Dynamic associations between the respiratory tract and gut antibiotic resistome of patients with COVID-19 and its prediction power for disease severity.

The antibiotic resistome is the collection of all antibiotic resistance genes (ARGs) present in an individual. Whether an individual's susceptibility to infection and the eventual severity of coronavirus disease 2019 (COVID-19) is influenced by their respiratory tract antibiotic resistome is unknown. Additionally, whether a relationship exists between the respiratory tract and gut ARGs composition has not been fully explored. We recruited 66 patients with COVID-19 at three disease stages (admission, progression, and recovery) and conducted a metagenome sequencing analysis of 143 sputum and 97 fecal samples obtained from them. Respiratory tract, gut metagenomes, and peripheral blood mononuclear cell (PBMC) transcriptomes are analyzed to compare the gut and respiratory tract ARGs of intensive care unit (ICU) and non-ICU (nICU) patients and determine relationships between ARGs and immune response. Among the respiratory tract ARGs, we found that Aminoglycoside, Multidrug, and Vancomycin are increased in ICU patients compared with nICU patients. In the gut, we found that Multidrug, Vancomycin, and Fosmidomycin were increased in ICU patients. We discovered that the relative abundances of Multidrug were significantly correlated with clinical indices, and there was a significantly positive correlation between ARGs and microbiota in the respiratory tract and gut. We found that immune-related pathways in PBMC were enhanced, and they were correlated with Multidrug, Vancomycin, and Tetracycline ARGs. Based on the ARG types, we built a respiratory tract-gut ARG combined random-forest classifier to distinguish ICU COVID-19 patients from nICU patients with an AUC of 0.969. Cumulatively, our findings provide some of the first insights into the dynamic alterations of respiratory tract and gut antibiotic resistome in the progression of COVID-19 and disease severity. They also provide a better understanding of how this disease affects different cohorts of patients. As such, these findings should contribute to better diagnosis and treatment scenarios.

Histone mRNA polyadenylation-mediated inflammation underlies various virus infections and cancers.

The mechanistic understanding of virus infection and inflammation in many diseases is incomplete. Normally, messenger RNA (mRNA) tails of replication-dependent histones (RDH) that safeguard naked nuclear DNAs are protected by a specialized stem-loop instead of polyadenylation. Here, we showed that infection by various RNA viruses (including severe acute respiratory syndrome coronavirus 2) induced aberrant polyadenylation of RDH mRNAs (pARDH) that resulted in inflammation or cellular senescence, based on which we constructed a pARDH inflammation score (pARIS). We further investigated pARIS elevation in various disease conditions, including different types of virus infection, cancer, and cellular senescence. Notably, we found that pARIS was positively correlated with coronavirus disease 2019 severity in specific immune cell types. We also detected a subset of HIV-1 elite controllers characterized by pARDH "flipping" potentially mediated by HuR. Importantly, pARIS was positively associated with transcription of endogenous retrovirus but negatively associated with most immune cell infiltration in tumors of various cancer types. Finally, we identified and experimentally verified two pARIS regulators, ADAR1 and ZKSCAN1, which was first linked to inflammation. The ZKSCAN1 was known as a transcription factor but instead was shown to regulate pARIS as a novel RNA binding protein. Both regulators were upregulated under most infection and inflammation conditions. In conclusion, we unraveled a potential antiviral mechanism underlying various types of virus infections and cancers.

Feasible intervention combinations for achieving a safe exit of the Zero-COVID policy in China and its determinants: an individual-based model study.

BACKGROUND: Although several pathways have been proposed as the prerequisite for a safe phase-out in China, it is not clear which of them are the most important for keeping the mortality rate low, what thresholds should be achieved for these most important interventions, and how the thresholds change with the assumed key epidemiological parameters and population characteristics. METHODS: We developed an individual-based model (IBM) to simulate the transmission of the Omicron variant in the synthetic population, accounting for the age-dependent probabilities of severe clinical outcomes, waning vaccine-induced immunity, increased mortality rates when hospitals are overburdened, and reduced transmission when self-isolated at home after testing positive. We applied machine learning algorithms on the simulation outputs to examine the importance of each intervention parameter and the feasible intervention parameter combinations for safe exits, which is defined as having mortality rates lower than that of influenza in China (14.3 per 100, 000 persons). RESULTS: We identified vaccine coverage in those above 70 years old, number of ICU beds per capita, and the availability of antiviral treatment as the most important interventions for safe exits across all studied locations, although the thresholds required for safe exits vary remarkably with the assumed vaccine effectiveness, as well as the age structure, age-specific vaccine coverage, community healthcare capacity of the studied locations. CONCLUSIONS: The analytical framework developed here can provide the basis for further policy decisions that incorporate considerations about economic costs and societal impacts. Achieving safe exits from the Zero-COVID policy is possible, but challenging for China's cities. When planning for safe exits, local realities such as the age structure and current age-specific vaccine coverage must be taken into consideration.

A Customized Novel Blocking ELISA for Detection of Bat-Origin Swine Acute Diarrhea Syndrome Coronavirus Infection.

Swine acute diarrhea syndrome coronavirus (SADS-CoV) is a newly discovered emerging alphacoronavirus. SADS-CoV shares over 90% genome sequence identity with bat alphacoronavirus HKU2. SADS-CoV was associated with severe diarrhea and high mortality rates in piglets. Accurate serological diagnosis of SADS-CoV infection is key in managing the emerging SADS-CoV. However, thus far there have been no effective antibody-based diagnostic tests for diagnose of SADS-CoV exposure. Here, monoclonal antibody (MAb) 6E8 against SADS-CoV N protein accurately recognized SADS-CoV infection. Then, MAb 6E8 was utilized as a blocking antibody to develop blocking ELISA (bELISA). We customized the rN coating antigen with concentration 0.25 µg/mL. According to receiver operator characteristic curve analysis, the cutoff value of the bELISA was determined as 38.19% when the max Youden index was 0.955, and specificity was 100%, and sensitivity was 95.5%. Specificity testing showed that there was no cross-reactivity with other serum positive swine enteric coronaviruses, such as porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis virus (TGEV), porcine deltacoronavirus (PDCoV), porcine rotavirus (PoRV), and porcine sapelovirus (PSV). In conclusion, we customized a novel and high-quality blocking ELISA for detection of SADS-CoV infection, and the current bELISA will be linked to a clinical and epidemiological assessment of SADS-CoV infection. IMPORTANCE SADS-CoV was reported to be of high potential for dissemination among various of host species. Accurate serological diagnosis of SADS-CoV infection is key in managing the emerging SADS-CoV. However, thus far there have been no effective antibody-based diagnostic tests for diagnose of SADS-CoV exposure. We customed a novel and high-quality bELISA assay for detection of SADS-CoV N protein antibodies, and the current bELISA will be linked to a clinical and epidemiological assessment of SADS-CoV infection.

Coronavirus disease (COVID-19): a scoping review.

BackgroundIn December 2019, a pneumonia caused by a novel coronavirus (SARS-CoV-2) emerged in Wuhan, China and has rapidly spread around the world since then.AimThis study aims to understand the research gaps related to COVID-19 and propose recommendations for future research.MethodsWe undertook a scoping review of COVID-19, comprehensively searching databases and other sources to identify literature on COVID-19 between 1 December 2019 and 6 February 2020. We analysed the sources, publication date, type and topic of the retrieved articles/studies.ResultsWe included 249 articles in this scoping review. More than half (59.0%) were conducted in China. Guidance/guidelines and consensuses statements (n = 56; 22.5%) were the most common. Most (n = 192; 77.1%) articles were published in peer-reviewed journals, 35 (14.1%) on preprint servers and 22 (8.8%) posted online. Ten genetic studies (4.0%) focused on the origin of SARS-CoV-2 while the topics of molecular studies varied. Nine of 22 epidemiological studies focused on estimating the basic reproduction number of COVID-19 infection (R0). Of all identified guidance/guidelines (n = 35), only ten fulfilled the strict principles of evidence-based practice. The number of articles published per day increased rapidly until the end of January.ConclusionThe number of articles on COVID-19 steadily increased before 6 February 2020. However, they lack diversity and are almost non-existent in some study fields, such as clinical research. The findings suggest that evidence for the development of clinical practice guidelines and public health policies will be improved when more results from clinical research becomes available.

Effects of EEG burst suppression on cerebral oxygen metabolism and postoperative cognitive function in elderly surgical patients: A randomized clinical trial.

BACKGROUND: This randomized clinical trial determined the effects of electroencephalographic burst suppression on cerebral oxygen metabolism and postoperative cognitive function in elderly surgical patients. METHODS: The patients were placed into burst suppression (BS) and non-burst suppression (NBS) groups. All patients were under bispectral index monitoring of an etomidate target-controlled infusion for anesthesia induction and intraoperative combination sevoflurane and remifentanil for anesthesia maintenance. The cerebral oxygen extraction ratio (CERO2), jugular bulb venous saturation (SjvO2), and difference in arteriovenous oxygen (Da-jvO2) were measured at T0, T1, and T2. One day before surgery, and 1, 3, and 7 days after surgery, postoperative cognitive dysfunction was assessed using the mini-mental state examination (MMSE). RESULTS: Compared with T0, the Da-jvO2 and CERO2 values were decreased, and SjvO2 was increased in the 2 groups at T1 and T2 (P < .05). There was no statistical difference in the SjvO2, Da-jvO2, and CERO2 values between T1 and T2. Compared with the NBS group, the SjvO2 value increased, and the Da-jvO2 and CERO2 values decreased at T1 and T2 in the BS group (P < .05). The MMSE scores on the 1st and 3rd days postoperatively were significantly lower in the 2 groups compared to the preoperative MMSE scores (P < .05). The MMSE scores of the NBS group were higher than the BS group on the 1st and 3rd days postoperatively (P < .05). CONCLUSION: In elderly patients undergoing surgery, intraoperative BS significantly reduced cerebral oxygen metabolism, which temporarily affected postoperative neurocognitive function.

The value of discharged case fatality rate in estimating the severity and epidemic trend of COVID-19 in China: a novel epidemiological study.

Aim: The main objective of this study was to explore the value of the discharged case fatality rate (DCFR) in estimating the severity and epidemic trend of COVID-19 in China. Subjects and methods: Epidemiological data on COVID-19 in China and Hubei Province were obtained from the National Health Commission of the People's Republic of China from January 20, 2020, to March 31, 2020. The number of daily new confirmed cases, daily confirmed deaths, daily recovered cases, the proportion of daily deaths and total deaths of discharged cases were collected, and the total discharge case fatality rate (tDCFR), daily discharge case fatality rate (dDCFR), and stage-discharge case fatality rate (sDCFR) were calculated. We used the R software (version 3.6.3, R core team) to apply a trimmed exact linear time method to search for changes in the mean and variance of dDCFR in order to estimate the pandemic phase from dDCFR. Results: The tDCFR of COVID-19 in China was 4.16% until March 31, 2020. According to the pattern of dDCFR, the pandemic was divided into four phases: the transmission phase (from January 20 to February 2), the epidemic phase (from February 3 to February 14), the decline phase (from February 15 to February 22), and the sporadic phase (from February 23 to March 31). The sDCFR for these four phases was 43.18% (CI 39.82-46.54%), 13.23% (CI 12.52-13.94%), 5.86% (CI 5.49-6.22%), and 1.61% (CI 1.50-1.72%), respectively. Conclusion: DCFR has great value in assessing the severity and epidemic trend of COVID-19. Supplementary Information: The online version contains supplementary material available at 10.1007/s10389-023-01895-4.

Corrigendum: Impact of Divergent Thinking Training on Teenagers' Emotion and Self-Efficacy During the COVID-19 Pandemic.

[This corrects the article DOI: 10.3389/fpsyg.2021.600533.].

Skipping the Boundary Layer: High-Speed Droplet-Based Immunoassay Using Rayleigh Acoustic Streaming.

Acoustic mixing of droplets is a promising way to implement biosensors that combine high speed and minimal reagent consumption. To date, this type of droplet mixing is driven by a volume force resulting from the absorption of high-frequency acoustic waves in the bulk of the fluid. Here, we show that the speed of these sensors is limited by the slow advection of analyte to the sensor surface due to the formation of a hydrodynamic boundary layer. We eliminate this hydrodynamic boundary layer by using much lower ultrasonic frequencies to excite the droplet, which drives a Rayleigh streaming that behaves essentially like a slip velocity. At equal average flow velocity in the droplet, both experiment and three-dimensional simulations show that this provides a three-fold speedup compared to Eckart streaming. Experimentally, we further shorten a SARS-CoV-2 antibody immunoassay from 20 min to 40 s taking advantage of Rayleigh acoustic streaming.

Successful clearance of persistent SARS-CoV-2 asymptomatic infection following a single dose of Ad5-nCoV vaccine.

Persistent asymptomatic (PA) SARS-CoV-2 infections have been identified. The immune responses in these patients are unclear, and the development of effective treatments for these patients is needed. Here, we report a cohort of 23 PA cases carrying viral RNA for up to 191 days. PA cases displayed low levels of inflammatory and interferon response, weak antibody response, diminished circulating follicular helper T cells (cTfh), and inadequate specific CD4+ and CD8+ T-cell responses during infection, which is distinct from symptomatic infections and resembling impaired immune activation. Administration of a single dose of Ad5-nCoV vaccine to 10 of these PA cases elicited rapid and robust antibody responses as well as coordinated B-cell and cTfh responses, resulting in successful viral clearance. Vaccine-induced antibodies were able to neutralize various variants of concern and persisted for over 6 months, indicating long-term protection. Therefore, our study provides an insight into the immune status of PA infections and highlights vaccination as a potential treatment for prolonged SARS-CoV-2 infections.

Bat-Origin Swine Acute Diarrhea Syndrome Coronavirus Is Lethal to Neonatal Mice.

Bats are reservoirs for diverse coronaviruses, including swine acute diarrhea syndrome coronavirus (SADS-CoV). SADS-CoV has been reported to have broad cell tropism and inherent potential to cross host species barriers for dissemination. We rescued synthetic wild-type SADS-CoV using one-step assembly of a viral cDNA clone by homologous recombination in yeast. Furthermore, we characterized SADS-CoV replication in vitro and in neonatal mice. We found that SADS-CoV caused severe watery diarrhea, weight loss, and a 100% fatality rate in 7- and 14-day-old mice after intracerebral infection. We also detected SADS-CoV-specific N protein in the brain, lungs, spleen, and intestines of infected mice. Furthermore, SADS-CoV infection triggers excessive cytokine expression that encompasses a broad array of proinflammatory mediators, including interleukin 1ß (IL-1ß), IL-6, IL-8, tumor necrosis factor alpha (TNF-α), C-X-C motif chemokine ligand 10 (CXCL10), interferon beta (IFN-ß), IFN-γ, and IFN-λ3. This study highlights the importance of identifying neonatal mice as a model for developing vaccines or antiviral drugs against SADS-CoV infection. IMPORTANCE SADS-CoV is the documented spillover of a bat coronavirus that causes severe disease in pigs. Pigs are in frequent contact with both humans and other animals and theoretically possess a greater chance, compared to many other species, of promoting cross-species viral transmission. SADS-CoV has been reported to have broad cell tropism and inherent potential to cross host species barriers for dissemination. Animal models are an essential feature of the vaccine design toolkit. Compared with neonatal piglets, the mouse is small, making it an economical choice for animal models for SADS-CoV vaccine design. This study showed the pathology of neonatal mice infected with SADS-CoV, which should be very useful for vaccine and antiviral studies.

The protective effects of baicalin for respiratory diseases: an update and future perspectives.

Background: Respiratory diseases are common and frequent diseases. Due to the high pathogenicity and side effects of respiratory diseases, the discovery of new strategies for drug treatment is a hot area of research. Scutellaria baicalensis Georgi (SBG) has been used as a medicinal herb in China for over 2000 years. Baicalin (BA) is a flavonoid active ingredient extracted from SBG that BA has been found to exert various pharmacological effects against respiratory diseases. However, there is no comprehensive review of the mechanism of the effects of BA in treating respiratory diseases. This review aims to summarize the current pharmacokinetics of BA, baicalin-loaded nano-delivery system, and its molecular mechanisms and therapeutical effects for treating respiratory diseases. Method: This review reviewed databases such as PubMed, NCBI, and Web of Science from their inception to 13 December 2022, in which literature was related to "baicalin", "Scutellaria baicalensis Georgi", "COVID-19", "acute lung injury", "pulmonary arterial hypertension", "asthma", "chronic obstructive pulmonary disease", "pulmonary fibrosis", "lung cancer", "pharmacokinetics", "liposomes", "nano-emulsions", "micelles", "phospholipid complexes", "solid dispersions", "inclusion complexes", and other terms. Result: The pharmacokinetics of BA involves mainly gastrointestinal hydrolysis, the enteroglycoside cycle, multiple metabolic pathways, and excretion in bile and urine. Due to the poor bioavailability and solubility of BA, liposomes, nano-emulsions, micelles, phospholipid complexes, solid dispersions, and inclusion complexes of BA have been developed to improve its bioavailability, lung targeting, and solubility. BA exerts potent effects mainly by mediating upstream oxidative stress, inflammation, apoptosis, and immune response pathways. It regulates are the NF-κB, PI3K/AKT, TGF-ß/Smad, Nrf2/HO-1, and ERK/GSK3ß pathways. Conclusion: This review presents comprehensive information on BA about pharmacokinetics, baicalin-loaded nano-delivery system, and its therapeutic effects and potential pharmacological mechanisms in respiratory diseases. The available studies suggest that BA has excellent possible treatment of respiratory diseases and is worthy of further investigation and development.

[Glycosylation, glycan receptors recognition of SARS-CoV-2 and discoveries of glycan inhibitors against SARS-CoV-2].

COVID-19 represents the most serious public health event in the past few decades of the 21st century. The development of vaccines, neutralizing antibodies, and small molecule chemical agents have effectively prevented the rapid spread of COVID-19. However, the continued emergence of SARS-CoV-2 variants have weakened the efficiency of these vaccines and antibodies, which brought new challenges for searching novel anti-SARS-CoV-2 drugs and methods. In the process of SARS-CoV-2 infection, the virus firstly attaches to heparan sulphate on the cell surface of respiratory tract, then specifically binds to hACE2. The S protein of SARS-CoV-2 is a highly glycosylated protein, and glycosylation is also important for the binding of hACE2 to S protein. Furthermore, the S protein is recognized by a series of lectin receptors in host cells. These finding implies that glycosylation plays important roles in the invasion and infection of SARS-CoV-2. Based on the glycosylation pattern and glycan recognition mechanisms of SARS-CoV-2, it is possible to develop glycan inhibitors against COVID-19. Recent studies have shown that sulfated polysaccharides originated from marine sources, heparin and some other glycans display anti-SARS-CoV-2 activity. This review summarized the function of glycosylation of SARS-CoV-2, discoveries of glycan inhibitors and the underpinning molecular mechanisms, which will provide guidelines to develop glycan-based new drugs against SARS-CoV-2.

A spatiotemporal decay model of human mobility when facing large-scale crises.

A common feature of large-scale extreme events, such as pandemics, wildfires, and major storms is that, despite their differences in etiology and duration, they significantly change routine human movement patterns. Such changes, which can be major or minor in size and duration and which differ across contexts, affect both the consequences of the events and the ability of governments to mount effective responses. Based on naturally tracked, anonymized mobility behavior from over 90 million people in the United States, we document these mobility differences in space and over time in six large-scale crises, including wildfires, major tropical storms, winter freeze and pandemics. We introduce a model that effectively captures the high-dimensional heterogeneity in human mobility changes following large-scale extreme events. Across five different metrics and regardless of spatial resolution, the changes in human mobility behavior exhibit a consistent hyperbolic decline, a pattern we characterize as "spatiotemporal decay." When applied to the case of COVID-19, our model also uncovers significant disparities in mobility changes-individuals from wealthy areas not only reduce their mobility at higher rates at the start of the pandemic but also maintain the change longer. Residents from lower-income regions show a faster and greater hyperbolic decay, which we suggest may help account for different COVID-19 rates. Our model represents a powerful tool to understand and forecast mobility patterns post emergency, and thus to help produce more effective responses.

Percolation of temporal hierarchical mobility networks during COVID-19.

Percolation theory is essential for understanding disease transmission patterns on the temporal mobility networks. However, the traditional approach of the percolation process can be inefficient when analysing a large-scale, dynamic network for an extended period. Not only is it time-consuming but it is also hard to identify the connected components. Recent studies demonstrate that spatial containers restrict mobility behaviour, described by a hierarchical topology of mobility networks. Here, we leverage crowd-sourced, large-scale human mobility data to construct temporal hierarchical networks composed of over 175 000 block groups in the USA. Each daily network contains mobility between block groups within a Metropolitan Statistical Area (MSA), and long-distance travels across the MSAs. We examine percolation on both levels and demonstrate the changes of network metrics and the connected components under the influence of COVID-19. The research reveals the presence of functional subunits even with high thresholds of mobility. Finally, we locate a set of recurrent critical links that divide components resulting in the separation of core MSAs. Our findings provide novel insights into understanding the dynamical community structure of mobility networks during disruptions and could contribute to more effective infectious disease control at multiple scales. This article is part of the theme issue 'Data science approaches to infectious disease surveillance'.

Remembering and forgetting information about the COVID-19 vaccine on Twitter.

Social media exposes people to selective information of what they have previously known. We conducted two laboratory studies to examine in a simulated online context the phenomenon of retrieval-induced forgetting, where information reposted on social media is likely to be later remembered and relevant but not reposted information may be forgotten. Specifically, we examined how exposure to selective information about the COVID-19 vaccine via tweets affected subsequent memory and whether people's attitudes towards vaccination played a role in their memory for the information. Young adults (N = 119; Study 1) and community members (N = 92; Study 2) were presented with information about the COVID-19 vaccine that included both pro- and anti-vaccine arguments, organised in four categories (i.e., science, children, religion, morality). They then read tweets that repeated half of the arguments from two of the categories. In a subsequent memory test, participants remembered best the statements repeated in the tweets and remembered worst the statements from the same category but not repeated in the tweets, thus exhibiting retrieval-induced forgetting. This pattern of results was similar across pro- and anti-vaccine arguments, regardless of the participants' level of support for vaccination. We discussed the findings in light of remembering and forgetting in the context of the pandemic and social media.

Development of a novel double-antibody sandwich quantitative ELISA for detecting SADS-CoV infection.

Swine acute diarrhea syndrome coronavirus (SADS-CoV) is an emerging swine enteric alphacoronavirus that can cause acute diarrhea, vomiting, dehydration, and death of newborn piglets. In this study, we developed a double-antibody sandwich quantitative enzyme-linked immunosorbent assay (DAS-qELISA) for detection of SADS-CoV by using an anti-SADS-CoV N protein rabbit polyclonal antibody (PAb) and a specific monoclonal antibody (MAb) 6E8 against the SADS-CoV N protein. The PAb was used as the capture antibodies and HRP-labeled 6E8 as the detector antibody. The detection limit of the developed DAS-qELISA assay was 1 ng/mL of purified antigen and 101.08TCID50/mL of SADS-CoV, respectively. Specificity assays showed that the developed DAS-qELISA has no cross-reactivity with other swine enteric coronaviruses, such as porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis virus (TGEV), and porcine deltacoronavirus (PDCoV). Three-day-old piglets were challenged with SADS-CoV and collected anal swab samples which were screened for the presence of SADS-CoV by using DAS-qELISA and reverse transcriptase PCR (RT-PCR). The coincidence rate of the DAS-qELISA and RT-PCR was 93.93%, and the kappa value was 0.85, indicating that DAS-qELISA is a reliable method for applying antigen detection of clinical samples. KEY POINTS: • The first double-antibody sandwich quantitative enzyme-linked immunosorbent assay for detection SADS-CoV infection. • The custom ELISA is useful for controlling the SADS-CoV spread.