The Role of Information Sources on Tourist Behavior Post-Earthquake Disaster in Indonesia: A Stimulus–Organism–Response (SOR) Approach

The earthquake disaster has an impact on tourist visit intention. This study aims to investigate tourist behavior in the post-earthquake disaster linkage between information sources (word of mouth and electronic word of mouth) and risk perception toward tourists' visit intentions to a destination in Indonesia. This study applies the SOR theory to predict tourists' behavior in the destination aftermath. The Partial Least Squares Structural Equation Model was used to examine the hypothesis of the study. The result found that information sources (electronic word of mouth and word of mouth) significantly influenced visit intention in the time of post-earthquake disaster. The risk perception has not significantly influenced visit intention in post-earthquake disasters. The discussion and conclusion of the study are discussed herein. Overall, the findings of the study may contribute to the theory by adding information sources to predict tourist behavior post-earthquake disaster and also gives a practical contribution to the tourism sector, stakeholders, tourism marketers, and policymakers in Indonesia to enhance the marketing strategy by considering destination promotion through word of mouth (offline) and electronic word of mouth (online) and its mechanism on tourists' travel decision in the time of aftermath.

Is a consumer loan a catalyst for confidence?

In the context of the global economic downturn, the approach guided by consumer loans (CL) to boost consumer confidence is a feasible way to promote the internal circulation of the Chinese economy. Therefore, we use a time-varying rolling-window approach to identify how CL affects the consumer confidence index (CCI). We find that CL can be seen as vital support for promoting confidence because it can ease liquidity constraints and improve consumption levels. The empirical outcome is supported by the Rational Expectations Perpetual Income Hypothesis (RE-PIH), emphasizing that increasing CL can boost consumer confidence. Conversely, CCI has both positive and negative effects on CL. The positive effects suggest that consumers' optimistic confidence leads them to increase borrowing, which in turn creates a heavier debt burden. This statement cannot be supported by the negative effect due to consumers' blind self-confidence will cause cognitive bias, which is not conducive to the loan market development. Against the backdrop of increased global uncertainty due to the COVID-19 pandemic and the government's continuous adjustment of loan policies, consumers can effectively optimise their consumption decision-making through borrowing. The policymaker can maintain loan stability by effectively promoting consumer confidence and raising the consumption level of the whole society.

Sandwich mode lateral flow assay for point-of-care detecting SARS-CoV-2

The global corona virus disease 2019 (COVID-19) has been announced a pandemic outbreak, and has threatened human life and health seriously. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as its causative pathogen, is widely detected in the screening of COVID-19 patients, infected people and contaminated substances. Lateral flow assay (LFA) is a popular point-of-care detection method, possesses advantages of quick response, simple operation mode, portable device, and low cost. Based on the above advantages, LFA has been widely developed for detecting SARS-CoV-2. In this review, we summarized the articles about the sandwich mode LFA detecting SARS-CoV-2, classified according to the target detection objects indicating genes, nucleocapsid protein, spike protein, and specific antibodies of SARS-CoV-2. In each part, LFA is further classified and summarized according to different signal detection types. Additionally, the properties of the targets were introduced to clarify their detection significance. The review is expected to provide a helpful guide for LFA sensitization and marker selection of SARS-CoV-2.

Assessing quality of online learning platforms for in-service teachers’ professional development: The development and application of an instrument

To help optimize online learning platforms for in-service teachers’ professional development, this study aims to develop an instrument to assess the quality of this type of platforms on teacher satisfaction. After reliability and validity tests and expert empowerment, the 27-item instrument was formed. Based on the information systems (IS) success model, this instrument was designed to measure teacher perceptions of the quality of online learning platforms from three dimensions, namely, content quality, technical quality, and service quality. Moreover, the developed instrument was used to analyze the effects of the National Teacher Training Platform amid the COVID-19 outbreak in China. The findings revealed that the improvement of the platform’s style, tool function, operating efficiency, and teaching methods could enhance teachers’ experience of online training.

Monitoring gas flaring in Texas using time-series sentinel-2 MSI and landsat-8 OLI images

Since the shale Oil/Gas revolution, gas flaring and venting in the United States has garnered increasing attention. There is a pressing need to understand the spatial–temporal characteristics of gas flaring and track the associated greenhouse gas emissions. In this context, we use a thermal anomaly index (TAI) incorporating the Google Earth Engine (GEE) cloud computation and local batch processing for monitoring gas flaring and characterizing its spatial–temporal dynamics. We then apply a quantitative analysis of satellite-based carbon dioxide (CO2) and methane (CH4) in the gas flaring region. Here, we generate a gas flaring sites inventory in Texas from 2013 to 2022 based on > 83,500 multi-source moderate-resolution images (including 74,627 Sentinel-2 Multispectral Instrument [MSI] images and 8,969 Landsat-8 Operational Land Imager [OLI] images). Validations and comparisons demonstrate that our method is reliable for MSI and OLI images, with an overall accuracy of > 95 % and a low commission rate and omission rate. We detected 217,034 gas flares from 9,296 flaring sites in Texas, and the majority (>92 %) were found in the central and western regions of the Permian Basin and the Eagle Ford Shale. The number of detected gas flaring sites vastly outnumbered the existing Visible Infrared Imaging Radiometer Suite (VIIRS) fire products, with an upward trend from 2013 to 2019 and a downward trend from 2020 to 2022. Notably, the gas flaring sites dropped significantly at the beginning of the COVID-19 pandemic (from December 2019 to May 2020), with the lowest average monthly growth rate of −14.38 %, and fell to the level of mid-2017. Application of gas flaring data identifies the localized greenhouse gas (GHG) emission hotspots in Texas and demonstrates that the increased effect of CH4 released from gas flaring regions was significantly stronger than that of CO2. These findings can provide references for monitoring similar small industrial sources in the future, can be used as an essential supplement to low-resolution fire products, and improve our understanding of CO2 and CH4 emissions from gas flaring at fine spatial scales.

Remanufacturing lead time planning of the medical device with multi-refurbishing steps

– This research is motivated by the challenges a ventilator remanufacturer encountered during the COVID-19 pandemic: (i) three refurbishing steps, namely, disassembling, sterilising, and reconditioning, which reduce the yield rates of reused components and thus complicating the remanufacturing process, are required to satisfy the compulsory hygienic regulations;and (ii) the lead time to procuring new components become rather variable because of the paralysed global logistics, thereby prolonging the remanufacturing time. To minimise the total remanufacturing costs, mathematical models are built to derive the optimal remanufacturing lead time analytically for one- and two-component cases and numerical studies are conducted to investigate the behaviour of the remanufacturing process. Four managerial insights are provided to improve the remanufacturing performance: (i) The minimum relative entropy method could approximate the optimal remanufacturing lead time with higher precision because the remanufacturing time might be multi-modal distributed. (ii) Increasing the yield rates at all refurbishing steps could shorten the remanufacturing lead time but does not lower the total cost necessarily. (iii) Investment in reducing the refurbishing lead times might not be economically efficient, whereas shortening the procurement lead time could lower the cost dramatically. (iv) Stock-based strategy for the components with low holding cost could help simplify the remanufacturing process and save the multi-skilled labour cost.

Expedient Synthesis of Ubiquitin‐like Protein ISG15 Tools through Chemo‐Enzymatic Ligation Catalyzed by a Viral Protease Lbpro

Ubiquitin (Ub)‐like protein ISG15 (interferon‐stimulated gene 15) regulates innate immunity and links with the evasion of host response by viruses such as SARS‐CoV‐2. Dissecting ISGylation pathways recently received increasing attention which can inform related disease interventions, but such studies necessitate the preparation and development of various ISG15 protein tools. Here, we find that the leader protease (Lbpro) encoded by foot‐and‐mouth disease virus can promote ligation reactions between recombinant ISG15 and synthetic glycyl compounds, generating protein tools such as ISG15‐propargylamide and ISG15‐rhodamine110, which are needed for cellular proteomic studies of deISGylases, and the screening and evaluation of inhibitors against SARS‐CoV‐2 papain‐like protease (PLpro). Furthermore, this strategy can be also used to load ISG15 onto the lysine of a synthetic peptide through an isopeptide bond, and prepare Ub and NEDD8 (ubiquitin‐like protein Nedd8) protein tools.

Effect of miR-221-3p targeting TIMP-2 on proliferation and apoptosis of vascular smooth muscle cells in abdominal aortic aneurysm

Objective: To investigate the effects of miR-221-3p on the proliferation and apoptosis of vascular smooth muscle cells (VSMC) in abdominal aortic aneurysm (AAA) by targeting tissue inhibitor of metalloproteinase- 2 (TIMP-2).

Molecular recognition of SARS-CoV-2 spike protein with three essential partners: exploring possible immune escape mechanisms of viarl mutants (preprint)

The COVID-19 epidemic is raging around the world, including the emergence of viral mutant strains such as Delta and Omicron, posing severe challenges to people's health and quality of life. Full understanding life cycle of the virus in host cells helps to reveal inactivation mechanism of antibody and provide inspiration for the development of a new-generation vaccines. In this work, molecular recognitions and conformational changes of SARS-CoV-2 spike protein (SP) mutants (i.e., Delta, Mu and Omicron) and three essential partners (i.e., membrane receptor hACE2, protease TMPRSS2 and antibody C121) both were compared and analyzed using molecular simulations. Water basin and binding free energy calculations both show that the three mutants possess higher affinity for hACE2 than WT, exhibiting stronger virus transmission. The descending order of cleavage ability by TMPRSS2 is Mu, Delta, Omicron and WT, which is related to the new S1/S2 cutting site induced by transposition effect. The inefficient utilization of TMPRSS2 by Omicron is consistent with its primary entry into cells via the endosomal pathway. In addition, RBD-directed antibody C121 showed obvious resistance to Omicron, which may have originated from high fluctuation of approaching angles, high flexibility of I472-F490 loop and reduced binding ability. According to the overall characteristics of the three mutants, high infectivity, high immune escape and low virulence may be the future evolutionary selection of SARS-CoV-2. In a word, this work not only proposes the possible resistance mechanism of SARS-CoV-2 mutants, but also provides theoretical guidance for the subsequent drug design against COVID-19 based on SP structure.

Intranasal delivery of NS1-deleted influenza virus vectored COVID-19 vaccine restrains the SARS-CoV-2 inflammatory response (preprint)

The emergence of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) variants and "anatomical escape" characteristics threaten the effectiveness of current coronavirus disease (COVID-19) vaccines. There is an urgent need to understand the immunological mechanism of broad-spectrum respiratory tract protection to guide broader vaccines development. In this study, we investigated immune responses induced by an NS1-deleted influenza virus vectored intranasal COVID-19 vaccine (dNS1-RBD) which provides broad-spectrum protection against SARS-CoV-2 variants. Intranasal delivery of dNS1-RBD induced innate immunity, trained immunity and tissue-resident memory T cells covering the upper and lower respiratory tract. It restrained the inflammatory response by suppressing early phase viral load post SARS-CoV-2 challenge and attenuating pro-inflammatory cytokine (IL-6, IL-1B, and IFN-{gamma}) levels, thereby reducing excess immune-induced tissue injury compared with the control group. By inducing local cellular immunity and trained immunity, intranasal delivery of NS1-deleted influenza virus vectored vaccine represents a broad-spectrum COVID-19 vaccine strategy to reduce disease burden.

Protective and detoxifying effects conferred by selenium against mycotoxins and livestock viruses: A review

Animal feed can easily be infected with molds during production and storage processes, and this can lead to the production of secondary metabolites, such as mycotoxins, which eventually threaten human and animal health. Furthermore, livestock production is also not free from viral infections. Under these conditions, the essential trace element, selenium (Se), can confer various biological benefits to humans and animals, especially due to its anticancer, antiviral, and antioxidant properties, as well as its ability to regulate immune responses. This article reviews the latest literature on the antagonistic effects of Se on mycotoxin toxicity and viral infections in animals. We outlined the systemic toxicity of mycotoxins and the primary mechanisms of mycotoxin-induced toxicity in this analysis. In addition, we pay close attention to how mycotoxins and viral infections in livestock interact. The use of Se supplementation against mycotoxin-induced toxicity and cattle viral infection was the topic of our final discussion. The coronavirus disease 2019 (COVID-19) pandemic, which is currently causing a health catastrophe, has altered our perspective on health concerns to one that is more holistic and increasingly embraces the One Health Concept, which acknowledges the interdependence of humans, animals, and the environment. In light of this, we have made an effort to present a thorough and wide-ranging background on the protective functions of selenium in successfully reducing mycotoxin toxicity and livestock viral infection. It concluded that mycotoxins could be systemically harmful and pose a severe risk to human and animal health. On the contrary, animal mycotoxins and viral illnesses have a close connection. Last but not least, these findings show that the interaction between Se status and host response to mycotoxins and cattle virus infection is crucial.

Analysis of epidemic characteristics of COVID-19 clusters in Chenzhou, Hunan Province

Objective: To analyze the epidemiological characteristics of 8 clusters of coronavirus disease 2019 (COVID-19) in Chenzhou City, and provide scientific basis for epidemic prevention and control.

Bioinformatics Approach Predicts Candidate Targets for SARS-CoV-2 Infections to COPD Patients

COVID-19 is still prevalent in more world regions and poses a severe threat to human health due to its high pathogenicity. The incidence of COPD patients is gradually increasing, especially in patients over 45 years old. COPD patients are susceptible to COVID-19 due to the specific lung receptor ACE2 of SARS-CoV-2. We attempt to reveal the genetic basis by analyzing the expression of common DEGs of the two diseases through bioinformatics approaches and find potential therapeutic agents based on the target genes. Thus, we search the GEO database for COVID-19 and COPD transcriptomic gene expression. We also study the enrichment of signaling regulatory pathways and hub genes for potential therapeutic treatments. There are 34 common DEGs in the two datasets. The signaling pathways are mainly enriched in intercellular junctions between virus and cytokine regulation. In the PPI network of common DEGs, we extract 5 hub genes. We find that artesunate CTD 00001840, dexverapamil MCF7 UP, and STOCK1N-35696 PC3 DOWN could be therapeutic agents for both diseases. We also analyze the regulatory network of differential genes with transcription factors and miRNAs. Therefore, we conclude that artesunate CTD 00001840, dexverapamil MCF7 UP, and STOCK1N-35696 PC3 DOWN can be therapeutic candidates in COPD combined with COVID-19.

Photocatalytic Chemical Crosslinking for Profiling RNA–Protein Interactions in Living Cells

The dynamic interactions between RNAs and proteins play crucial roles in regulating diverse cellular processes. Proteome‐wide characterization of these interactions in their native cellular context remains desirable but challenging. Herein, we developed a photocatalytic crosslinking (PhotoCAX) strategy coupled with mass spectrometry (PhotoCAX‐MS) and RNA sequencing (PhotoCAX‐seq) for the study of the composition and dynamics of protein‐RNA interactions. By integrating the blue light‐triggered photocatalyst with a dual‐functional RNA–protein crosslinker (RP‐linker) and the phase separation‐based enrichment strategy, PhotoCAX‐MS revealed a total of 2044 RBPs in human HEK293 cells. We further employed PhotoCAX to investigate the dynamic change of RBPome in macrophage cells upon LPS‐stimulation, as well as the identification of RBPs interacting directly with the 5′ untranslated regions of SARS‐CoV‐2 RNA. [ FROM AUTHOR] Copyright of Angewandte Chemie International Edition is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Effect of Direct Bilirubin Level on Clinical Outcome and Prognoses in Severely/Critically Ill Patients With COVID-19

Objectives We aimed to investigate how changes in direct bilirubin (DBiL) levels in severely/critically ill the coronavirus disease (COVID-19) patients during their first week of hospital admission affect their subsequent prognoses and mortality. Methods We retrospectively enrolled 337 severely/critically ill COVID-19 patients with two consecutive blood tests at hospital admission and about 7 days after. Based on the trend of the two consecutive tests, we categorized patients into the normal direct bilirubin (DBiL) group (224), declined DBiL group (44) and elevated DBiL group (79). Results The elevated DBiL group had a significantly larger proportion of critically ill patients (χ2-test, p < 0.001), a higher risk of ICU admission, respiratory failure, and shock at hospital admission (χ2-test, all p < 0.001). During hospitalization, the elevated DBiL group had significantly higher risks of shock, acute respiratory distress syndrome (ARDS), and respiratory failure (χ2-test, all p < 0.001). The same findings were observed for heart damage (χ2-test, p = 0.002) and acute renal injury (χ2-test, p = 0.009). Cox regression analysis showed the risk of mortality in the elevated DBiL group was 2.27 (95% CI: 1.50–3.43, p < 0.001) times higher than that in the normal DBiL group after adjusted age, initial symptom, and laboratory markers. The Receiver Operating Characteristic curve (ROC) analysis demonstrated that the second test of DBiL was consistently a better indicator of the occurrence of complications (except shock) and mortality than the first test in severely/critically ill COVID-19 patients. The area under the ROC curve (AUC) combined with two consecutive DBiL levels for respiratory failure and death was the largest. Conclusion Elevated DBiL levels are an independent indicator for complication and mortality in COVID-19 patients. Compared with the DBiL levels at admission, DBiL levels on days 7 days of hospitalization are more advantageous in predicting the prognoses of COVID-19 in severely/critically ill patients.

Pulmonary and Renal Long COVID at Two-year Revisit (preprint)

More than 450 million individuals have recovered from COVID-19, but little is known about the host responses to long COVID. We performed proteomic and metabolomic analyses of 991 blood and urine specimens from 144 COVID-19 patients with comprehensive clinical data and up to 763 days of follow up. Our data showed that the lungs and kidneys are the most vulnerable organs in long COVID patients. Pulmonary and renal long COVID of one-year revisit can be predicted by a machine learning model based on clinical and multi-omics data collected during the first month from the disease onset with an ACC of 87.5%. Serum protein SFTPB and ATR were associated with pulmonary long COVID and might be potential therapeutic targets. Notably, our data show that all the patients with persistent pulmonary ground glass opacity or patchy opacity lesions developed into pulmonary fibrosis at two-year revisit. Together, this study depicts the longitudinal clinical and molecular landscape of COVID-19 with up to two-year follow-up and presents a method to predict pulmonary and renal long COVID.