic impacts of PM2.5 concentrations heterogeneity in China in 2020 were investigated. The results showed that the annual average PM2.5 concentration in 2020 was 32.73 µg/m3 existing a U-shaped variation pattern, which has decreased by 6.38 µg/m3 compared to 2018. A consistent temporal pattern was found in 2018 and 2020 with significant high values in winter and low in summer. PM2.5 declined dramatically in eastern and central China, where are densely populated and economically developed areas during the COVID-19 epidemic compared with previous years, indicating that the significantly decline of social activities had an important effect on the reduction of PM2.5 concentrations. The lowest PM2.5 was found in August because that precipitation had a certain dilution effect on pollutants. January was the most polluted due to centralized coal burning for heating in North China. Overall, the PM2.5 concentrations in China were spatially agglomerated. The highly polluted contiguous zones were mainly located in northwest China and the central plains city group, while the coastal area and Inner Mongolia were areas with good air quality. Negative correlations were found between natural factors (temperature, precipitation, wind speed and relative humidity) and PM2.5 concentrations, with precipitation has the greatest impact on PM2.5, which are beneficial for reducing PM2.5 concentrations. Among the socio-economic factors, proportion of the secondary industry, number of taxis, per capita GDP, population, and industrial nitrogen oxide emissions have positive correlation effects on PM2.5, while the overall social electricity consumption, industrial sulfur dioxide emissions, green coverage in built-up areas, and total gas and liquefied gas supply have negative correlation effects on the PM2.5.

5G-Based Telerobotic Ultrasound System Improves Access to Breast Examination in Rural and Remote Areas: A Prospective and Two-Scenario Study.

OBJECTIVE: Ultrasound (US) plays an important role in the diagnosis and management of breast diseases; however, effective breast US screening is lacking in rural and remote areas. To alleviate this issue, we prospectively evaluated the clinical availability of 5G-based telerobotic US technology for breast examinations in rural and remote areas. METHODS: Between September 2020 and March 2021, 63 patients underwent conventional and telerobotic US examinations in a rural island (Scenario A), while 20 patients underwent telerobotic US examination in a mobile car located in a remote county (Scenario B) in May 2021. The safety, duration, US image quality, consistency, and acceptability of the 5G-based telerobotic US were assessed. RESULTS: In Scenario A, the average duration of the telerobotic US procedure was longer than that of conventional US (10.3 ± 3.3 min vs. 7.6 ± 3.0 min, p = 0.017), but their average imaging scores were similar (4.86 vs. 4.90, p = 0.159). Two cases of gynecomastia, one of lactation mastitis, and one of postoperative breast effusion were diagnosed and 32 nodules were detected using the two US methods. There was good interobserver agreement between the US features and BI-RADS categories of the identical nodules (ICC = 0.795-1.000). In Scenario B, breast nodules were detected in 65% of the patients using telerobotic US. Its average duration was 10.1 ± 2.3 min, and the average imaging score was 4.85. Overall, 90.4% of the patients were willing to choose telerobotic US in the future, and tele-sonologists were satisfied with 85.5% of the examinations. CONCLUSION: The 5G-based telerobotic US system is feasible for providing effective breast examinations in rural and remote areas.

Application of logistic regression, support vector machine and random forest on the effects of titanium dioxide nanoparticles using macroalgae in treatment of certain risk factors associated with kidney injuries.

The use of titanium dioxide (TiO2) nanoparticles in many biological and technical domains is on the rise. There hasn't been much research on the toxicity of titanium dioxide nanoparticles in biological systems, despite their ubiquitous usage. In the current investigation, samples were exposed to various dosages of TiO2 nanoparticles for 4 days, 1 month, and 2 months following treatment. ICP-AES was used to dose TiO2 into the tissues, and the results showed that the kidney had a significant TiO2 buildup. On the other hand, apoptosis of renal tubular cells is one of the most frequent cellular processes contributing to kidney disease (KD). Nevertheless, the impact of macroalgal seaweed extract on KD remains undetermined. In this work, machine learning (ML) approaches have been applied to develop prediction algorithms for acute kidney injury (AKI) by use of titanium dioxide and macroalgae in hospitalized patients. Fifty patients with (AKI) and 50 patients (non-AKI group) have been admitted and considered. Regarding demographic data, and laboratory test data as input parameters, support vector machine (SVM), and random forest (RF) are utilized to build models of AKI prediction and compared to the predictive performance of logistic regression (LR). Due to its strong antioxidant and anti-inflammatory powers, the current research ruled out the potential of using G. oblongata red macro algae as a source for a variety of products for medicinal uses. Despite a high and fast processing of algorithms, logistic regression showed lower overfitting in comparison to SVM, and Random Forest. The dataset is subjected to algorithms, and the categorization of potential risk variables yields the best results. AKI samples showed significant organ defects than non-AKI ones. Multivariate LR indicated that lymphocyte, and myoglobin (MB) ≥ 1000 ng/ml were independent risk parameters for AKI samples. Also, GCS score (95% CI 1.4-8.3 P = 0.014) were the risk parameters for 60-day mortality in samples with AKI. Also, 90-day mortality in AKI patients was significantly high (P < 0.0001). In compared to the control group, there were no appreciable changes in the kidney/body weight ratio or body weight increases. Total thiol levels in kidney homogenate significantly decreased, and histopathological analysis confirmed these biochemical alterations. According to the results, oral TiO2 NP treatment may cause kidney damage in experimental samples.

Working from Home in Urban China during the COVID-19 Pandemic: Assemblages of Work-Family Interference.

During the COVID-19 pandemic, millions of workers globally have been forced to work from home. Empirical data from Chinese cities in the Hubei province reveal work productivity decreased among many respondents working from home in 2020, primarily due to family interference with work. Such interference stems not only from the domain of daily life but also from other family members' e-working and e-learning. Conversely, respondents' work interferes with family; thus, interference operates bi-directionally. This article proposes an analytical framework of work-family interference along three dimensions: work-daily life, work-work, work-study, and each dimension can be understood through four distinct aspects: temporality, physicality, vocality, digitality. Remote workers encounter 'assemblages of work-family interference', consisting of a heterogeneous mixture of these dimensions and aspects. Furthermore, some factors (e.g., living patterns, work culture, digital infrastructure) constrain effective work-family boundary management among urban households.

Demographic Factors Among HIV Confirmed Blood Donors from 2013 to 2021 in Shenzhen

Background New HIV (Human immune deficiency virus) infections are continuously increasing in China and it remains a huge challenge to blood donation. As access to health services has affected by COVID-19 (Corona virus disease 2019) pandemic, a drop in new diagnoses (especially HIV) was observed worldwide. Methods During 2013–2021, 735,247 specimens from unpaid blood donors collected by Shenzhen Blood Center underwent ELISA (Enzyme -linked immunosorbent assay) and NAT (Nucleic acid test). Samples with reactivity results were sent to the Shenzhen Center for Disease Control and Prevention for WB (Western blot). All data were statistically analyzed by the Chi-Square test. Results From 2013 to 2021, the prevalence of HIV among male blood donors was higher than in females (P < 0.01). During the COVID-19 pandemic, the prevalence of HIV among repeat blood donors decreased significantly compared to 2019 (P < 0.05), and the characteristics of blood donors changed in 2020 compared to 2019 and 2021. Conclusion The high proportion of female blood donors would help prevent HIV from getting into the blood supply. The COVID-19 pandemic affected the demographics of blood donors as well as the prevalence of HIV among repeat blood donors. An increased number of repeat blood donors can help decrease the risk of HIV transfusion transmission during the epidemic.

Characteristics of and User Engagement With Antivaping Posts on Instagram: Observational Study.

BACKGROUND: Although government agencies acknowledge that messages about the adverse health effects of e-cigarette use should be promoted on social media, effectively delivering those health messages is challenging. Instagram is one of the most popular social media platforms among US youth and young adults, and it has been used to educate the public about the potential harm of vaping through antivaping posts. OBJECTIVE: We aim to analyze the characteristics of and user engagement with antivaping posts on Instagram to inform future message development and information delivery. METHODS: A total of 11,322 Instagram posts were collected from November 18, 2019, to January 2, 2020, by using antivaping hashtags including #novape, #novaping, #stopvaping, #dontvape, #antivaping, #quitvaping, #antivape, #stopjuuling, #dontvapeonthepizza, and #escapethevape. Among those posts, 1025 posts were randomly selected and 500 antivaping posts were further identified by hand coding. The image type, image content, and account type of antivaping posts were hand coded, the text information in the caption was explored by topic modeling, and the user engagement of each category was compared. RESULTS: Analyses found that antivaping images of the educational/warning type were the most common (253/500; 50.6%). The average likes of the educational/warning type (15 likes/post) were significantly lower than the catchphrase image type (these emphasized a slogan such as "athletesdontvape" in the image; 32.5 likes/post; P<.001). The majority of the antivaping posts contained the image content element text (n=332, 66.4%), followed by the image content element people/person (n=110, 22%). The images containing people/person elements (32.8 likes/post) had more likes than the images containing other elements (13.8-21.1 likes/post). The captions of the antivaping Instagram posts covered topics including "lung health," "teen vaping," "stop vaping," and "vaping death cases." Among the 500 antivaping Instagram posts, while most posts were from the antivaping community (n=177, 35.4%) and personal account types (n=182, 36.4%), the antivaping community account type had the highest average number of posts (1.69 posts/account). However, there was no difference in the number of likes among different account types. CONCLUSIONS: Multiple features of antivaping Instagram posts may be related to user engagement and perception. This study identified the critical elements associated with high user engagement, which could be used to design antivaping posts to deliver health-related information more efficiently.

Imported cold chain food traceability management platform and innovative application

In 2020, the COVID-19 pandemic broke out globally, and cold-chain food has become the key point of the task to prevent the coronavirus from spreading within the city/region or beyond. Using information tools like establishing a national cold-chain traceability management platform to control the risk of imported cold-chain food has become an important topic at present. The paper focuses on the technology used by provinces and cities in cold-chain traceability, and combined with the actual needs, analyzes the advantages of heterogeneous identification technology. This paper starts from the present situation, introducing the technical roadmap selecting of traceability of imported cold-chain food and elaborating the data circulation structure of traceability of imported cold-chain food. Based on that, this paper introduces the national traceability platform of imported cold-chain food and its core functions based on heterogeneous identification. Through the construction of a three-level framework with the national cold-chain traceability management platform, to make sure the cold chain food can be traceable and be manageable. Meanwhile, through the two applications of inter-provincial confirmation and data verification, the national management effect of imported cold chain food is improved. [Outlook] Currently, the platform mainly focuses on imported livestock, poultry and aquatic products. In the future, the traceability scope may be gradually expanded to help improve the management effect. Establishing the imported cold-chain food traceability platform has a good effect on improving the information management level and promoting the traceability efficiency of problematic food, which is conducive to ensuring food safety.

Interferon α-2b spray shortened viral shedding time of SARS-CoV-2 Omicron variant: An open prospective cohort study.

Background: The Omicron SARS-CoV-2 variant has spread quickly worldwide due to its effects on virus transmission and vaccine effectiveness. Interferon(IFN) has been shown to have a protective effect against SARS-CoV because of its broad antiviral activity. This study aimed to analyze the treatment effects of IFN α-2b spray in virus clearance of the Omicron SARS-CoV-2 variant. Methods: We examined the effectiveness and safety of IFN α-2b spray in Shanghai, China, with participants infected with the Omicron SARS-CoV-2 variant in an open, prospective cohort study from April 16th to May 5th, 2022. Results: A total of 871 confirmed patients were enrolled in this study. Four hundred and thirteen patients were allocated to the IFN α-2b spray group, and 458 patients were allocated to the control group. The viral shedding time was significantly different between experimental group and control group (11.90 vs.12.58, P <0.05). In the experimental group, the median administration time since the first positive test for SARS-CoV-2 was three days, ranging from 0 to 15 days. There was no obvious adverse effect associated with the spray of IFN α-2b. The univariate Cox regression analysis revealed that the administration time since the first positive test ≤3 days was a protective factor associated with viral shedding time (HR 0.81 95% CI 0.74-0.87, P <0.05). Subgroup analysis showed that the viral shedding time was 10.41 (4.00-16.00) days in the ≤3 days group, which was significantly less than that in the control group (12.58, 95% CI: 7.00-19.15, P <0.0001) and in the >3 days group (13.56, 95%CI: 7.00-22.25, P <0.0001). Conclusions: IFN α-2b spray shortened the viral shedding time of the Omicron SARS-CoV-2 variant when administrated within three days since the first positive test for SARS-CoV-2.

Health Services Utilization in China during the COVID-19 Pandemic: Results from a Large-Scale Online Survey.

Timely access to essential health services is a concern as COVID-19 continues. This study aimed to investigate health services utilization during the first wave of the pandemic in China. A cross-sectional online survey was conducted using a self-administrated questionnaire in March 2020. Descriptive statistics and logistic regression were used for data analysis. A total of 4744 respondents were included, with 52.00% reporting affected services utilization. Clinical testing (68.14%) and drug purchase (49.61%) were the most affected types. Higher education level, being married, chronic disease, frequently visiting a provincial medical institution, spending more time on pandemic-related information, perception of high-risk of infection, perception of large health impact of the pandemic, and anxiety/depression were significant predictors for reporting affected services utilization. For the 431 chronic disease respondents, 62.18% reported interruption, especially for drug purchase (58.58%). Affected health services utilization was reported during the first wave of the pandemic in China, especially for those with higher education level, chronic diseases, and COVID-19 related concerns. Enhancing primary healthcare, use of telehealth, extended prescription, and public communication were countermeasures undertaken by China during the rapid rise period. As COVID-19 progresses, the changing disease characteristics, adapted health system, along with enhanced public awareness/knowledge should be considered for the evolution of health services utilization, and further investigation is needed.

The COVID-19 Pandemic and Mental Health Concerns on Twitter in the United States

Background During the COVID-19 pandemic, mental health concerns (such as fear and loneliness) have been actively discussed on social media. We aim to examine mental health discussions on Twitter during the COVID-19 pandemic in the US and infer the demographic composition of Twitter users who had mental health concerns. Methods COVID-19-related tweets from March 5th, 2020, to January 31st, 2021, were collected through Twitter streaming API using keywords (i.e., “corona,” “covid19,” and “covid”). By further filtering using keywords (i.e., “depress,” “failure,” and “hopeless”), we extracted mental health-related tweets from the US. Topic modeling using the Latent Dirichlet Allocation model was conducted to monitor users' discussions surrounding mental health concerns. Deep learning algorithms were performed to infer the demographic composition of Twitter users who had mental health concerns during the pandemic. Results We observed a positive correlation between mental health concerns on Twitter and the COVID-19 pandemic in the US. Topic modeling showed that “stay-at-home,” “death poll,” and “politics and policy” were the most popular topics in COVID-19 mental health tweets. Among Twitter users who had mental health concerns during the pandemic, Males, White, and 30-49 age group people were more likely to express mental health concerns. In addition, Twitter users from the east and west coast had more mental health concerns. Conclusions The COVID-19 pandemic has a significant impact on mental health concerns on Twitter in the US. Certain groups of people (such as Males and White) were more likely to have mental health concerns during the COVID-19 pandemic.

The associations between COVID-19 vaccination and psychological disorders among healthcare workers in China.

INTRODUCTION: COVID-19 has caused an unprecedented psychological affection that might impact the nationwide vaccination program in China. This study was to explore the association between COVID-19 vaccination and psychological disorders among healthcare workers. METHODS: The study included 1571 healthcare workers from an anonymous online survey. Participants' sociodemographic characteristics, uptake data for the COVID-19 vaccine, and scores of the Depression, Anxiety, and Stress Scale (DASS-21) were collected. Nonparametric tests were conducted to compare the mean scores of DASS-21 between different subgroups. The potential factors related to psychological disorders of healthcare workers were analyzed using logistic regression. RESULTS: The vaccination rate was 69.6 %, the incidence of vaccine-related adverse events was 35.13 %, and the prevalence of depression, anxiety, and stress were 24.8 %, 32 %, and 33.4 % in this study, respectively. Compared to vaccinated participants (single-dose and double-dose vaccines), unvaccinated participants got significantly higher mean scores of DASS-21 (p < 0.05 for all). Vaccinated participants who suffered no adverse events scored significantly lower than those who suffered 1-2 or ≥3 adverse events (p < 0.05 for all). Vaccination was negatively associated with higher depression, anxiety, and stress, however, the number of vaccine-related adverse events was positively associated with them. LIMITATIONS: As this is a cross-sectional study, we could only speculate on the causality. CONCLUSIONS: An obvious impact of the psychological disorders on the COVID-19 vaccine coverage and related adverse events was detected in this study. Public health agencies should attach great importance to the psychological states of our citizens before getting vaccinated.

Mental Health Research During the COVID-19 Pandemic: Focuses and Trends.

Background: The COVID-19 pandemic has profoundly influenced the world. In wave after wave, many countries suffered from the pandemic, which caused social instability, hindered global growth, and harmed mental health. Although research has been published on various mental health issues during the pandemic, some profound effects on mental health are difficult to observe and study thoroughly in the short term. The impact of the pandemic on mental health is still at a nascent stage of research. Based on the existing literature, we used bibliometric tools to conduct an overall analysis of mental health research during the COVID-19 pandemic. Method: Researchers from universities, hospitals, communities, and medical institutions around the world used questionnaire surveys, telephone-based surveys, online surveys, cross-sectional surveys, systematic reviews and meta-analyses, and systematic umbrella reviews as their research methods. Papers from the three academic databases, Web of Science (WOS), ProQuest Academic Database (ProQuest), and China National Knowledge Infrastructure (CNKI), were included. Their previous research results were systematically collected, sorted, and translated and CiteSpace 5.1 and VOSviewers 1.6.13 were used to conduct a bibliometric analysis of them. Result: Authors with papers in this field are generally from the USA, the People's Republic of China, the UK, South Korea, Singapore, and Australia. Huazhong University of Science and Technology, Hong Kong Polytechnic University, and Shanghai Jiao Tong University are the top three institutions in terms of the production of research papers on the subject. The University of Toronto, Columbia University, and the University of Melbourne played an important role in the research of mental health problems during the COVID-19 pandemic. The numbers of related research papers in the USA and China are significantly larger than those in the other countries, while co-occurrence centrality indexes in Germany, Italy, England, and Canada may be higher. Conclusion: We found that the most mentioned keywords in the study of mental health research during the COVID-19 pandemic can be divided into three categories: keywords that represent specific groups of people, that describe influences and symptoms, and that are related to public health policies. The most-cited issues were about medical staff, isolation, psychological symptoms, telehealth, social media, and loneliness. Protection of the youth and health workers and telemedicine research are expected to gain importance in the future.

Analysis of mechanisms of Shenhuang Granule in treating severe COVID-19 based on network pharmacology and molecular docking.

OBJECTIVE: Severe cases of coronavirus disease 2019 (COVID-19) are expected to have a worse prognosis than mild cases. Shenhuang Granule (SHG) has been shown to be a safe and effective treatment for severe COVID-19 in a previous randomized clinical trial, but the active chemical constituents and underlying mechanisms of action remain unknown. The goal of this study is to explore the chemical basis and mechanisms of SHG in the treatment of severe COVID-19, using network pharmacology. METHODS: Ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry was employed to screen chemical constituents of SHG. Putative therapeutic targets were predicted by searching traditional Chinese medicine system pharmacology database and analysis platform, SwissTargetPrediction, and Gene Expression Omnibus (GEO) databases. The target protein-protein interaction network and enrichment analysis were performed to investigate the hub genes and presumptive mechanisms. Molecular docking and molecular dynamics simulations were used to verify the stability and interaction between the key chemical constituents of SHG and COVID-19 protein targets. RESULTS: Forty-five chemical constituents of SHG were identified along with 131 corresponding therapeutic targets, including hub genes such as HSP90AA1, MMP9, CXCL8, PTGS2, IFNG, DNMT1, TYMS, MDM2, HDAC3 and ABCB1. Functional enrichment analysis indicated that SHG mainly acted on the neuroactive ligand-receptor interaction, calcium signaling pathway and cAMP signaling pathway. Molecular docking showed that the key constituents had a good affinity with the severe acute respiratory syndrome coronavirus 2 protein targets. Molecular dynamics simulations indicated that ginsenoside Rg4 formed a stable protein-ligand complex with helicase. CONCLUSION: Multiple components of SHG regulated multiple targets to inhibit virus invasion and cytokine storm through several signaling pathways; this provides a scientific basis for clinical applications and further experiments.

Factors Influencing Post-traumatic Stress Symptoms in Chinese Adolescents During the COVID-19 Pandemic.

To investigate the prevalence of post-traumatic stress symptoms (PTSSs) and analyze the influencing factors of PTSS among adolescents in a large sample study during the COVID-19 pandemic, we did a cross-sectional study by collecting demographic data and mental health measurements from a large group of 175,318 adolescents in 32 Chinese provinces and autonomous regions, using the Impact of Event Scale-Revised (IES-R) that was used to measure the PTSS of the participants. The results showed that the prevalence of PTSS was 35.7% in Chinese adolescents during the COVID-19 pandemic. Binary logistic regression analysis showed that, for the personal risk factors, the older age, female gender, the personality domains of extroversion, the irregular sleep schedule, the lack of aerobic exercise, and the lack of peer support were associated with the higher levels of PTSS. The family subjective and objective factors were associated with higher levels of PTSS. Our findings suggested that family factors are the most important factors that affect Chinese adolescents' PTSS due to the longtime home quarantine.

Survivorship Analysis in Asymptomatic COVID-19+ Hip Fracture Patients: Is There an Increase in Mortality?

Purpose: Mortality rates following hip fracture surgery have been well-studied. This study was conducted to examine mortality rates in asymptomatic patients presenting for treatment of acute hip fractures with concurrent positive COVID-19(+) tests compared to those with negative COVID-19(-) tests. Materials and Methods: A total of 149 consecutive patients undergoing hip fracture surgery during the COVID-19 pandemic at two academic medical centers were reviewed retrospectively. Patients were divided into two groups for comparative analysis: one group included asymptomatic patients with COVID-19+ tests versus COVID-19- tests. The primary outcome was mortality at 30-days and 90-days. Results: COVID-19+ patients had a higher mortality rate than COVID-19- patients at 30-days (26.7% vs 6.0%, P=0.005) and 90-days (41.7% vs 17.2%, P=0.046) and trended towards an increased length of hospital stay (10.1±6.2 vs 6.8±3.8 days, P=0.06). COVID-19+ patients had more pre-existing respiratory disease (46.7% vs 11.2%, P=0.0002). Results of a Cox regression analysis showed an increased risk of mortality at 30-days and 90-days from COVID-19+ status alone without an increased risk of death in patients with pre-existing chronic respiratory disease. Conclusion: Factors including time to surgery, age, preexisting comorbidities, and postoperative ambulatory status have been proven to affect mortality and complications in hip fracture patients; however, a positive COVID-19 test result adds another variable to this process. Implementation of protocols that will promote prompt orthogeriatric assessments, expedite patient transfer, limit operating room traffic, and optimize anesthesia time can preserve the standard of care in this unique patient population.

New C9 -Monoterpenoid Alkaloids Featuring a Rare Skeleton with Anti-Inflammatory and Antiviral Activities from Forsythia suspensa.

Forsyqinlingines C (1) and D (2), two C9 -monoterpenoid alkaloids bearing a rare skeleton, were isolated from the ripe fruits of Forsythia suspensa. Their structures, including absolute configurations, were fully elucidated by extensive spectroscopic data and ECD experiments. The plausible biogenetic pathway for compounds 1 and 2 was also proposed. In vitro, two C9 -monoterpenoid alkaloids showed anti-inflammatory activity performed by the inhibitory effect on the release of ß-glucuronidase in rat polymorphonuclear leukocytes (PMNs), as well as antiviral activity against influenza A (H1N1) virus and respiratory syncytial virus (RSV).

Efficacy and potential mechanisms of Chinese herbal compounds in coronavirus disease 2019: advances of laboratory and clinical studies.

The Coronavirus disease 2019 (COVID-19) pandemic is still spread and has made a severe public health threat around the world. To improve disease progression, emerging Chinese herbal compounds were used in clinical practice and some agents have proven beneficial in treating COVID-19. Here, the relevant literature from basic researches to clinical application were identified and comprehensively assessed. A variety of Chinese herbal compounds have been reported to be effective in improving symptoms and outcomes in patients with COVID-19, particularly together with routine treatment strategy. The pharmacological activities were mainly attributed to the relief of clinical symptoms, inhibition of cytokine storm, and improvement of organ function. Besides, the development of novel antiviral drugs from medicinal herbs were further discussed. The updated laboratory and clinical studies provided the evidence of Chinese herbal compounds such as Lianhua Qingwen prescription, Shufeng Jiedu prescription, and Qingfei Paidu Tang for the relief of COVID-19. However, both of the randomized controlled trials and real world researches need to be done for supporting the evidence including the efficacy and safety in fighting COVID-19.

Global economic performance and natural resources commodity prices volatility: Evidence from pre and post COVID-19 era.

The emergence of Covid-19 has created a global panic that affects global economic performance and causes natural resources commodity price volatility. In this regard, the current research study investigated the nexus of natural resource commodity price volatility and global economic performance from January 01, 2019, to July 01, 2021. Using the wavelet power spectrum and wavelet coherence approaches, the empirical findings reveal that only the natural resource commodity prices are vulnerable. However, no vulnerability has been observed for the global economic performance. Additionally, the wavelet coherence reveals that there is no long-run or the short run causal association between these two variables. Moreover, the Breitung-Candelon spectral Granger causality test confirms no causal relationship between natural resource commodity price volatility and global economic performance. Based on the empirical findings, this study provides some relevant policy implications.