Algorithm for Optimized mRNA Design Improves Stability and Immunogenicity.

Messenger RNA (mRNA) vaccines are being used to contain COVID-19 (1, 2, 3), but still suffer from the critical limitation of mRNA instability and degradation, which is a major obstacle in the storage, distribution, and efficacy of the vaccine products (4). Previous work showed that increasing secondary structure lengthens mRNA half-life, which, together with optimal codons, improves protein expression (5). Therefore, a principled mRNA design algorithm must optimize both structural stability and codon usage. However, due to synonymous codons, the mRNA design space is prohibitively large (e.g., ~10632 candidates for the SARS-CoV-2 Spike protein), which poses insurmountable computational challenges. Here we provide a simple and unexpected solution using a classical concept in computational linguistics, where finding the optimal mRNA sequence is akin to identifying the most likely sentence among similar sounding alternatives (6). Our algorithm LinearDesign takes only 11 minutes for the Spike protein, and can jointly optimize stability and codon usage. On both COVID-19 and varicella-zoster virus mRNA vaccines, LinearDesign substantially improves mRNA half-life and protein expression, and dramatically increases antibody titer by up to 128× in vivo, compared to the codon-optimization benchmark. This surprising result reveals the great potential of principled mRNA design, and enables the exploration of previously unreachable but highly stable and efficient designs. Our work is a timely tool not only for vaccines but also for mRNA medicine encoding all therapeutic proteins (e.g., monoclonal antibodies and anti-cancer drugs (7, 8)).

Excessive IL-10 and IL-18 trigger hemophagocytic lymphohistiocytosis-like hyperinflammation and enhanced myelopoiesis.

BACKGROUND: Hyperinflammation is a life-threatening condition associated with various clinical disorders characterized by excessive immune activation and tissue damage. Multiple cytokines promote the development of hyperinflammation; however, the contribution of IL-10 remains unclear despite emerging speculations for a pathological role. Clinical observations from hemophagocytic lymphohistiocytosis (HLH), a prototypical hyperinflammatory disease, suggest that IL-18 and IL-10 may collectively promote the onset of a hyperinflammatory state. OBJECTIVE: We aimed to investigate the collaborative roles of IL-10 and IL-18 in hyperinflammation. METHODS: A comprehensive plasma cytokine profile for 87 secondary HLH patients was first depicted and analyzed. We then investigated the systemic and cellular effects of coelevated IL-10 and IL-18 in a transgenic mouse model and cultured macrophages. Single-cell RNA sequencing was performed on the monocytes/macrophages isolated from secondary HLH patients to explore the clinical relevance of IL-10/IL-18-mediated cellular signatures. The therapeutic efficacy of IL-10 blockade was tested in HLH mouse models. RESULTS: Excessive circulating IL-10 and IL-18 triggered a lethal hyperinflammatory disease recapitulating HLH-like phenotypes in mice, driving peripheral lymphopenia and a striking shift toward enhanced myelopoiesis in the bone marrow. IL-10 and IL-18 polarized cultured macrophages to a distinct proinflammatory state with pronounced expression of myeloid cell-recruiting chemokines. Transcriptional characterization suggested the IL-10/IL-18-mediated cellular features were clinically relevant with HLH, showing enhanced granzyme expression and proteasome activation in macrophages. IL-10 blockade protected against the lethal disease in HLH mouse models. CONCLUSION: Coelevated IL-10 and IL-18 are sufficient to drive HLH-like hyperinflammatory syndrome, and blocking IL-10 is protective in HLH models.

Generation and Functional Analysis of Defective Viral Genomes during SARS-CoV-2 Infection.

Defective viral genomes (DVGs) have been identified in many RNA viruses as a major factor influencing antiviral immune response and viral pathogenesis. However, the generation and function of DVGs in SARS-CoV-2 infection are less known. In this study, we elucidated DVG generation in SARS-CoV-2 and its relationship with host antiviral immune response. We observed DVGs ubiquitously from transcriptome sequencing (RNA-seq) data sets of in vitro infections and autopsy lung tissues of COVID-19 patients. Four genomic hot spots were identified for DVG recombination, and RNA secondary structures were suggested to mediate DVG formation. Functionally, bulk and single-cell RNA-seq analysis indicated the interferon (IFN) stimulation of SARS-CoV-2 DVGs. We further applied our criteria to the next-generation sequencing (NGS) data set from a published cohort study and observed a significantly higher amount and frequency of DVG in symptomatic patients than those in asymptomatic patients. Finally, we observed exceptionally diverse DVG populations in one immunosuppressive patient up to 140 days after the first positive test of COVID-19, suggesting for the first time an association between DVGs and persistent viral infections in SARS-CoV-2. Together, our findings strongly suggest a critical role of DVGs in modulating host IFN responses and symptom development, calling for further inquiry into the mechanisms of DVG generation and into how DVGs modulate host responses and infection outcome during SARS-CoV-2 infection. IMPORTANCE Defective viral genomes (DVGs) are generated ubiquitously in many RNA viruses, including SARS-CoV-2. Their interference activity to full-length viruses and IFN stimulation provide the potential for them to be used in novel antiviral therapies and vaccine development. SARS-CoV-2 DVGs are generated through the recombination of two discontinuous genomic fragments by viral polymerase complex, and this recombination is also one of the major mechanisms for the emergence of new coronaviruses. Focusing on the generation and function of SARS-CoV-2 DVGs, these studies identify new hot spots for nonhomologous recombination and strongly suggest that the secondary structures within viral genomes mediate the recombination. Furthermore, these studies provide the first evidence for IFN stimulation activity of de novo DVGs during natural SARS-CoV-2 infection. These findings set up the foundation for further mechanism studies of SARS-CoV-2 recombination and provide evidence to harness the immunostimulatory potential of DVGs in the development of a vaccine and antivirals for SARS-CoV-2.

LazySampling and LinearSampling: fast stochastic sampling of RNA secondary structure with applications to SARS-CoV-2.

Many RNAs fold into multiple structures at equilibrium, and there is a need to sample these structures according to their probabilities in the ensemble. The conventional sampling algorithm suffers from two limitations: (i) the sampling phase is slow due to many repeated calculations; and (ii) the end-to-end runtime scales cubically with the sequence length. These issues make it difficult to be applied to long RNAs, such as the full genomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To address these problems, we devise a new sampling algorithm, LazySampling, which eliminates redundant work via on-demand caching. Based on LazySampling, we further derive LinearSampling, an end-to-end linear time sampling algorithm. Benchmarking on nine diverse RNA families, the sampled structures from LinearSampling correlate better with the well-established secondary structures than Vienna RNAsubopt and RNAplfold. More importantly, LinearSampling is orders of magnitude faster than standard tools, being 428× faster (72 s versus 8.6 h) than RNAsubopt on the full genome of SARS-CoV-2 (29 903 nt). The resulting sample landscape correlates well with the experimentally guided secondary structure models, and is closer to the alternative conformations revealed by experimentally driven analysis. Finally, LinearSampling finds 23 regions of 15 nt with high accessibilities in the SARS-CoV-2 genome, which are potential targets for COVID-19 diagnostics and therapeutics.

Perceived Social Support, Psychological Capital, and Subjective Well-Being among College Students in the Context of Online Learning during the COVID-19 Pandemic

This study examined the relationship between perceived social support and subjective well-being among college students in the context of online learning during the COVID-19 pandemic. 515 college students in China that participated in an online questionnaire investigation were selected as the research sample. The results showed that perceived social support was significantly and positively associated with life satisfaction and positive affect and was significantly and negatively related to negative affect among college students learning online during the COVID-19 pandemic. Psychological capital (PsyCap) significantly mediated the relationships between perceived social support and three subjective well-being variables. The present study provides some implications to protect college students' subjective well-being in the context of online learning during the COVID-19 pandemic.

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.

NASA Satellite Measurements Show Global-Scale Reductions in Free Tropospheric Ozone in 2020 and Again in 2021 During COVID-19.

NASA satellite measurements show that ozone reductions throughout the Northern Hemisphere (NH) free troposphere reported for spring-summer 2020 during the COronaVIrus Disease 2019 pandemic have occurred again in spring-summer 2021. The satellite measurements show that tropospheric column ozone (TCO) (mostly representative of the free troposphere) for 20°N-60°N during spring-summer for both 2020 and 2021 averaged ∼3 Dobson Units (DU) (or ∼7%-8%) below normal. These ozone reductions in 2020 and 2021 were the lowest in the 2005-2021 record. We also include satellite measurements of tropospheric NO2 that exhibit reductions of ∼10%-20% in the NH in early spring-to-summer 2020 and 2021, suggesting that reduced pollution was the main cause for the low anomalies in NH TCO in 2020 and 2021. Reductions of TCO ∼2 DU (7%) are also measured in the Southern Hemisphere in austral summer but are not associated with reduced NO2.

LinearTurboFold: Linear-time global prediction of conserved structures for RNA homologs with applications to SARS-CoV-2.

The constant emergence of COVID-19 variants reduces the effectiveness of existing vaccines and test kits. Therefore, it is critical to identify conserved structures in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes as potential targets for variant-proof diagnostics and therapeutics. However, the algorithms to predict these conserved structures, which simultaneously fold and align multiple RNA homologs, scale at best cubically with sequence length and are thus infeasible for coronaviruses, which possess the longest genomes (∼30,000 nt) among RNA viruses. As a result, existing efforts on modeling SARS-CoV-2 structures resort to single-sequence folding as well as local folding methods with short window sizes, which inevitably neglect long-range interactions that are crucial in RNA functions. Here we present LinearTurboFold, an efficient algorithm for folding RNA homologs that scales linearly with sequence length, enabling unprecedented global structural analysis on SARS-CoV-2. Surprisingly, on a group of SARS-CoV-2 and SARS-related genomes, LinearTurboFold's purely in silico prediction not only is close to experimentally guided models for local structures, but also goes far beyond them by capturing the end-to-end pairs between 5' and 3' untranslated regions (UTRs) (∼29,800 nt apart) that match perfectly with a purely experimental work. Furthermore, LinearTurboFold identifies undiscovered conserved structures and conserved accessible regions as potential targets for designing efficient and mutation-insensitive small-molecule drugs, antisense oligonucleotides, small interfering RNAs (siRNAs), CRISPR-Cas13 guide RNAs, and RT-PCR primers. LinearTurboFold is a general technique that can also be applied to other RNA viruses and full-length genome studies and will be a useful tool in fighting the current and future pandemics.

Quantum dots assembly enhanced and dual-antigen sandwich structured lateral flow immunoassay of SARS-CoV-2 antibody with simultaneously high sensitivity and specificity.

Exploring reliable and highly-sensitive SARS-CoV-2 antibody diagnosis by point-of-care (POC) manner, holds great public health significance for extensive COVID-19 screening and controlling. Unfortunately, the currently applied gold based lateral flow immunoassay (GLFIA) may expose both false-negative and false-positive interpretations owing to the sensitivity and specificity limitations, which may cause significant risk and waste of public resources for large population screening. To simultaneously overcome the drawbacks of GLFIA, a novel fluorescent LFIA based on signal amplification and dual-antigen sandwich structure was established with largely improved sensitivity and specificity. The compact three-dimensional incorporation of hydrophobic quantum dots within dendritic affinity templates and multilayer surface derivation guaranteed a high and robust fluorescence of single label, which lowered the false negative rate of GLFIA prominently. A dual-antigen sandwich structure using labeled/immobilized SARS-CoV-2 spike receptor binding domain antigen for capturing total human SARS-CoV-2 antibody was developed, instead of general indirect antibody capturing approach, to reduce the false positive rate of GLFIA. Over 300 cases of COVID-19 negative and 97 cases of COVID-19 positive samples, the current assay revealed a 100% sensitivity and 100% specificity confirmed by both polymerase chain reaction (PCR) and chemiluminescence immunoassay (CLIA), compared with the considerable misinterpretation cases by currently applied GLFIA. The quantitative results verified by receiver operating characteristic curve and other statistical analysis indicated a well-distinguished positive/negative sample groups. The proposed strategy is highly sensitive towards low concentrated SARS-CoV-2 antibody serums and highly specific towards serums from COVID-19 negative persons and patients infected by other viruses.

Emergency management strategy for prevention and control of novel coronavirus pneuminia-Tenth people's hospital pf Tongi University

To explore scientifically configure medical equipment, standardize distribution of protective materials and manage safely, efficiently in prevention and control of novel coronavirus pneumonia, which comprehensively ensure medical personnel safety and provide support for battle against epidemic. The medical equipment division actively implemented relevant national requirements and coordinated hospital internal, information unblocked and data accuracy. Combined with epidemic character-istics. the needs of key departments were guaranteed based on existing medical equipment and protective materials, and re-fined medical equipment management in emergency situations. The real-time department transfer and scientific management of hospital could effectively respond to risks caused by sudden novel coronavirus pneumonia. In condition of shortage of supplies, hospital was prevented clinical cross-infection and ensured normal operation of medical equipment. which provided reliable and effective medical equipment guarantee. After emergency management during epidemic, summarize effective management and control medical equipment department in special period to ensure overall safe and stable operation at hospital, which has strong practicability and repeatability.

Dynamics of Blood Viral Load Is Strongly Associated with Clinical Outcomes in Coronavirus Disease 2019 (COVID-19) Patients: A Prospective Cohort Study.

The prevalence and clinical relevance of viremia in patients with coronavirus disease 2019 (COVID-19) have not been well studied. A prospective cohort study was designed to investigate blood viral load and clearance kinetics in 52 patients (median age, 62 years; 31 [59.6%] male) and explore their association with clinical features and outcomes based on a novel one-step RT droplet digital PCR (RT-ddPCR). By using one-step RT-ddPCR, 92.3% (48 of 52) of this cohort was quantitatively detected with viremia. The concordance between the blood and oropharyngeal swab tests was 60.92% (53 of 87). One-step RT-ddPCR was tested with a 3.03% false-positive rate and lower 50% confidence interval of detection at 54.026 copies/mL plasma. There was no reduction in the blood viral load in all critical patients, whereas the general and severe patients exhibited a similar ability to clear the viral load. The viral loads in critical patients were significantly higher than those in their general and severe counterparts. Among the 52 study patients, 30 (58%) were discharged from the hospital. Among half of the 30 discharged patients, blood viral load remained positive, of which 76.9% (10 of 13) completely cleared their blood viral load at follow-up. Meanwhile, none of their close contacts had evidence of infection. Quantitative determination of the blood viral test is of great clinical significance in the management of patients with coronavirus disease 2019.

CoV-Seq, a New Tool for SARS-CoV-2 Genome Analysis and Visualization: Development and Usability Study.

BACKGROUND: COVID-19 became a global pandemic not long after its identification in late 2019. The genomes of SARS-CoV-2 are being rapidly sequenced and shared on public repositories. To keep up with these updates, scientists need to frequently refresh and reclean data sets, which is an ad hoc and labor-intensive process. Further, scientists with limited bioinformatics or programming knowledge may find it difficult to analyze SARS-CoV-2 genomes. OBJECTIVE: To address these challenges, we developed CoV-Seq, an integrated web server that enables simple and rapid analysis of SARS-CoV-2 genomes. METHODS: CoV-Seq is implemented in Python and JavaScript. The web server and source code URLs are provided in this article. RESULTS: Given a new sequence, CoV-Seq automatically predicts gene boundaries and identifies genetic variants, which are displayed in an interactive genome visualizer and are downloadable for further analysis. A command-line interface is available for high-throughput processing. In addition, we aggregated all publicly available SARS-CoV-2 sequences from the Global Initiative on Sharing Avian Influenza Data (GISAID), National Center for Biotechnology Information (NCBI), European Nucleotide Archive (ENA), and China National GeneBank (CNGB), and extracted genetic variants from these sequences for download and downstream analysis. The CoV-Seq database is updated weekly. CONCLUSIONS: We have developed CoV-Seq, an integrated web service for fast and easy analysis of custom SARS-CoV-2 sequences. The web server provides an interactive module for the analysis of custom sequences and a weekly updated database of genetic variants of all publicly accessible SARS-CoV-2 sequences. We believe CoV-Seq will help improve our understanding of the genetic underpinnings of COVID-19.

Xuebijing injection in the treatment of COVID-19: a retrospective case-control study.

BACKGROUND: Neither a vaccine nor specific therapeutic drugs against 2019 novel coronavirus have been developed. Some studies have shown that Xuebijing injection (XBJ) can exert an anti-inflammatory effect by inhibiting the production of interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and other cytokines. This study aimed to investigate the effect of XBJ on coronavirus disease 2019 (COVID-19) and its effects on IL-6 and tumor necrosis alpha TNF-α. METHODS: A total of 42 patients, who were diagnosed with COVID-19 and treated with XBJ combined with routine treatment at Chongqing University Three Gorges Hospital between January 20, 2020, and March 11, 2020, were selected as the observation group. A control group comprising 16 patients who received routine treatment was also established, and cases were matched from the observation group on a 1:1 basis according to age, comorbidities, and mild and severe disease. The clinical symptoms, laboratory test indexes, and changes in computed tomography (CT) scans of patients in the two groups were observed at the time of admission and 7 days after treatment, and the time taken for the patients to produce a negative nucleic acid test was also recorded. RESULTS: There were no significant differences in baseline data between the two groups. After treatment, there were significant improvements in IL-6 levels and body temperature in the observation group as compared with the control group. Particularly in severe patients, the reduction in body temperature in the observation group was greater than that in the control group (P<0.05). A higher number of patients in the observation group showed improved CT imaging results compared with the control group, and the time taken to produce a negative nucleic acid test was shorter in the observation group than in the control group; however, the differences were not statistically significant (P>0.05). Furthermore, there were no significant differences in TNF-α and IL-10 between the two groups. CONCLUSIONS: The results of this study suggest that routine treatment combined with XBJ can better improve the clinical outcomes of COVID-19 patients.

Clinical characteristics of moderate and severe cases with COVID-19 in Wuhan, China: a retrospective study.

With the outbreak of COVID-19 ongoing, this infectious disease has been posing a significant threat to public health. However, we are still relatively inexperienced on recognizing the clinical characteristics of severe COVID-19 and death cases. Therefore, we hereby collected and analyzed a total of 232 cases to illustrate the clinical characteristics of such patients in Wuhan and to find notable marks for early clinical warning. We consider age, comorbidities, platelet count, albumin, D-dimer, LDH, CRP and IL-6 level might be more meaningful marks for COVID-19 prognostic evaluation.

Inactivation times from 290 to 315 nm UVB in sunlight for SARS coronaviruses CoV and CoV-2 using OMI satellite data for the sunlit Earth.

UVB in sunlight, 290-315 nm, can inactivate SARS CoV and SARS CoV-2 viruses on surfaces and in the air. Laboratory exposure to ultraviolet irradiance in the UVC range inactivates many viruses and bacteria in times less than 30 min. Estimated UVB inactivation doses from sunlight in J/m2 are obtained from UVC measurements and radiative transfer calculations, weighted by a virus inactivation action spectrum, using OMI satellite atmospheric data for ozone, clouds, and aerosols. For SARS CoV, using an assumed UVC dose near the mid-range of measured values, D 90 = 40 J/m2, 90% inactivation times T 90 are estimated for exposure to midday 10:00-14:00 direct plus diffuse sunlight and for nearby locations in the shade (diffuse UVB only). For the assumed D 90 = 40 J/m2 model applicable to SARS CoV viruses, calculated estimates show that near noon 11:00-13:00 clear-sky direct sunlight gives values of T 90 < 90 min for mid-latitude sites between March and September and less than 60 min for many equatorial sites for 12 months of the year. Recent direct measurements of UVB sunlight inactivation of the SARS CoV-2 virus that causes COVID-19 show shorter T 90 inactivation times less than 10 min depending on latitude, season, and hour. The equivalent UVC 254 nm D 90 dose for SARS CoV-2 is estimated as 3.2 ± 0.7 J/m2 for viruses on a steel mesh surface and 6.5 ± 1.4 J/m2 for viruses in a growth medium. For SARS CoV-2 clear-sky T 90 on a surface ranges from 4 min in the equatorial zone to less than 30 min in a geographic area forming a near circle with solar zenith angle < 60O centered on the subsolar point for local solar times from 09:00 to 15:00 h.

Ruxolitinib in treatment of severe coronavirus disease 2019 (COVID-19): A multicenter, single-blind, randomized controlled trial.

BACKGROUND: Accumulating evidence proposed Janus-associated kinase (JAK) inhibitors as therapeutic targets warranting rapid investigation. OBJECTIVE: This study evaluated the efficacy and safety of ruxolitinib, a JAK1/2 inhibitor, for coronavirus disease 2019. METHODS: We conducted a prospective, multicenter, single-blind, randomized controlled phase II trial involving patients with severe coronavirus disease 2019. RESULTS: Forty-three patients were randomly assigned (1:1) to receive ruxolitinib plus standard-of-care treatment (22 patients) or placebo based on standard-of-care treatment (21 patients). After exclusion of 2 patients (1 ineligible, 1 consent withdrawn) from the ruxolitinib group, 20 patients in the intervention group and 21 patients in the control group were included in the study. Treatment with ruxolitinib plus standard-of-care was not associated with significantly accelerated clinical improvement in severe patients with coronavirus disease 2019, although ruxolitinib recipients had a numerically faster clinical improvement. Eighteen (90%) patients from the ruxolitinib group showed computed tomography improvement at day 14 compared with 13 (61.9%) patients from the control group (P = .0495). Three patients in the control group died of respiratory failure, with 14.3% overall mortality at day 28; no patients died in the ruxolitinib group. Ruxolitinib was well tolerated with low toxicities and no new safety signals. Levels of 7 cytokines were significantly decreased in the ruxolitinib group in comparison to the control group. CONCLUSIONS: Although no statistical difference was observed, ruxolitinib recipients had a numerically faster clinical improvement. Significant chest computed tomography improvement, a faster recovery from lymphopenia, and favorable side-effect profile in the ruxolitinib group were encouraging and informative to future trials to test efficacy of ruxolitinib in a larger population.

[Discussion of Medical Protective Consumables Management to Fight against COVID-19 Pneumonia].

This article researches how to allocate medical protective consumables in hospital and ensure the safety of emergency marketing procurement under the condition that people are easily susceptible to COVID-19. To inform medical staffs about the standard instruction, we establish the corresponding hierarchical control management system and standards of medical protective consumables. To reduce the stress of clinical medical staff and prevent excessive protection, we enhance the training mechanisms and promote the superior normative guidance. The aim is to fully play the effectiveness of the key departments of medical protective consumables, reduce the risk of infection of clinical medical staff and ensure the safety of medical staffs.