ABSTRACT
MicroRNAs (miRNAs) can repress viral replication by targeting viral messenger RNA (mRNA), which makes them potential antiviral agents. The antiviral effects of miRNAs on infectious viruses have been explored extensively;however, recent studies mainly considered the action modes of miRNAs, neglecting another key factor, the molecular biology of viruses, which may be particularly important in the study of miRNA actions against a given virus. In this paper, the action modes of miRNAs and the molecular biology of viruses are jointly considered for the first time and based on the reported roles of miRNAs on viruses and human coronaviruses (HCoVs) molecular biology, the general and specific interaction modes of miRNAs-HCoVs are systematically reviewed. It was found that HCoVs transcriptome is a nested set of subgenomic mRNAs, sharing the same 5′ leader, 3′ untranslated region (UTR) and open reading frame (ORF). For a given HCoV, one certain miRNA with a target site in the 5′ leader or 3’ UTR has the potential to target all viral mRNAs, indicating tremendous antiviral effects against HCoVs. However, for the shared ORFs, some parts are untranslatable attributed to the translation pattern of HCoVs mRNA, and it is unknown whether the base pairing between the untranslated ORFs and miRNAs plays a regulatory effect on the local mRNAs where the untranslated ORFs are located;therefore, the regulatory effects of miRNAs with targets within the shared ORFs are complicated and need to be confirmed. Collectively, miRNAs may bepromising antiviral agents against HCoVs due to their intrinsically nested set of mRNAs, and some gaps are waiting to be filled. In this review, insight is provided into the exploration of miRNAs that can interrupt HCoVs infection.
ABSTRACT
MicroRNAs (miRNAs) can repress viral replication by targeting viral messenger RNA (mRNA), which makes them potential antiviral agents. The antiviral effects of miRNAs on infectious viruses have been explored extensively; however, recent studies mainly considered the action modes of miRNAs, neglecting another key factor, the molecular biology of viruses, which may be particularly important in the study of miRNA actions against a given virus. In this paper, the action modes of miRNAs and the molecular biology of viruses are jointly considered for the first time and based on the reported roles of miRNAs on viruses and human coronaviruses (HCoVs) molecular biology, the general and specific interaction modes of miRNAs-HCoVs are systematically reviewed. It was found that HCoVs transcriptome is a nested set of subgenomic mRNAs, sharing the same 5' leader, 3' untranslated region (UTR) and open reading frame (ORF). For a given HCoV, one certain miRNA with a target site in the 5' leader or 3' UTR has the potential to target all viral mRNAs, indicating tremendous antiviral effects against HCoVs. However, for the shared ORFs, some parts are untranslatable attributed to the translation pattern of HCoVs mRNA, and it is unknown whether the base pairing between the untranslated ORFs and miRNAs plays a regulatory effect on the local mRNAs where the untranslated ORFs are located; therefore, the regulatory effects of miRNAs with targets within the shared ORFs are complicated and need to be confirmed. Collectively, miRNAs may bepromising antiviral agents against HCoVs due to their intrinsically nested set of mRNAs, and some gaps are waiting to be filled. In this review, insight is provided into the exploration of miRNAs that can interrupt HCoVs infection.
ABSTRACT
The person-artifact-task model provided us with a method to consider the practical performance anxiety (PPA) of technical college students who were working on a computer-related task via online learning. This study investigated 474 technical college students’ PPA in online courses without hands-on demonstration (PPAOC-without-HD) and with hands-on demonstration (PPAOC-with-HD), and it explored whether their PPA varied according to gender and average time spent on online learning. The results indicated that the students’ two types of PPA (PPAOC-without-HD and PPAOC-with-HD) varied significantly by gender and across the different online learning time groups. The average levels of participants’ two types of PPA were both high, and their PPAOC-without-HD was higher than their PPAOC-with-HD. Both types of PPA for females were significantly higher than those for males. Participants’ PPAOC-with-HD showed a significant difference for the average time of online learning. The findings of this study will be of value to educators who need to design and carry out online learning courses for technical college students.
ABSTRACT
Emojis are small pictograms that are frequently embedded within micro-texts to more directly express emotional meanings. To understand the changes in the emoji usage of internet users during the COVID-19 outbreak, we analysed a large dataset collected from Weibo, the most popular Twitter-like social media platform in China, from December 1, 2019, to March 20, 2020. The data contained 38,183,194 microblog posts published by 2,239,472 unique users in Wuhan. We calculated the basic statistics of users’ usage of emojis, topics, and sentiments and analysed the temporal patterns of emoji occurrence. After examining the emoji co-occurrence structure, we finally explored other factors that may affect individual emoji usage. We found that the COVID-19 outbreak greatly changed the pattern of emoji usage;i.e., both the proportion of posts containing emojis and the ratio of users using emojis declined substantially, while the number of posts remained the same. The daily proportion of Happy emojis significantly declined to approximately 32%, but the proportions of Sad- and Encouraging-related emojis rose to 24% and 34%, respectively. Despite a significant decrease in the number of nodes and edges in the emoji co-occurrence network, the average degree of the network increased from 34 to 39.8, indicating that the diversity of emoji usage increased. Most interestingly, we found that male users were more inclined towards using regular textual language with fewer emojis after the pandemic, suggesting that during public crises, male groups appeared to control their emotional display. In summary, the COVID-19 pandemic remarkably impacted individual sentiments, and the normal pattern of emoji usage tends to change significantly following a public emergency. Supplementary Information The online version contains supplementary material available at 10.1007/s10489-022-03195-y.
ABSTRACT
The Covid-19 pandemic has forced the workforce to switch to working from home, which has put significant burdens on the management of broadband networks and called for intelligent service-by-service resource optimization at the network edge. In this context, network traffic prediction is crucial for operators to provide reliable connectivity across large geographic regions. Although recent advances in neural network design have demonstrated potential to effectively tackle forecasting, in this work we reveal based on real-world measurements that network traffic across different regions differs widely. As a result, models trained on historical traffic data observed in one region can hardly serve in making accurate predictions in other areas. Training bespoke models for different regions is tempting, but that approach bears significant measurement overhead, is computationally expensive, and does not scale. Therefore, in this paper we propose TransMUSE, a novel deep learning framework that clusters similar services, groups edge-nodes into cohorts by traffic feature similarity, and employs a Transformer-based Multi-service Traffic Prediction Network (TMTPN), which can be directly transferred within a cohort without any customization. We demonstrate that TransMUSE exhibits imperceptible performance degradation in terms of mean absolute error (MAE) when forecasting traffic, compared with settings where a model is trained for each individual edge node. Moreover, our proposed TMTPN architecture outperforms the state-of-the-art, achieving up to 43.21% lower MAE in the multi-service traffic prediction task. To the best of our knowledge, this is the first work that jointly employs model transfer and multi-service traffic prediction to reduce measurement overhead, while providing fine-grained accurate demand forecasts for edge services provisioning.
Subject(s)
COVID-19ABSTRACT
The recurrent outbreak of coronaviruses and variants underscores the need for broadly reactive antivirals and vaccines. Here, a novel broad-spectrum human antibody named 76E1 was isolated from a COVID-19 convalescent patient and showed broad neutralization activity against multiple α- and β-coronaviruses, including the SARS-CoV-2 variants and also exhibited the binding breath to peptides containing the epitope from γ- and δ- coronaviruses. 76E1 cross-protects mice from SARS-CoV-2 and HCoV-OC43 infection in both prophylactic and treatment models. The epitope including the fusion peptide and S2’ cleavage site recognized by 76E1 was significantly conserved among α-, β-, γ- and δ- coronaviruses. We uncovered a novel mechanism of antibody neutralization that the epitope of 76E1 was proportionally less exposed in the prefusion trimeric structure of spike protein but could be unmasked by binding to the receptor ACE2. Once the epitope exposed, 76E1 inhibited S2’ cleavage, thus blocked the membrane fusion process. Our data demonstrate a key epitope targeted by broadly-neutralizing antibodies and will guide next-generation epitope-based pan-coronavirus vaccine design.
Subject(s)
COVID-19 , InfectionsABSTRACT
The receptor-binding domain (RBD) variants of SARS-CoV-2 could impair antibody-mediated neutralization of the virus by host immunity; thus, prospective surveillance for such antibody escape mutants is urgently needed. Here, we comprehensively profiled four antigenic sites of the RBD and mapped the binding hot spots for a panel of RBD-specific monoclonal antibodies isolated from COVID-19 convalescents, especially dominant VH3-53/3–66 antibodies, which are valuable indicators of antigenic changes in the RBD. We further demonstrated that several natural mutations, namely, K417N, F486L, N450K, L452R, E484K, F490S and R346S, significantly decreased the neutralizing activity of multiple human monoclonal antibodies and of human convalescent plasma obtained in the early stage of the COVID-19 pandemic. Of note, among the natural escape mutations, L452R enhanced ACE2 binding affinity, indicating that it potentially increased virulence. Overall, the in-depth maps may have far-reaching value for surveillance of SARS-CoV-2 immune escape variants and guidance of vaccine design.
Subject(s)
COVID-19ABSTRACT
The metabolic profiles of Tanreqing injection, which is a traditional Chinese medicine recommended for complementary administration to treat a novel coronavirus, have remained unclear, which inhibit the understanding of the effective chemical compounds of Tanreqing injection. In this study, a sensitive high-performance liquid chromatography quadrupole time-of-flight mass spectrometry method was used to identify the compounds and metabolites in various biosamples, including plasma, bile, liver, lung, kidney, urine, and feces, following the intravenous administration of Tanreqing injection in rats. A total of 89 compounds were characterized in the biosamples of Tanreqing injection-treated rats including 25 precursor constituents and 64 metabolites. Nine flavonoid compounds, twelve phenolic acids, and four iridoid glycosides were identified in the rats. Their metabolites were mainly produced by glucuronidation, deglucuronidation, glycosylation, deglycosylation, methylation, demethylation, N-heterocyclisation, sulphation, dehydroxylation, decarboxylation, dehydration, hydroxylation, and corresponding recombination reactions. This study was the first to comprehensively investigate the metabolic profile of Tanreqing injection and provides a scientific basis to further elucidate the pharmacodynamic material basis and therapeutic mechanism of Tanreqing injection.