Multi-omics blood atlas reveals unique features of immune and platelet responses to SARS-CoV-2 Omicron breakthrough infection.

Although host responses to the ancestral SARS-CoV-2 strain are well described, those to the new Omicron variants are less resolved. We profiled the clinical phenomes, transcriptomes, proteomes, metabolomes, and immune repertoires of >1,000 blood cell or plasma specimens from SARS-CoV-2 Omicron patients. Using in-depth integrated multi-omics, we dissected the host response dynamics during multiple disease phases to reveal the molecular and cellular landscapes in the blood. Specifically, we detected enhanced interferon-mediated antiviral signatures of platelets in Omicron-infected patients, and platelets preferentially formed widespread aggregates with leukocytes to modulate immune cell functions. In addition, patients who were re-tested positive for viral RNA showed marked reductions in B cell receptor clones, antibody generation, and neutralizing capacity against Omicron. Finally, we developed a machine learning model that accurately predicted the probability of re-positivity in Omicron patients. Our study may inspire a paradigm shift in studying systemic diseases and emerging public health concerns.

Plasma metabolomic characterization of SARS-CoV-2 Omicron infection.

Omicron variants of SARS-CoV-2 have spread rapidly worldwide; however, most infected patients have mild or no symptoms. This study aimed to understand the host response to Omicron infections by performing metabolomic profiling of plasma. We observed that Omicron infections triggered an inflammatory response and innate immune, and adaptive immunity was suppressed, including reduced T-cell response and immunoglobulin antibody production. Similar to the original SARS-CoV-2 strain circulating in 2019, the host developed an anti-inflammatory response and accelerated energy metabolism in response to Omicron infection. However, differential regulation of macrophage polarization and reduced neutrophil function has been observed in Omicron infections. Interferon-induced antiviral immunity was not as strong in Omicron infections as in the original SARS-CoV-2 infections. The host response to Omicron infections increased antioxidant capacity and liver detoxification more than in the original strain. Hence, these findings suggest that Omicron infections cause weaker inflammatory alterations and immune responses than the original SARS-CoV-2 strain.

Thymic tuft cells: potential "regulators" of non-mucosal tissue development and immune response.

As the leading central immune organ, the thymus is where T cells differentiate and mature, and plays an essential regulatory role in the adaptive immune response. Tuft cells, as chemosensory cells, were first found in rat tracheal epithelial, later gradually confirmed to exist in various mucosal and non-mucosal tissues. Although tuft cells are epithelial-derived, because of their wide heterogeneity, they show functions similar to cholinergic and immune cells in addition to chemosensory ability. As newly discovered non-mucosal tuft cells, thymic tuft cells have been demonstrated to be involved in and play vital roles in immune responses such as antigen presentation, immune tolerance, and type 2 immunity. In addition to their unique functions in the thymus, thymic tuft cells have the characteristics of peripheral tuft cells, so they may also participate in the process of tumorigenesis and virus infection. Here, we review tuft cells' characteristics, distribution, and potential functions. More importantly, the potential role of thymic tuft cells in immune response, tumorigenesis, and severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) infection was summarized and discussed.

Amplification-free CRISPR/Cas detection technology: challenges, strategies, and perspectives.

Rapid and accurate molecular diagnosis is a prerequisite for precision medicine, food safety, and environmental monitoring. The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas)-based detection, as a cutting-edged technique, has become an immensely effective tool for molecular diagnosis because of its outstanding advantages including attomolar level sensitivity, sequence-targeted single-base specificity, and rapid turnover time. However, the CRISPR/Cas-based detection methods typically require a pre-amplification step to elevate the concentration of the analyte, which may produce non-specific amplicons, prolong the detection time, and raise the risk of carryover contamination. Hence, various strategies for target amplification-free CRISPR/Cas-based detection have been developed, aiming to minimize the sensitivity loss due to lack of pre-amplification, enable detection for non-nucleic acid targets, and facilitate integration in portable devices. In this review, the current status and challenges of target amplification-free CRISPR/Cas-based detection are first summarized, followed by highlighting the four main strategies to promote the performance of target amplification-free CRISPR/Cas-based technology. Furthermore, we discuss future perspectives that will contribute to developing more efficient amplification-free CRISPR/Cas detection systems.

Towards a global One Health index: a potential assessment tool for One Health performance.

BACKGROUND: A One Health approach has been increasingly mainstreamed by the international community, as it provides for holistic thinking in recognizing the close links and inter-dependence of the health of humans, animals and the environment. However, the dearth of real-world evidence has hampered application of a One Health approach in shaping policies and practice. This study proposes the development of a potential evaluation tool for One Health performance, in order to contribute to the scientific measurement of One Health approach and the identification of gaps where One Health capacity building is most urgently needed. METHODS: We describe five steps towards a global One Health index (GOHI), including (i) framework formulation; (ii) indicator selection; (iii) database building; (iv) weight determination; and (v) GOHI scores calculation. A cell-like framework for GOHI is proposed, which comprises an external drivers index (EDI), an intrinsic drivers index (IDI) and a core drivers index (CDI). We construct the indicator scheme for GOHI based on this framework after multiple rounds of panel discussions with our expert advisory committee. A fuzzy analytical hierarchy process is adopted to determine the weights for each of the indicators. RESULTS: The weighted indicator scheme of GOHI comprises three first-level indicators, 13 second-level indicators, and 57 third-level indicators. According to the pilot analysis based on the data from more than 200 countries/territories the GOHI scores overall are far from ideal (the highest score of 65.0 out of a maximum score of 100), and we found considerable variations among different countries/territories (31.8-65.0). The results from the pilot analysis are consistent with the results from a literature review, which suggests that a GOHI as a potential tool for the assessment of One Health performance might be feasible. CONCLUSIONS: GOHI-subject to rigorous validation-would represent the world's first evaluation tool that constructs the conceptual framework from a holistic perspective of One Health. Future application of GOHI might promote a common understanding of a strong One Health approach and provide reference for promoting effective measures to strengthen One Health capacity building. With further adaptations under various scenarios, GOHI, along with its technical protocols and databases, will be updated regularly to address current technical limitations, and capture new knowledge.

Modeling Kaempferol as a Potential Pharmacological Agent for COVID-19/PF Co-Occurrence Based on Bioinformatics and System Pharmacological Tools.

Objective: People suffering from coronavirus disease 2019 (COVID-19) are prone to develop pulmonary fibrosis (PF), but there is currently no definitive treatment for COVID-19/PF co-occurrence. Kaempferol with promising antiviral and anti-fibrotic effects is expected to become a potential treatment for COVID-19 and PF comorbidities. Therefore, this study explored the targets and molecular mechanisms of kaempferol against COVID-19/PF co-occurrence by bioinformatics and network pharmacology. Methods: Various open-source databases and Venn Diagram tool were applied to confirm the targets of kaempferol against COVID-19/PF co-occurrence. Protein-protein interaction (PPI), MCODE, key transcription factors, tissue-specific enrichment, molecular docking, Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to clarify the influential molecular mechanisms of kaempferol against COVID-19 and PF comorbidities. Results: 290 targets and 203 transcription factors of kaempferol against COVID-19/PF co-occurrence were captured. Epidermal growth factor receptor (EGFR), proto-oncogene tyrosine-protein kinase SRC (SRC), mitogen-activated protein kinase 3 (MAPK3), mitogen-activated protein kinase 1 (MAPK1), mitogen-activated protein kinase 8 (MAPK8), RAC-alpha serine/threonine-protein kinase (AKT1), transcription factor p65 (RELA) and phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) were identified as the most critical targets, and kaempferol showed effective binding activities with the above critical eight targets. Further, anti-COVID-19/PF co-occurrence effects of kaempferol were associated with the regulation of inflammation, oxidative stress, immunity, virus infection, cell growth process and metabolism. EGFR, interleukin 17 (IL-17), tumor necrosis factor (TNF), hypoxia inducible factor 1 (HIF-1), phosphoinositide 3-kinase/AKT serine/threonine kinase (PI3K/AKT) and Toll-like receptor signaling pathways were identified as the key anti-COVID-19/PF co-occurrence pathways. Conclusion: Kaempferol is a candidate treatment for COVID-19/PF co-occurrence. The underlying mechanisms may be related to the regulation of critical targets (EGFR, SRC, MAPK3, MAPK1, MAPK8, AKT1, RELA, PIK3CA and so on) and EGFR, IL-17, TNF, HIF-1, PI3K/AKT and Toll-like receptor signaling pathways. This study contributes to guiding development of new drugs for COVID-19 and PF comorbidities.

COVID-19 Breakthrough Infections in Vaccinated Kidney Transplant Recipients.

Coronavirus disease 2019 (COVID-19) is associated with increased morbidity and mortality among kidney transplant recipients (KTRs). The administration of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination is the only reliable strategy to prevent COVID-19 and alleviate the severity of COVID-19 in this particular population. The aim of this article was to evaluate the clinical protection by vaccines (breakthrough infections, deaths, and hospitalizations) in KTRs. There were 135 KTRs with COVID-19 breakthrough infections for whom patient-level data were available in PubMed and Web of Science. There was a male predominance (61.4%), 97 were given the standard vaccination regimen, and 38 received three or four doses of the vaccine. The median age was 59.0 (IQR: 49.0-69.0) years. A total of 67 patients were hospitalized, and 10 patients died. In 72.6% of cases, triple-maintenance immunosuppression was employed. The deceased patients were older than the survivors (p < 0.05); an age over 60 years was a risk factor for death (p < 0.05). The KTRs with booster vaccines had a longer time interval from the last vaccine to COVID-19 infection and lower hospitalization rates than the individuals who received the standard vaccination regimen (33.3% vs. 54.8%, p < 0.05). The hospitalized patients were older than the outpatients (p < 0.05). Among 16,820 fully vaccinated or boosted KTRs from 14 centers, there were 633 breakthrough infections (3.58%) and 73 associated deaths (0.41%). The center-level breakthrough infection rates varied from 0.21% to 9.29%. These findings highlight the need for booster doses for KTRs. However, more research is needed to define the long-term effectiveness and immunogenicity of booster doses and to identify methods to boost the protective response to vaccination in these immunocompromised patients.

Clustered Regularly Interspaced short palindromic repeats-Based Microfluidic System in Infectious Diseases Diagnosis: Current Status, Challenges, and Perspectives.

Mitigating the spread of global infectious diseases requires rapid and accurate diagnostic tools. Conventional diagnostic techniques for infectious diseases typically require sophisticated equipment and are time consuming. Emerging clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated proteins (Cas) detection systems have shown remarkable potential as next-generation diagnostic tools to achieve rapid, sensitive, specific, and field-deployable diagnoses of infectious diseases, based on state-of-the-art microfluidic platforms. Therefore, a review of recent advances in CRISPR-based microfluidic systems for infectious diseases diagnosis is urgently required. This review highlights the mechanisms of CRISPR/Cas biosensing and cutting-edge microfluidic devices including paper, digital, and integrated wearable platforms. Strategies to simplify sample pretreatment, improve diagnostic performance, and achieve integrated detection are discussed. Current challenges and future perspectives contributing to the development of more effective CRISPR-based microfluidic diagnostic systems are also proposed.

Stock Market Reaction to the Announcement of the COVID-19 Lockdown: Evidence from Healthcare Companies in Malaysia.

The sudden global pandemic of COVID-19 occurred in Malaysia at the beginning of new 2020, which increased the uncertainty of the economy. As a highly demanded industry during diseases, COVID-19-related news had a mixed influence on investors' confidence in the healthcare industry, so the short-term market reaction of the Malaysian healthcare industry is investigated during this unfolding event. This paper examines whether the "lockdown" suppressed the influence of COVID-19 pandemic on stock performance in 12 listed healthcare companies in Malaysia. We consider the "lockdown" order has different impacts on samples. The hardest hit among the four events is the first announcement of lockdown, whose cumulative average abnormal return (CAAR) is negative (CAAR<0), for its strict movement control. However, the impacts of the following three lockdown events are positive and less severe as the market gradually digest these kinds of news and the deregulation of movement control. Previous studies have justified the influence of disease outbreaks on the stock market; however, this study compensates for other studies by employing the event study methodology (ESM) approach to provide the first empirical evidence of the unprecedented influence of "lockdown" on Malaysian healthcare stock market. This study has practical implications for Malaysian financial markets that the lockdown orders matter for the Malaysian healthcare industry. The empirical results show that the stock market has positively affected the lockdown announcement after the first event. In turn, the policymakers could draw on these results related to stock performance to modify the regulations in the healthcare industry.

Stock Market Reaction to the Announcement of the COVID-19 Lockdown: Evidence from Healthcare Companies in Malaysia

The sudden global pandemic of COVID-19 occurred in Malaysia at the beginning of new 2020, which increased the uncertainty of the economy. As a highly demanded industry during diseases, COVID-19-related news had a mixed influence on investors' confidence in the healthcare industry, so the short-term market reaction of the Malaysian healthcare industry is investigated during this unfolding event. This paper examines whether the “lockdown” suppressed the influence of COVID-19 pandemic on stock performance in 12 listed healthcare companies in Malaysia. We consider the “lockdown” order has different impacts on samples. The hardest hit among the four events is the first announcement of lockdown, whose cumulative average abnormal return (CAAR) is negative (CAAR<0), for its strict movement control. However, the impacts of the following three lockdown events are positive and less severe as the market gradually digest these kinds of news and the deregulation of movement control. Previous studies have justified the influence of disease outbreaks on the stock market;however, this study compensates for other studies by employing the event study methodology (ESM) approach to provide the first empirical evidence of the unprecedented influence of “lockdown” on Malaysian healthcare stock market. This study has practical implications for Malaysian financial markets that the lockdown orders matter for the Malaysian healthcare industry. The empirical results show that the stock market has positively affected the lockdown announcement after the first event. In turn, the policymakers could draw on these results related to stock performance to modify the regulations in the healthcare industry.

Epidemiological and virological surveillance of influenza viruses in China during 2020-2021.

BACKGROUND: During the coronavirus disease 2019 (COVID-19) pandemic, seasonal influenza activity declined globally and remained below previous seasonal levels, but intensified in China since 2021. Preventive measures to COVID-19 accompanied by different epidemic characteristics of influenza in different regions of the world. To better respond to influenza outbreaks under the COVID-19 pandemic, we analyzed the epidemiology, antigenic and genetic characteristics, and antiviral susceptibility of influenza viruses in the mainland of China during 2020-2021. METHODS: Respiratory specimens from influenza like illness cases were collected by sentinel hospitals and sent to network laboratories in Chinese National Influenza Surveillance Network. Antigenic mutation analysis of influenza virus isolates was performed by hemagglutination inhibition assay. Next-generation sequencing was used for genetic analyses. We also conducted molecular characterization and phylogenetic analysis of circulating influenza viruses. Viruses were tested for resistance to antiviral medications using phenotypic and/or sequence-based methods. RESULTS: In the mainland of China, influenza activity recovered in 2021 compared with that in 2020 and intensified during the traditional influenza winter season, but it did not exceed the peak in previous years. Almost all viruses isolated during the study period were of the B/Victoria lineage and were characterized by genetic diversity, with the subgroup 1A.3a.2 viruses currently predominated. 37.8% viruses tested were antigenically similar to reference viruses representing the components of the vaccine for the 2020-2021 and 2021-2022 Northern Hemisphere influenza seasons. In addition, China has a unique subgroup of 1A.3a.1 viruses. All viruses tested were sensitive to neuraminidase inhibitors and endonuclease inhibitors, except two B/Victoria lineage viruses identified to have reduced sensitivity to neuraminidase inhibitors. CONCLUSIONS: Influenza activity increased in the mainland of China in 2021, and caused flu season in the winter of 2021-2022. Although the diversity of influenza (sub)type decreases, B/Victoria lineage viruses show increased genetic and antigenic diversity. The world needs to be fully prepared for the co-epidemic of influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus globally.

Modeling Kaempferol as a Potential Pharmacological Agent for COVID-19/PF Co-Occurrence Based on Bioinformatics and System Pharmacological Tools

Objective: People suffering from coronavirus disease 2019 (COVID-19) are prone to develop pulmonary fibrosis (PF), but there is currently no definitive treatment for COVID-19/PF co-occurrence. Kaempferol with promising antiviral and anti-fibrotic effects is expected to become a potential treatment for COVID-19 and PF comorbidities. Therefore, this study explored the targets and molecular mechanisms of kaempferol against COVID-19/PF co-occurrence by bioinformatics and network pharmacology. Methods: Various open-source databases and Venn Diagram tool were applied to confirm the targets of kaempferol against COVID-19/PF co-occurrence. Protein-protein interaction (PPI), MCODE, key transcription factors, tissue-specific enrichment, molecular docking, Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to clarify the influential molecular mechanisms of kaempferol against COVID-19 and PF comorbidities. Results: 290 targets and 203 transcription factors of kaempferol against COVID-19/PF co-occurrence were captured. Epidermal growth factor receptor (EGFR), proto-oncogene tyrosine-protein kinase SRC (SRC), mitogen-activated protein kinase 3 (MAPK3), mitogen-activated protein kinase 1 (MAPK1), mitogen-activated protein kinase 8 (MAPK8), RAC-alpha serine/threonine-protein kinase (AKT1), transcription factor p65 (RELA) and phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) were identified as the most critical targets, and kaempferol showed effective binding activities with the above critical eight targets. Further, anti-COVID-19/PF co-occurrence effects of kaempferol were associated with the regulation of inflammation, oxidative stress, immunity, virus infection, cell growth process and metabolism. EGFR, interleukin 17 (IL-17), tumor necrosis factor (TNF), hypoxia inducible factor 1 (HIF-1), phosphoinositide 3-kinase/AKT serine/threonine kinase (PI3K/AKT) and Toll-like receptor signaling pathways were identified as the key anti-COVID-19/PF co-occurrence pathways. Conclusion: Kaempferol is a candidate treatment for COVID-19/PF co-occurrence. The underlying mechanisms may be related to the regulation of critical targets (EGFR, SRC, MAPK3, MAPK1, MAPK8, AKT1, RELA, PIK3CA and so on) and EGFR, IL-17, TNF, HIF-1, PI3K/AKT and Toll-like receptor signaling pathways. This study contributes to guiding development of new drugs for COVID-19 and PF comorbidities.

Behavioral Intention to Resist the Consumption of Wild Animals in China: Netizen Survey

Since the beginning of 2020, China has banned the consumption of wild animals to combat the spread of zoonoses. Most existing studies focus on the intention and behavior of wildlife consumption and their causes;however, few have looked at public willingness to resist wildlife consumption, as well as the cause and effects of such actions. In this study, a framework for an extended theory of planned behavior was constructed. Based on a 7-point Likert scale, a sample of 1194 respondents from eight provinces across China was obtained through an online survey. Structural equation modeling was used to analyze netizen behavioral intention to resist consuming wild animals and their causes to provide a reference for the implementation and optimization of relevant policies. The study model passed the goodness-of-fit test, confirming the robustness of the results. The results showed that Chinese netizens’ intention to resist consuming wild animals was moderate, with 55.19% willing to participate in activities against it, i.e., it is important to resist eating wild animals as a standard. Attitude, subjective norm, perceived behavioral control, and past experience of the Chinese netizen had significant positive effects on resistance intention, i.e., (1) netizens’ current living area with severe outbreaks were more likely to resist wildlife consumption, (2) highly knowledge level netizens were more likely to resist wildlife consumption than less knowledgeable ones, and (3) lower income level had higher behavioral intentions of netizens. The findings suggest that the government must take a lead role in wildlife protection and strengthen its restrictions, laws, and regulations. The media should also be used to promote conservation and popularize a protective message in favor of wild animals. Public quality and assurance of wildlife protection should be culturally reinforced to effectively ban the illegal trade of wild animals and their products.

The Impact of COVID-19 on Investors' Investment Intention of Sustainability-Related Investment: Evidence from China

This paper investigates how investors respond to the COVID-19 pandemic, particularly regarding their intention to invest in sustainability-related investment (SRI) funds. We conduct two experiments online with participants who have experience with stock and fund investments. The first one includes 292 participants, which aims to explore investors' attitudes and investment intention of different sustainability-related components, and the second one includes 432 participants, which aims to examine how the COVID-19 pandemic affects individuals' attitudes and investment intention. Our results show that investors tend to invest in SRI funds when the threat of the COVID-19 pandemic is salient. Specifically, we find that although investors perceive environmental issues to be more important than economic and social issues, their investment intention of economic-focused SRI funds significantly increases in response to the COVID-19 pandemic threat. These findings suggest that fund managers can focus on particular types of investors when designing SRI funds, such as active investors with a preference for technical analysis and young female investors with a high level of income and education.

Extracorporeal Hemoperfusion Therapy for Sepsis: Multi-Lamellar Microspheres towards Cascade Endotoxin Removal and Broad-Spectrum Radical Eliminating

Sepsis is a life-threatening condition originated from the accumulation of endotoxin in blood in response to infection (e.g., bacterial infection, COVID-19), and then aggravating by the systemic inflammatory responses, microcirculation disorders and oxidative stress, ultimately resulting in the dysfunction of multiple organs. Herein, advanced multi-lamellar microspheres (CPG-Ln-MSs) with cascade endotoxin adsorption and oxidative stress relief functions are constructed as an alternative adsorbent for hemoperfusion therapy towards sepsis. The CPG-Ln-MSs achieve effective endotoxin absorption (nearly 455.3 EU/g) and show excellent broad-spectrum radical scavenging activity for treating oxidative stress triggered by endotoxin accumulation. Specifically, the structural integrity of the multi-layered structure plays a vital role in promoting the efficiency of endotoxin removal and the subsequently scavenging of reactive oxygen species. Hemoperfusion simulation experiments demonstrate that the CPG-Ln-MSs could effectively remove endotoxin with a ratio of 92%, and the following oxidative stress state could be well alleviated, as confirmed by the reduced H2O2 and MDA levels in septic blood. Furthermore, endogenous antioxidants could be restored (recover SOD and CAT activity to 96.9 and 10.1 U/mL, respectively) and the red blood cells could be protected from oxidative damage. This study provides a promising therapeutic strategy and guides the design of future for septic blood purification.

Impact of Self-Concept, Self-Imagination, and Self-Efficacy on English Language Learning Outcomes Among Blended Learning Students During COVID-19.

The purpose of the present study was to explore the direct influence of self-concept and self-imagination on English language learning outcomes (ELLO). Furthermore, this study examined the mediating role of self-efficacy in the relationship between self-concept, self-imagination, and ELLO. A survey questionnaire of 21 items was used in this study. We distributed the questionnaire through QR code and collected the data from 2,517 participants who enrolled in blended learning courses at the undergraduate level in Chinese universities. The relationship among the variables was measured through SmartPLS-SEM 3.3.3 (partial least squares structural equation modeling). The outcomes of the present study indicated a direct, positive, and significant connection of self-concept, self-imagination, and self-efficacy with ELLO. Looking at indirect influences, self-concept and self-imagination, positive and significant, influence ELLO through self-efficacy. Thus, self-efficacy was indicated to play a mediating role between self-concept, self-imagination and ELLO. We can conclude that self-concept, self-imagination, and self-efficacy are the main predictors of ELLO in blended learning courses during the pandemic. Additionally, self-concept and self-imagination along with the intervening role of self-efficacy, play a more effective role in improving ELLO. Moreover, this study provided some useful, practical implications, and future research directions.

A Practical Strategy for Exploring the Pharmacological Mechanism of Luteolin Against COVID-19/Asthma Comorbidity: Findings of System Pharmacology and Bioinformatics Analysis.

Asthma patients may increase their susceptibility to SARS-CoV-2 infection and the poor prognosis of coronavirus disease 2019 (COVID-19). However, anti-COVID-19/asthma comorbidity approaches are restricted on condition. Existing evidence indicates that luteolin has antiviral, anti-inflammatory, and immune regulation capabilities. We aimed to evaluate the possibility of luteolin evolving into an ideal drug and explore the underlying molecular mechanisms of luteolin against COVID-19/asthma comorbidity. We used system pharmacology and bioinformatics analysis to assess the physicochemical properties and biological activities of luteolin and further analyze the binding activities, targets, biological functions, and mechanisms of luteolin against COVID-19/asthma comorbidity. We found that luteolin may exert ideal physicochemical properties and bioactivity, and molecular docking analysis confirmed that luteolin performed effective binding activities in COVID-19/asthma comorbidity. Furthermore, a protein-protein interaction network of 538 common targets between drug and disease was constructed and 264 hub targets were obtained. Then, the top 6 hub targets of luteolin against COVID-19/asthma comorbidity were identified, namely, TP53, AKT1, ALB, IL-6, TNF, and VEGFA. Furthermore, the enrichment analysis suggested that luteolin may exert effects on virus defense, regulation of inflammation, cell growth and cell replication, and immune responses, reducing oxidative stress and regulating blood circulation through the Toll-like receptor; MAPK, TNF, AGE/RAGE, EGFR, ErbB, HIF-1, and PI3K-AKT signaling pathways; PD-L1 expression; and PD-1 checkpoint pathway in cancer. The possible "dangerous liaison" between COVID-19 and asthma is still a potential threat to world health. This research is the first to explore whether luteolin could evolve into a drug candidate for COVID-19/asthma comorbidity. This study indicated that luteolin with superior drug likeness and bioactivity has great potential to be used for treating COVID-19/asthma comorbidity, but the predicted results still need to be rigorously verified by experiments.

A control strategy for cabin temperature of electric vehicle considering health ventilation for lowering virus infection.

A cooperative control strategy is proposed for the air conditioning (AC) system and ventilation system to reduce the risk of COVID-19 infection and save the energy of the AC system. This strategy integrates the dynamic model of the AC-cabin system, infection risk assessment, model predictive control (MPC) of the thermal environment inside the cabin, and ventilation control that considers passengers' sneezing. Unlike other existing AC system models, the thermal-health model established can describe not only the system performance but also the virus concentration and risk of COVID-19 infection using the Wells-Riley assessment model. Experiments are conducted to verify the prediction accuracy of the AC-cabin model. The results prove that the proposed model can accurately predict the evolution of cabin temperature under different cases. The cooperative control strategy of the AC system integrates the MPC-based refrigeration algorithm for the cabin temperature and intermittent ventilation strategy to reduce the risk of COVID-19 infection. This strategy well balances the control accuracy, energy consumption of the AC system, and the risk of COVID-19 infection, and greatly reduces the infection risk at the expense of a little rise in the energy consumption.

Retrospective analysis of influencing factors on the efficacy of mechanical ventilation in severe and critical COVID-19 patients.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) has spread widely around the world with strong infectivity, rapid mutation and a high mortality rate. Mechanical ventilation has been included in the Diagnosis and Treatment Protocol for Novel Coronavirus Pneumonia (Trial Version 8) as an important treatment for severe and critical COVID-19 patients, but its clinical efficacy in COVID-19 patients is various. Therefore, it is necessary to study the influencing factors on the efficacy of mechanical ventilation in severe and critical COVID-19 patients. AIM: The aim of this study was to determine the influencing factors on the efficacy of mechanical ventilation in severe and critical COVID-19 patients. METHODS: A total of 27 severe and critical COVID-19 patients were enrolled in this study and treated with mechanical ventilation at the Optical Valley Campus of Hubei Maternal and Child Health Care Hospital (Wuhan, Hubei Province) from February 20, 2020 to April 5, 2020. According to the final treatment outcomes, the patients were divided into the "effective group" and "death group." The clinical data of the two groups, such as the treatment process and final outcome, were retrospectively analyzed in order to determine the specific curative effects on the two groups and the reasons for the differences in such curative effects, as well as to explore the factors related to death. RESULTS: This study enrolled 27 severe and critical COVID-19 patients, including 17 males (63.0%) and 10 females (37.0%). Their ages were 74.41 ± 11.73-years-old, and 19 patients (70.4%) were over 70-years-old. Severe COVID-19 patients over 70-years-old who were treated with mechanical ventilation died in 14 cases (82.4%); thus, this was the peak age. A total of 17 patients died of basic disease, 16 of whom had more than two basic diseases. The basic diseases were hypertension, diabetes, and cardiovascular and cerebrovascular diseases. At the same time, 13 patients (76.5%) died from an abnormal increase in blood glucose. Among them, eight had diabetes before contracting COVID-19 and five had a stress-induced increase in blood glucose after contracting COVID-19. Diabetic ketoacidosis occurred in one case. The use of tocilizumab may be a double-edged sword that carries a certain risk in clinical usage. Among the patients who died, 16 (94.1%) went into septic shock at the end. There were significant differences in the degree of infection, cardiac and renal function, and blood glucose between the death group and effective group. CONCLUSION: Age, blood glucose, cardiac and renal function, and inflammatory reaction are important indicators of poor prognosis for mechanical ventilation in severe and critical COVID-19 patients.

Applications of Blockchain in the Medical Field: Narrative Review.

BACKGROUND: As a distributed technology, blockchain has attracted increasing attention from stakeholders in the medical industry. Although previous studies have analyzed blockchain applications from the perspectives of technology, business, or patient care, few studies have focused on actual use-case scenarios of blockchain in health care. In particular, the outbreak of COVID-19 has led to some new ideas for the application of blockchain in medical practice. OBJECTIVE: This paper aims to provide a systematic review of the current and projected uses of blockchain technology in health care, as well as directions for future research. In addition to the framework structure of blockchain and application scenarios, its integration with other emerging technologies in health care is discussed. METHODS: We searched databases such as PubMed, EMBASE, Scopus, IEEE, and Springer using a combination of terms related to blockchain and health care. Potentially relevant papers were then compared to determine their relevance and reviewed independently for inclusion. Through a literature review, we summarize the key medical scenarios using blockchain technology. RESULTS: We found a total of 1647 relevant studies, 60 of which were unique studies that were included in this review. These studies report a variety of uses for blockchain and their emphasis differs. According to the different technical characteristics and application scenarios of blockchain, we summarize some medical scenarios closely related to blockchain from the perspective of technical classification. Moreover, potential challenges are mentioned, including the confidentiality of privacy, the efficiency of the system, security issues, and regulatory policy. CONCLUSIONS: Blockchain technology can improve health care services in a decentralized, tamper-proof, transparent, and secure manner. With the development of this technology and its integration with other emerging technologies, blockchain has the potential to offer long-term benefits. Not only can it be a mechanism to secure electronic health records, but blockchain also provides a powerful tool that can empower users to control their own health data, enabling a foolproof health data history and establishing medical responsibility.