Identification and characterization of 7-azaindole derivatives as inhibitors of the SARS-CoV-2 spike-hACE2 protein interaction.

The COVID-19 pandemic, caused by SARS-CoV-2, has become a global public health crisis. The entry of SARS-CoV-2 into host cells is facilitated by the binding of its spike protein (S1-RBD) to the host receptor hACE2. Small molecule compounds targeting S1-RBD-hACE2 interaction could provide an alternative therapeutic strategy sensitive to viral mutations. In this study, we identified G7a as a hit compound that targets the S1-RBD-hACE2 interaction, using high-throughput screening in the SARS2-S pseudovirus model. To enhance the antiviral activity of G7a, we designed and synthesized a series of novel 7-azaindole derivatives that bind to the S1-RBD-hACE2 interface. Surprisingly, ASM-7 showed excellent antiviral activity and low cytotoxicity, as confirmed by pseudovirus and native virus assays. Molecular docking and molecular dynamics simulations revealed that ASM-7 could stably bind to the binding interface of S1-RBD-hACE2, forming strong non-covalent interactions with key residues. Furthermore, the binding of ASM-7 caused alterations in the structural dynamics of both S1-RBD and hACE2, resulting in a decrease in their binding affinity and ultimately impeding the viral invasion of host cells. Our findings demonstrate that ASM-7 is a promising lead compound for developing novel therapeutics against SARS-CoV-2.

Newly Characterized Porcine Epidemic Diarrhea Virus GII Subtype Strain

Diarrhea outbreaks in piglets on pig farms are commonly attributed to porcine epidemic diarrhea virus (PEDV) infection. This research analyzed the S gene prevalence variation and recombination patterns in PEDV GII strains. Throughout the previous two years, 172 clinical samples of piglet diarrhea have been collected, from which 24 PEDV isolates have been isolated. Analysis of the evolutionary relationships among all 24 S genes revealed that 21 were most closely related to strains within the GII-a subgroup. The 2 isolates grouped into one clade with the GII-b subgroup. According to the mutation analysis of the amino acids (aa) that encode the S protein, 43 of the common aa in strains of the GII subtype were found to have undergone a change in polarity or charge, and 36 of these aa had a mutation frequency of more than 90%. Three different aa mutation sites were identified as exclusive to GII-a subtype strains. The genomes of three PEDV isolates were sequenced, and the resulting range in genome length was 28,035−28,041 nt. The results of recombination analysis showed that the SD1 isolate is a novel strain recombinant from the foreign S-INDEL strain and a domestic GII subtype strain. Based on the findings, the PEDV GII-a strain has been the most circulating strain in several parts of China during the previous two years. Our study reveals for the first time the unique change of aa mutations in the S protein of the GII-a subtype strain and the new characteristics of the recombination of foreign strains and domestic GII subtype strains, indicating that it is crucial to monitor the epidemic dynamics of PEDV promptly to prevent and control the occurrence of PED effectively.

Strategies for the Emergency Treatment of Pregnant Women with Neurological Symptoms during the COVID-19 Pandemic.

Coronavirus disease-19 (COVID-19) has been spreading all over the world for more than two years. Though several kinds of vaccines are currently available, emergence of new variants, spike mutations and immune escape have raised new challenges. Pregnant women are vulnerable to respiratory infections due to their altered immune defence and surveillance functions. Besides, whether pregnant persons should receive a COVID-19 vaccine is still under debate because limited data are available on the efficacy and safety of receiving a vaccine during pregnancy. Physiological features and lack of effective protection making pregnant women at high risk of getting infected. Another concern is that pregnancy may trigger the onset of underlying existing neurological disease, which is highly similar to those neurological symptoms of pregnant women caused by COVID-19. These similarities interfere with diagnosis and delay timely and effective management. Therefore, providing efficient emergency support for pregnant women suffering from neurological symptoms caused by COVID-19 remains a challenge among neurologists and obstetricians. To improve the diagnosis and treatment efficiency of pregnant women with neurological symptoms, we propose an emergency management framework based on the clinicians' experience and available resources. This emergency care system aimed at addressing the conundrums faced by the emergency guarantee system under COVID-19 pandemic and could serve as a potential multisystem project for clinical practice and medical education.

Ultrasmall and highly biocompatible carbon dots derived from natural plant with amelioration against acute kidney injury.

BACKGROUND: Acute kidney injury (AKI) refers to a tricky clinical disease, known by its high morbidity and mortality, with no real specific medicine for AKI. The carbonization product from Pollen Typhae (i.e., Pu-huang in China) has been extensively employed in clinic, and it is capable of relieving the renal damage and other diseases in China since acient times. RESULTS: Inspired by the carbonization process of Traditional Chinese Medicine (TCM), a novel species of carbon dots derived from Pollen Typhae (PT-CDs) was separated and then collected using a one-pot pyrolysis method. The as-prepared PT-CDs (4.85 ± 2.06 nm) with negative charge and abundant oxygenated groups exhibited high solubility, and they were stable in water. Moreover, the rhabdomyolysis (RM)-induced AKI rat model was used, and it was first demonstrated that PT-CDs had significant activity in improving the level of BUN and CRE, urine volume and kidney index, and histopathological morphology in RM-induced AKI rats. It is noteworthy that interventions of PT-CDs significantly reduced degree of inflammatory reaction and oxidative stress, which may be correlated with the basial potential mechanism of anti-AKI activities. Furthermore, cytotoxicity assay and biosafety evaluation exhibited high biocompatibility of PT-CDs. CONCLUSION: This study offers a novel relieving strategy for AKI based on PT-CDs and suggests its potential to be a related candidate for clinical applications.

Exploring scenarios for the food system-zoonotic risk interface.

The unprecedented economic and health impacts of the COVID-19 pandemic have shown the global necessity of mitigating the underlying drivers of zoonotic spillover events, which occur at the human-wildlife and domesticated animal interface. Spillover events are associated to varying degrees with high habitat fragmentation, biodiversity loss through land use change, high livestock densities, agricultural inputs, and wildlife hunting-all facets of food systems. As such, the structure and characteristics of food systems can be considered key determinants of modern pandemic risks. This means that emerging infectious diseases should be more explicitly addressed in the discourse of food systems to mitigate the likelihood and impacts of spillover events. Here, we adopt a scenario framework to highlight the many connections among food systems, zoonotic diseases, and sustainability. We identify two overarching dimensions: the extent of land use for food production and the agricultural practices employed that shape four archetypal food systems, each with a distinct risk profile with respect to zoonotic spillovers and differing dimensions of sustainability. Prophylactic measures to curb the emergence of zoonotic diseases are therefore closely linked to diets and food policies. Future research directions should explore more closely how they impact the risk of spillover events.

Analysis of the Impact of Meteorological Factors on Ambient Air Quality during the COVID-19 Lockdown in Jilin City in 2022

This paper explored the changes of six significant pollutants (PM2.5, PM10, SO2, NO2, O3, and CO) in Jilin City during the coronavirus disease 2019 (COVID-19) epidemic in 2022, and compared them with the same period of previous years to analyze the impact of anthropogenic emissions on the concentration of pollutants;The Weather Research and Forecasting Community Multiscale Air Quality (WRF-CMAQ) model was used to evaluate the effect of meteorological factors on pollutant concentration. The results showed that except for O3, the concentrations of the other five pollutants decreased significantly, with a range of 21-47%, during the lockdown period caused by the government's shutdown and travel restrictions. Compared with the same period in 2021, the decrease of PM2.5 was only 25% of PM10. That was because there was still a large amount of PM2.5 produced by coal-fired heating during the blockade period, which made the decrease of PM2.5 more minor. A heavy pollution event caused by adverse meteorological conditions was found during the lockdown period, indicating that only controlling artificial emissions cannot eliminate the occurrence of severe pollution events. The WRF-CMAQ results showed that the lower pollutant concentration in 2022 was not only caused by the reduction of anthropogenic emissions but also related to the influence of favorable meteorological factors (higher planetary boundary layer thickness, higher wind speed, and higher temperature).

Probing the Affinity of Noble Metal Nanoparticles to the Segments of the SARS-CoV-2 Spike Protein

Currently, scientists have devoted great efforts to finding effective treatments to combat Covid-19 infections. Although noble metal nanoparticles are able to realize protein modifications, their interactions with the protein are still unclear from the atomic perspective. To supply a general understanding, in this work, we have carried out theoretical calculations to investigate the interaction between protein segments (RBD1, RBD2, RBD3) of SARS-Cov-2 spike protein and a series of noble metal (Au, Ag, Cu, Pd, Pt) surfaces regarding the binding strength, protein orientation, and electronic modulations. In particular, the Au surface has shown the strongest binding preferences for the protein segments, which induces electron transfer between the Au and receptor-binding domain (RBD) segments. This further leads to the polarization of segments for virus denaturation. This work has offered a direct visualization of protein interactions with noble metal surfaces from the atomic level, which will benefit anti-virus material developments in the future. Graphical

Constructing a diversified online neurology teaching model under the COVID-19.

Purpose: To construct a diversified and comprehensive network teaching model to provide highly qualified medical teaching in neurology under COVID-19 pandemic. Materials and methods: Published studies on medical education were systematically reviewed and summarized. Based on previous studies and our experience, we constructed a novel online neurology teaching model and applied it to real scene. Students taking traditional in class lessons and online lessons were asked to finish the test, respectively, to compare the efficiency of learning. Questionnaires were designed and assigned to get the feedback from students. Results: The average test score of students who take online class (84.27 ± 4.64) was significantly higher than those who take in class lessons (82.08 ± 6.17) (P < 0.01). According to the feedbacks from students, online classes were more attractive to students than the conventional one. Conclusion: Traditional single-mode teaching can no longer meet the needs of current medical education, especially under the rampant epidemic. This novel teaching mode, which orchestrates high-tech tools, diverse teaching methods and traditional teaching concepts, provides the solution to the challenge faced by traditional medical education. We believe that this novel online teaching mode will boost neurology education and inspire educators in other fields during this tough period.

Probing the affinity of noble metal nanoparticles to the segments of the SARS-CoV-2 spike protein.

Currently, scientists have devoted great efforts to finding effective treatments to combat COVID-19 infections. Although noble metal nanoparticles are able to realize protein modifications, their interactions with the protein are still unclear from the atomic perspective. To supply a general understanding, in this work, we have carried out theoretical calculations to investigate the interaction between protein segments (RBD1, RBD2, RBD3) of SARS-Cov-2 spike protein and a series of noble metal (Au, Ag, Cu, Pd, Pt) surfaces regarding the binding strength, protein orientations, and electronic modulations. In particular, the Au surface has shown the strongest binding preferences for the protein segments, which induces electron transfer between the Au and receptor-binding domain (RBD) segments. This further leads to the polarization of segments for virus denaturation. This work has offered a direct visualization of protein interactions with noble metal surfaces from the atomic level, which will benefit anti-virus material developments in the future.

Constructing a diversified online neurology teaching model under the COVID-19

Purpose To construct a diversified and comprehensive network teaching model to provide highly qualified medical teaching in neurology under COVID-19 pandemic. Materials and methods Published studies on medical education were systematically reviewed and summarized. Based on previous studies and our experience, we constructed a novel online neurology teaching model and applied it to real scene. Students taking traditional in class lessons and online lessons were asked to finish the test, respectively, to compare the efficiency of learning. Questionnaires were designed and assigned to get the feedback from students. Results The average test score of students who take online class (84.27 ± 4.64) was significantly higher than those who take in class lessons (82.08 ± 6.17) (P < 0.01). According to the feedbacks from students, online classes were more attractive to students than the conventional one. Conclusion Traditional single-mode teaching can no longer meet the needs of current medical education, especially under the rampant epidemic. This novel teaching mode, which orchestrates high-tech tools, diverse teaching methods and traditional teaching concepts, provides the solution to the challenge faced by traditional medical education. We believe that this novel online teaching mode will boost neurology education and inspire educators in other fields during this tough period.

Development of highly effective LCB1-based lipopeptides targeting the spike receptor-binding motif of SARS-CoV-2.

LCB1 is a computationally designed 56-mer miniprotein targeting the spike (S) receptor-binding motif of SARS-CoV- 2 with high potent activity (Science, 2020; Cell host microbe, 2021); however, recent studies have demonstrated that emerging SARS-CoV-2 variants are highly resistant to LCB1's inhibition. In this study, we first identified a truncated peptide termed LCB1v8, which maintained the high antiviral potency. Then, a group of lipopeptides were generated by modifying LCB1v8 with diverse lipids, and of two lipopeptides, the C-terminally stearicacid-conjugtaed LCB1v17 and cholesterol-conjugated LCB1v18, were highly effective in inhibiting both S protein-pseudovirus and authentic SARS-CoV-2 infections. We further showed that LCB1-based inhibitors had similar α-helicity and thermostability in structure and bound to the target-mimic RBD protein with high affinity, and the lipopeptides exhibited greatly enhanced binding with the viral and cellular membranes, improved inhibitory activities against emerging SARS-CoV-2 variants. Moreover, LCB1v18 was validated with high preventive and therapeutic efficacies in K18-hACE2 transgenic mice against lethal SARS-CoV-2 challenge. In conclusion, our studies have provided important information for understanding the structure and activity relationship (SAR) of LCB1 inhibitor and would guide the future development of novel antivirals.

Containment of SARS-CoV-2 Delta strain in Guangzhou, China by quarantine and social distancing: a modelling study.

China detected the first case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with Delta variant in May 2021. We assessed control strategies against this variant of concern. We constructed a robust transmission model to assess the effectiveness of interventions against the Delta variant in Guangzhou with initial quarantine/isolation, followed by social distancing. We also assessed the effectiveness of alternative strategies and that against potentially more infectious variants. The effective reproduction number (Rt) fell below 1 when the average daily number of close contacts was reduced to ≤ 7 and quarantine/isolation was implemented on average at the same day of symptom onset in Guangzhou. Simulations showed that the outbreak could still be contained when quarantine is implemented on average 1 day after symptom onset while the average daily number of close contacts was reduced to ≤ 9 per person one week after the outbreak's beginning. Early quarantine and reduction of close contacts were found to be important for containment of the outbreaks. Early implementation of quarantine/isolation along with social distancing measures could effectively suppress spread of the Delta and more infectious variants.

Resistance profile and mechanism of severe acute respiratory syndrome coronavirus-2 variants to LCB1 inhibitor targeting the spike receptor-binding motif.

LCB1 is a 56-mer miniprotein computationally designed to target the spike (S) receptor-binding motif of SARS-CoV-2 with potent in vitro and in vivo inhibitory activities (Cao et al., 2020; Case et al., 2021). However, the rapid emergence and epidemic of viral variants have greatly impacted the effectiveness of S protein-targeting vaccines and antivirals. In this study, we chemically synthesized a peptide-based LCB1 inhibitor and characterized the resistance profile and underlying mechanism of SARS-CoV-2 variants. Among five variants of concern (VOCs), we found that pseudoviruses of Beta, Gamma, and Omicron were highly resistant to the LCB1 inhibition, whereas the pseudoviruses of Alpha and Delta as well as the variant of interest (VOI) Lambda only caused mild resistance. By generating a group of mutant viruses carrying single or combination mutations, we verified that K417N and N501Y substitutions in RBD critically determined the high resistance phenotype of VOCs. Furthermore, a large panel of 85 pseudoviruses with naturally occurring RBD point-mutations were generated and applied to LCB1, which identified that E406Q, K417N, and L455F conferred high-levels of resistance, when Y505W caused a ∼6-fold resistance fold-change. We also showed that the resistance mutations could greatly weaken the binding affinity of LCB1 to RBD and thus attenuated its blocking capacity on the interaction between RBD and the cell receptor ACE2. In conclusion, our data have provided crucial information for understanding the mechanism of SARS-CoV-2 resistance to LCB1 and will guide the design strategy of novel LCB1-based antivirals against divergent VOCs and evolutionary mutants.

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.

Mental fatigue and negative emotion among nurses during the COVID-19 pandemic.

COVID-19 is a major public health event affecting the people worldwide. Nurses are still under immense psychological pressure. This study aimed to explore the relationship between mental fatigue and negative emotions among frontline medical staff during the COVID-19 pandemic. The study was conducted in August 2020, which included 419 medical staff between 17 to 28 years. The Fatigue Scale, Multidimensional Mental Flexibility Questionnaire, Cognitive Fusion Scale, and Depression-Anxiety-Stress Brief Version Scale were used. During the data collection period, the pandemic was under control in China and continued worldwide. The results indicated that 27.7% of the medical staff experienced depression, and 32.3% of them feel stressed. Specifically, first, correlation analyses showed significant positive pairwise correlations between mental fatigue, psychological inflexibility, cognitive fusion, and negative emotions among nurses. Second, mediation model tests showed statistically significant mediating effects of psychological inflexibility and cognitive fusion between mental fatigue on nurses' negative emotions, and statistically, significant chain mediating effects of psychological inflexibility and cognitive fusion. Mental fatigue indirectly affects nurses' negative effects through the mediating effects of psychological inflexibility, cognitive fusion, and the chain mediating effects of psychological inflexibility and cognitive fusion, respectively. the negative effects of mental fatigue come from impairment of cognitive functioning, and interventions using acceptance and commitment therapy for mental fatigue and negative emotions are more effective since both psychological inflexibility and cognitive fusion are important components of the therapy.

Quantifying the dynamic transmission of COVID-19 asymptomatic and symptomatic infections: Evidence from four Chinese regions

The dynamic transmission of asymptomatic and symptomatic COVID-19 infections is difficult to quantify because asymptomatic infections are not readily recognized or self-identified. To address this issue, we collected data on asymptomatic and symptomatic infections from four Chinese regions (Beijing, Dalian, Xinjiang, and Guangzhou). These data were considered reliable because the government had implemented large-scale multiple testing during the outbreak in the four regions. We modified the classical susceptible–exposure–infection–recovery model and combined it with mathematical tools to quantitatively analyze the number of infections caused by asymptomatic and symptomatic infections during dynamic transmission, respectively. The results indicated that the ratios of the total number of asymptomatic to symptomatic infections were 0.13:1, 0.48:1, 0.29:1, and 0.15:1, respectively, in the four regions. However, the ratio of the total number of infections caused by asymptomatic and symptomatic infections were 4.64:1, 6.21:1, 1.49:1, and 1.76:1, respectively. Furthermore, the present study describes the daily number of healthy people infected by symptomatic and asymptomatic transmission and the dynamic transmission process. Although there were fewer asymptomatic infections in the four aforementioned regions, their infectivity was found to be significantly higher, implying a greater need for timely screening and control of infections, particularly asymptomatic ones, to contain the spread of COVID-19.

SARS-CoV-2 fusion-inhibitory lipopeptides maintain high potency against divergent variants of concern including Omicron.

The emergence of SARS-CoV-2 Omicron and other variants of concern (VOCs) has brought huge challenges to control the COVID-19 pandemic, calling for urgent development of effective vaccines and therapeutic drugs. In this study, we focused on characterizing the impacts of divergent VOCs on the antiviral activity of lipopeptide-based fusion inhibitors that we previously developed. First, we found that pseudoviruses bearing the S proteins of five VOCs (Alpha, Beta, Gamma, Delta, and Omicron) and one variant of interest (Lambda) exhibited greatly decreased infectivity relative to the wild-type (WT) strain or single D614G mutant, especially the Omicron pseudovirus. Differently, the most of variants exhibited an S protein with significantly enhanced cell fusion activity, whereas the S protein of Omicron still mediated decreased cell-cell fusion. Next, we verified that two lipopeptide-based fusion inhibitors, IPB02V3 and IPB24, maintained the highly potent activities in inhibiting various S proteins-driven cell fusion and pseudovirus infection. Surprisingly, both IPB02V3 and IPB24 lipopeptides displayed greatly increased potencies against the infection of authentic Omicron strain relative to the WT virus. The results suggest that Omicron variant evolves with a reduced cell fusion capacity and is more sensitive to the inhibition of fusion-inhibitory lipopeptides; thus, IPB02V3 and IPB24 can be further developed as potent, broad-spectrum antivirals for combating Omicron and the potential future outbreak of other emerging variants.

AI-Aided Design of Novel Targeted Covalent Inhibitors against SARS-CoV-2.

The drug repurposing of known approved drugs (e.g., lopinavir/ritonavir) has failed to treat SARS-CoV-2-infected patients. Therefore, it is important to generate new chemical entities against this virus. As a critical enzyme in the lifecycle of the coronavirus, the 3C-like main protease (3CLpro or Mpro) is the most attractive target for antiviral drug design. Based on a recently solved structure (PDB ID: 6LU7), we developed a novel advanced deep Q-learning network with a fragment-based drug design (ADQN-FBDD) for generating potential lead compounds targeting SARS-CoV-2 3CLpro. We obtained a series of derivatives from the lead compounds based on our structure-based optimization policy (SBOP). All of the 47 lead compounds obtained directly with our AI model and related derivatives based on the SBOP are accessible in our molecular library. These compounds can be used as potential candidates by researchers to develop drugs against SARS-CoV-2.

AI-Aided Design of Novel Targeted Covalent Inhibitors against SARS-CoV-2

The drug repurposing of known approved drugs (e.g., lopinavir/ritonavir) has failed to treat SARS-CoV-2-infected patients. Therefore, it is important to generate new chemical entities against this virus. As a critical enzyme in the lifecycle of the coronavirus, the 3C-like main protease (3CLpro or Mpro) is the most attractive target for antiviral drug design. Based on a recently solved structure (PDB ID: 6LU7), we developed a novel advanced deep Q-learning network with a fragment-based drug design (ADQN–FBDD) for generating potential lead compounds targeting SARS-CoV-2 3CLpro. We obtained a series of derivatives from the lead compounds based on our structure-based optimization policy (SBOP). All of the 47 lead compounds obtained directly with our AI model and related derivatives based on the SBOP are accessible in our molecular library. These compounds can be used as potential candidates by researchers to develop drugs against SARS-CoV-2.