Combination of multiple omics and machine learning identifies diagnostic genes for ARDS and COVID-19 (preprint)

BACKGROUND Acute respiratory distress syndrome (ARDS) is a common acute clinical syndrome of the respiratory system with a high mortality rate and difficult prognosis.COVID-19 is a serious respiratory infectious disease caused by coronaviruses in a global pandemic. Some studies have suggested a possible association between COVID-19 and ARDS, but few studies have investigated the mechanism of interaction between them.METHODS Microarray data of ARDS (GSE32707 and GSE66890) and COVID-19 (GSE213313) were downloaded from the GEO database and searched for common differential genes for enrichment analysis.WGCNA was used to identify co-expression modules and genes associated with ARDS and COVID-19. RF and LASSO were performed for candidate gene identification. Machine learning XGBoost improved the diagnosis of hub genes in ARDS and COVID-19. The degree of immune cell infiltration in ARDS and COVID-19 samples was assessed using the CIBERSORT algorithm, and the relationship between hub genes and infiltrating immune cells was investigated. Changes in pathway activity per cell were visualized using Seurat standard flow down clustering (seurat) to visualize peripheral blood mononuclear cell (PBMC) single-cell RNA sequencing (scRNA-seq) data from patients with sepsis-combined ARDS and patients with sepsis alone.RESULTS Limma difference analysis identified 314 up-regulated genes and 241 down-regulated genes in ARDS and COVID-19.WGCNA identified the purple-red co-expression module as the core module of ARDS and COVID-19. Five candidate genes, namely HIST1H2BK, TCF4, OLFM4, KIF14 and HK1, were screened using two machine learning algorithms, RF and LASSO. XGBoost constructed diagnostic models to evaluate the hub genes with high diagnostic efficacy in ARDS and COVID-19. Single-cell sequencing revealed the presence of alterations in five immune subpopulations, including monocytes, B cells, T cells, NK cells and platelets, with high expression levels and cellular occupancy of TCF4 and HK1, which are involved in oxidative reactions.

SARS-CoV-2 spike protein induces the cytokine release syndrome by stimulating T cells to produce more IL-2 (preprint)

Cytokine release syndrome (CRS) is one of the leading causes of mortality in COVID-19 patients caused by the SARS-CoV-2 coronavirus. However, the mechanism of CRS induced by SARS-CoV-2 is vague. This study shows that dendritic cells loaded with spike protein of SARS-CoV-2 stimulate T cells to release much more IL-2, which subsequently cooperates with spike protein to facilitate peripheral blood mononuclear cells to release IL-1{beta}, IL-6, and IL-8. These effects are achieved via IL-2 stimulation of NK cells to release TNF- and IFN-{gamma}, as well as T cells to release IFN-{gamma}. Mechanistically, IFN-{gamma} and TNF- enhance the transcription of CD40, and the interaction of CD40 and its ligand stabilizes the membrane expression of TLR4 which serves as a receptor of spike protein on the surface of monocytes. As a result, there is a constant interaction between spike protein and TLR4, leading to continuous activation of NF-{kappa}B. Furthermore, TNF- also activates NF-{kappa}B signaling in monocytes, which further cooperates with IFN-{gamma} and spike protein to modulate NF-{kappa}B-dependent transcription of CRS-related inflammatory cytokines. Targeting TNF-/IFN-{gamma} in combination with TLR4 may represent a promising therapeutic approach for alleviating CRS in individuals with COVID-19.

Tourism Demand Prediction after COVID-19 with Deep Learning Hybrid CNN–LSTM—Case Study of Vietnam and Provinces

The tourism industry experienced a positive increase after COVID-19 and is the largest segment in the foreign exchange contribution in developing countries, especially in Vietnam, where China has begun reopening its borders and lifted the pandemic limitation on foreign travel. This research proposes a hybrid algorithm, combined convolution neural network (CNN) and long short-term memory (LSTM), to accurately predict the tourism demand in Vietnam and some provinces. The number of new COVID-19 cases worldwide and in Vietnam is considered a promising feature in predicting algorithms, which is novel in this research. The Pearson matrix, which evaluates the correlation between selected features and target variables, is computed to select the most appropriate input parameters. The architecture of the hybrid CNN–LSTM is optimized by utilizing hyperparameter fine-tuning, which improves the prediction accuracy and efficiency of the proposed algorithm. Moreover, the proposed CNN–LSTM outperformed other traditional approaches, including the backpropagation neural network (BPNN), CNN, recurrent neural network (RNN), gated recurrent unit (GRU), and LSTM algorithms, by deploying the K-fold cross-validation methodology. The developed algorithm could be utilized as the baseline strategy for resource planning, which could efficiently maximize and deeply utilize the available resource in Vietnam.

Bridging the research-practice gap in supply chain risks induced by the COVID-19

PurposeThis study aims to explore the gap between research and practice on supply chain risks due to COVID-19 by exploring the changes in global emphasis on supply chain risk research.Design/methodology/approachThis work designed a research framework to compare the research of supply chain risks before and during the COVID-19 pandemic based on machining learning and text clustering and using the relevant publications of the web of science database.FindingsThe results show that scholars' attention to supply chain crisis has increased in the wake of the COVID-19 outbreak, but there are differences among countries. The United Kingdom, India, Australia, the USA and Italy have greatly increased their emphasis on risk research, while the supply chain risk research growth rate in other countries, including China, has been lower than the global level. Compared with the pre-pandemic period, the research of business finance, telecommunications, agricultural economics policy, business and public environmental occupational health increased significantly during the pandemic. The hotspots of supply chain risk research have changed significantly during the pandemic, focusing on routing problem, organizational performance, food supply chain, dual-channel supply chain, resilient supplier selection, medical service and machine learning.Research limitations/implicationsThis study has limitations in using a single database.Social implicationsThis work compared the changes in global and various countries' supply chain risk research before and during the pandemic. On the one hand, it helps to judge the degree of response of scholars to the global supply chain risk brought about by COVID-19. On the other hand, it is beneficial for supply chain practitioners and policymakers to gain an in-depth understanding of the relationship between the COVID-19 pandemic and supply chain risk, which might provide insights into not only addressing the supply chain risk but also the recovery of the supply chain.Originality/valueThe initial exploration of the changing extent of supply chain risk research in the context of COVID-19 provided in this paper is a unique and earlier attempt that extends the findings of the existing literature. Secondly, this research provides a feasible analysis strategy for supply chain risk research, which provides a direction and paradigm for exploring more effective supply chain research to meet the challenges of COVID-19.

Reliability Analysis of AlGaN-Based Deep UV-LEDs.

The current pandemic crisis caused by SARS-CoV-2 has also pushed researchers to work on LEDs, especially in the range of 220-240 nm, for the purpose of disinfecting the environment, but the efficiency of such deep UV-LEDs is highly demanding for mass adoption. Over the last two decades, several research groups have worked out that the optical power of GaN-based LEDs significantly decreases during operation, and with the passage of time, many mechanisms responsible for the degradation of such devices start playing their roles. Only a few attempts, to explore the reliability of these LEDs, have been presented so far which provide very little information on the output power degradation of these LEDs with the passage of time. Therefore, the aim of this review is to summarize the degradation factors of AlGaN-based near UV-LEDs emitting in the range of 200-350 nm by means of combined optical and electrical characterization so that work groups may have an idea of the issues raised to date and to achieve a wavelength range needed for disinfecting the environment from SARS-CoV-2. The performance of devices submitted to different stress conditions has been reviewed for the reliability of AlGaN-based UV-LEDs based on the work of different research groups so far, according to our knowledge. In particular, we review: (1) fabrication strategies to improve the efficiency of UV-LEDs; (2) the intensity of variation under constant current stress for different durations; (3) creation of the defects that cause the degradation of LED performance; (4) effect of degradation on C-V characteristics of such LEDs; (5) I-V behavior variation under stress; (6) different structural schemes to enhance the reliability of LEDs; (7) reliability of LEDs ranging from 220-240 nm; and (8) degradation measurement strategies. Finally, concluding remarks for future research to enhance the reliability of near UV-LEDs is presented. This draft presents a comprehensive review for industry and academic research on the physical properties of an AlGaN near UV-LEDs that are affected by aging to help LED manufacturers and end users to construct and utilize such LEDs effectively and provide the community a better life standard.

Accounting Transparency, Fear Sentiment and the COVID-19 Epidemic: For Public Health Security and the Construction of an Early Warning System

A central issue of public health security and the construction of an early warning system is to establish a set of responsibility-oriented incentives and restraint mechanisms. This is closely related to the accounting transparency of the institutional environment and the fear sentiment of the individual's predicament. This study analyses the relationship between accounting transparency, fear sentiment, and COVID-19 through a VAR model analysis. The results show a significant and negative relationship between accounting transparency and daily new COVID-19 patients. In particular, accounting transparency has a negative impact on the increase in the number of people infected with a two-period lag, while the three-period lag in the number of new epidemics has a negative impact on accounting information. Second, accounting transparency has a positive impact on the increase in the search volume on COVID-19 within a three-period lag. After the three-period lag, the number of new epidemics has a positive impact on accounting information. Third, an increase in fear sentiment can be driven by the fear of COVID-19. Fourth, in the public health early warning system, according to the abovementioned time characteristics, the system arranges the emotional counseling, early warning incentives, and institutional constraints to be dealt with in the first 4 days. In addition, in the early warning target-oriented system setting, the parallel system helps to improve the early warning efficiency.

Boosting the Photothermal Conversion Efficiency of MXene Film by Porous Wood for Light-driven Soft Actuators

Ti3C2Tx (a typical MXene) has been widely used in light-driven actuators due to its outstanding photothermal conversion capability. However, the response speed of these actuators is always slow because the effective irradiated area is limited to their surface. Herein, we propose a wood-based composite material which is made by coating Ti3C2Tx on delignified wood (DW). The high porosity of DW leads to high loading of Ti3C2Tx and provides large irradiated areas, thus enhancing photothermal conversion efficiency. The delignification on wood can expose cellulose with highly hydrophilic surface for rapid diffusion of Ti3C2Tx suspension, and the hydroxy in cellulose can act as binding sites to form stable combination with Ti3C2Tx. Taking advantage of the good compressibility of DW, a simple densification is conducted on TDW (Ti3C2Tx/DW) to greatly shorten the distance between adjacent oxygen-enriched Ti3C2Tx nanosheets, enhancing the conjugation among nanosheets, thus endowing TDW with good flexibility and high heat transfer efficiency. Moreover, we manufacture a light-driven bilayer actuator comprised of TDW as the passive layer and low-density polyethylene (LDPE) as the active layer. Our light-driven actuator exhibits a tremendous angle variation of 160° at a light intensity of 120 mW/cm2. A series of devices based on the TDW/LDPE actuator are demonstrated, including simulated gestures, a four-finger soft gripper, and a bionic flower. Moreover, we propose a light-controlled smart switch which can be used on non-contact (COVID-19) or dangerous (blasting) occasions. Additionally, we present a finite element simulation to predict the bending deformation, which guides the accurate control of the devices.

Evaluation of Patients with Vaccine Allergies Prior to mRNA-Based COVID-19 Vaccination.

During the initial rollout of coronavirus disease 2019 (COVID-19) vaccination in Singapore, the Ministry of Health (MOH) issued a recommendation that patients with a history of any previous vaccine allergy be referred to an allergist for further review of their suitability to proceed with mRNA-based COVID-19 vaccines. Patients fulfilling the above criterion were divided into three groups: immediate reaction (Group A), delayed reaction (Group B) and no/irrelevant reaction (Group C). They were subjected to either a skin prick test (SPT) and intradermal test (IDT) with polyethylene glycol (PEG) or polysorbate-containing products; direct injection with the Pfizer BNT162b2 vaccine in the allergy clinic; or injection at community vaccination centres, respectively. Groups A and B were also invited to complete a questionnaire survey on post-vaccination reactions, and blood sampling pre-vaccination and 1 h after the first dose of the BNT162b2 vaccine to measure immunoglobulin (Ig) G, IgM and IgE antibodies to the Pfizer BNT162b2 vaccine via ELISA assays immobilised with the BNT162b2 vaccine, as well as levels of allergic cytokines interleukin (IL)-4 and IL-33, complement C5a and the endothelial activation marker intercellular adhesion molecule-1 (ICAM-1). Groups A and B comprised 62 (20.5%) patients each. In Group A, two subjects (3.2%) with equivocal IDT results tolerated both doses of the BNT162b2 vaccine without major allergic reactions. The remaining 60 (96.8%) in Group A and 62 (100%) in Group B completed both doses of BNT162b2 vaccination without major adverse reactions. Among the 99 who completed the questionnaire survey, 13 (13%) patients reported mild allergic reactions after the first dose of the vaccine. Immunoglobulin (Ig) G and M antibodies, but not IgE antibodies to the Pfizer BNT162b2 vaccine were detected in 67 subjects prior to vaccination. The presence of anti-Pfizer BNT162b2 IgG and IgM prior to vaccination did not result in major allergic reactions nor increases in Th2-related cytokines (IL-4, IL-33), complement activation products (C5a) or endothelial activation (ICAM-1). The majority of those with suspected reactions to non-COVID-19 polysorbate-containing vaccines tolerated the BNT162b2 vaccine. Excipient skin tests for PEG and polysorbate prior to vaccination are unnecessary.

Integrated store service quality measurement scale in omni-channel retailing

Purpose>Brick-and-mortar store is an essential channel to deliver a seamless shopping experience and meet customer's dynamic needs in omni-channel retailing. This paper aims to understand customers' expectations of the integrated stores and develop a measurement scale to assess in-store service quality in omni-channel retailing.Design/methodology/approach>Grounded theory methodology (GTM) is employed to obtain a clear picture of consumer expectations and preferences regarding the omni-channel brick-and-mortar integrated stores. Then, an integrated store service quality scale is proposed, refined and validated using a questionnaire survey and structural equation model (SEM).Findings>The measurement scale is set to include seven dimensions: in-store environment, in-store technology, product information consistency, employee assistance, personalization, channel availability and instant gratification and return. The relationships among these seven dimensions and customer satisfaction and loyalty are also verified. According to SEM, product information consistency is more important for customer satisfaction while personalization contributes more to customer loyalty. The results demonstrate that by analysing the seven dimensions, retailers can better understand customers and further improve service quality.Originality/value>This paper proposes a sufficient measurement scale for in-store service quality and fills the gap in omni-channel retailing by capturing its integration attribute.

A Meta-Analysis of MOOC-Based Academic Achievement, Engagement, Motivation, and Self-Regulation During the COVID-19 Pandemic

Massive open online courses (MOOCs)-based education has gained a great popularity especially during this special COVID-19 pandemic time. This study, aiming to summarize the effectiveness of MOOCs, seems meaningful and necessary. Through a meta-analysis using Stata/MP 14.0, this study concludes that MOOCs-based education could significantly improve academic achievements and motivation rather than self-regulation and engagement compared with the non-MOOCs-based approach. Blended, independent, and gamified instead of interactive MOOCs could significantly improve academic achievements compared with their counterparts. Different approaches to MOOCs could not predict academic achievements. Future research into MOOCs-based education could focus on how to blend elements of gamification and interaction, as well as instructional methods, with MOOCs-based education.

Trends of morbidity and mortality of hand foot and mouth disease in China, 2008-2017

Objective: To analyze the trends of morbidity and mortality of hand foot and mouth disease (HFMD) in China from 2008 to 2017, and provide scientific evidence for the development of HFMD prevention and control strategies.

Potential intestinal infection and faecal-oral transmission of human coronaviruses.

Human coronaviruses (HCoVs) were first described in 1960s for patients experiencing common cold. Since then, increasing number of HCoVs have been discovered, including those causing severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and the circulating coronavirus disease 2019 (COVID-19), which can cause fatal respiratory disease in humans on infection. HCoVs are believed to spread mainly through respiratory droplets and close contact. However, studies have shown that a large proportion of patients with HCoV infection develop gastrointestinal (GI) symptoms, and many patients with confirmed HCoV infection have shown detectable viral RNA in their faecal samples. Furthermore, multiple in vitro and in vivo animal studies have provided direct evidence of intestinal HCoV infection. These data highlight the nature of HCoV GI infection and its potential faecal-oral transmission. Here, we summarise the current findings on GI manifestations of HCoVs. We also discuss how HCoV GI infection might occur and the current evidence to establish the occurrence of faecal-oral transmission.

CRISPR/Cas12a-based SARS-CoV-2 Rapid Visual Detection and Clinical Application (preprint)

Background: Currently, rapid and widespread testing is essential to promote early intervention and curb the ongoing COVID-19 pandemic. The reverse transcription-polymerase chain reaction (RT-PCR) for detecting novel coronavirus (SARS-CoV-2) is restricted to professional laboratories and well-trained personnel, thus, limiting its widespread use in in resource-limited conditions. Methods: To overcome these challenges, we developed a rapid and convenient assay using recombinase polymerase amplification (RPA) and clustered regularly interspaced short palindromic repeats (CRISPR) technology for the rapid detection SARS-CoV-2, which was named as Visual Detection of RPA-amplified Products (VDAP). The reaction conditions of the VDAP were optimized and selected using pure SARS-CoV-2 RNA standards and the sensitivity and specificity of the VDAP were further determined. Finally, the VDAP was verified on clinical specimens. Results: The VDAP was performed at 37 °C for 15 min, and the result was visible by the naked eye. The limits of detection (LODs) of the VDAP for the target ORF1ab and N genes are 70 and 500 copies, respectively. No cross-reactivity was observed with the RNA standard samples of four respiratory viruses or clinical samples of common respiratory viral infections. These results confirmed that the assay was highly specific. Thirty SARS-CoV-2 positive and 30 SARS-CoV-2 negative patient specimens were analyzed. We compared these results to RT-PCR, the overall sensitivity and specificity of the VDAP compared to RT-PCR for detection SARS-CoV-2 were 93.3% and 100.0%, respectively. Conclusions: The VDAP is a simple, highly specific, and convenient assay for the detection of SARS-CoV-2 in resource-limited conditions

Pathogen spectrum in lower respiratory tracts of suspected case infected with SARS-CoV-2

Objective: To understand the pathogen spectrum in the lower respiratory tracts of 100 suspected cases infected with SARS-CoV-2 in Chaoyang district of Beijing from January to March, 2020.

Emergency management strategies for clinical laboratories on COVID-19 epidemic and future prevention and control recommendations

The epidemic of coronavirus disease 2019 (COVID-19) has been basically contained in China, but increasingly severe overseas. It indicates that COVID-19 has stepped into the stage of"global pandemic". In the process of the prevention and the control of COVID-19 epidemic, clinical laboratory has been playing an important role. To end the epidemic as soon as possible and improve the capacity of anti-epidemic, the management experience and measures of clinical laboratories during the epidemic are summarized. Meanwhile, some suggestions are made for the future prevention and control measures, in case that the COVID-19 becomes seasonal disease or epidemic-prone infectious disease in winter.

Surveillance of SARS-CoV-2 in the environment and animal samples of the Huanan Seafood Market (preprint)

Emerging in December 2019, coronavirus disease 2019 (COVID-19) eventually became a pandemic and has posed a tremendous threat to global public health. However, the origins of SARS-CoV-2, the causative agent of COVID-19, remain to be determined. It has reported that a certain number of the early case clusters had a contact history with Huanan Seafood Market. Therefore, surveillance of SARS-CoV-2 within the market is of vital importance. Herein, we presented the SARS-CoV-2 detection results of 1380 samples collected from the environment and the animals within the market in early 2020. By SARS-CoV-2-specific RT-qPCR, 73 environmental samples tested positive for SARS-CoV-2 and three live viruses were successfully isolated. The viruses from the market shared nucleotide identity of 99.980% to 99.993% with the human isolate HCoV/Wuhan/IVDC-HB-01. In contrast, no virus was detected in the animal swabs covering 18 species of animals in the market. The SARS-COV-2 nucleic acids in the positive environmental samples showed significant correlation of abundance of Homo sapiens with SARS-CoV-2. In summary, this study provided convincing evidence of the prevalence of SARS-CoV-2 in the Huanan Seafood Market during the early stage of COVID-19 outbreak.

Nutritional therapy for critical coronavirus disease 2019 patients: a case report (preprint)

Background: An ongoing outbreak of coronavirus disease 2019 (COVID-19) is spreading, there are few reports on exploring individualized nutritional therapy for critical coronavirus disease 2019 (COVID-19) patients. Case presentation: To explore individualized nutritional therapy for critical coronavirus disease 2019 (COVID-19) patients.A nutritional treatment plan was created through nutritional risk screening and nutritional assessment, and an individualized nutritional treatment was implemented through multidisciplinary collaboration. The patient’s gastrointestinal symptoms were corrected, and her nutrition-related indicators such as albumin and body weight were improved. She was cured and discharged. Conclusion: Nutritional therapy is beneficial to improve the nutritional status and clinical outcome of critical COVID- 19 patients.

Kinetics of IgM and IgG antibody specific to SARS-CoV-2 nucleocapsid and spike proteins

：Objective To study the kinetics of IgM and IgG antibodies based on nucleocapsid（N） and spike（S） protein of SARS-Co V2-in COVID-19 patients. Methods Immunofluorescent kits were used to detect N and S protein specific IgM and IgG antibodies from Jan.21 to Feb.11, 2020 for the 60 hospitalized COVID-19 patients（48 mild, 12 severe cases） with a total of 290 plasma samples collected 9 weeks after the onset of the disease. Results The level of antibodies specific for S protein varied significantly with the course of disease（Ig M from 27.32 to 110.10 TU/ml, IgG from 56.85 to 135.00 TU/ml）, but not for N protein.Higher level of Ig M/Ig G antibodies specific to S protein was observed during the 2-7 week than that to N protein.The seropositive rate of antibodies gradually increased during the early stage of disease.IgM/IgG antibodies specific to N protein changed from 12.50% at the first week to peak level（51.72% and 86.21% respectively） at the 4 th week and those for S protein from 25.00% and 14.58% to 100.00%, and then declined.The seropositive rate of Ig M antibody specific to S protein was higher than that for N protein during 2-8 th week and that for Ig G antibody at 2, 3, 4, 6 and 7 th week.The seropositive rate of Ig G antibody specific to N protein in severe patients at the third week was higher than that in mild patients（100.00% vs 59.52%,χ2=9.67, P=0.001 9）, and the same as to Ig G antibody for S protein at the second week after disease onset（80.00% vs 46.58%, χ2=5.57, P=0.018 2）. Conclusions SARS-Co V2-S protein can induc stronger antibody response than N protein, and the antibody level was related to the severity of the disease.

ASGR1 is a candidate receptor for SARS-CoV-2 that promotes infection of liver cells (preprint)

Currently, the COVID-19 pandemic, caused by SARS-CoV-2 infection, represents a serious public health problem worldwide. Although it has been shown that ACE2 serves as the main receptor for SARS-CoV-2 entry into host cells, studies have shown that ACE2 is expressed at extremely low levels in various tissues, especially in some organs where virus particles have been found, such as the heart and liver. Therefore, these organs potentially express additional SARS-CoV-2 receptors that have not yet been discovered. Here, by a genome-wide CRISPR-Cas9 activation library screening, we found that ASGR1 promoted SARS-CoV-2 infection of 293T cells. In Huh-7 and HepG2 cell lines, simultaneous knock out of ACE2 and ASGR1 prevented SARS-CoV-2 pseudovirus infection. In the immortalized THLE-2 hepatocyte cell line and primary liver parenchymal cells, both of which hardly express ACE2, SARS-CoV-2 could successfully establish an infection. After treatment with ASGR1 antibody, the infection rate significantly reduced. This suggests that SARS-CoV-2 infects liver cells mainly through an ASGR1-dependent mechanism. Finally, we also found that the soluble ASGR1 could not only prevent the SARS-CoV-2 pseudovirus, which binds to the ASGR1 receptors, from infecting host liver cells, but also had a protective effect on those expressing ACE2, indicating that administration of soluble ASGR1 protein may represent a new treatment approach. CONCLUSIONS: Colletively, these findings indicate that ASGR1 is a candidate receptor for SARS-CoV-2 that promotes infection of liver cells.