Microfluidic Immuno-Serolomic Assay Reveals Systems Level Association with COVID-19 Pathology and Vaccine Protection.

How to develop highly informative serology assays to evaluate the quality of immune protection against coronavirus disease-19 (COVID-19) has been a global pursuit over the past years. Here, a microfluidic high-plex immuno-serolomic assay is developed to simultaneously measure50 plasma or serum samples for50 soluble markers including 35proteins, 11 anti-spike/receptor binding domian (RBD) IgG antibodies spanningmajor variants, and controls. This assay demonstrates the quintuplicate test in a single run with high throughput, low sample volume, high reproducibilityand accuracy. It is applied to the measurement of 1012 blood samples including in-depth analysis of sera from 127 patients and 21 healthy donors over multiple time points, either with acute COVID infection or vaccination. The protein analysis reveals distinct immune mediator modules that exhibit a reduced degree of diversity in protein-protein cooperation in patients with hematologic malignancies or receiving B cell depletion therapy. Serological analysis identifies that COVID-infected patients with hematologic malignancies display impaired anti-RBD antibody response despite high level of anti-spike IgG, which can be associated with limited clonotype diversity and functional deficiency in B cells. These findings underscore the importance to individualize immunization strategies for these high-risk patients and provide an informative tool to monitor their responses at the systems level.

New observation of perceptive mechanism behind the long-lasting change of people's community mobility: evidence from COVID-19 in China.

COVID-19 pandemic provides an opportunity to investigate how a new and long-lasting threat affects public risk perception and social distancing behavior, which is important for pandemic risk management and recovery of the tertiary industry. We have found that the mechanism that perception decides behavior changes over time. At the beginning of the pandemic, risk directly shapes people's willingness of going out. But under a persistent threat, perception no longer plays the direct role of shape people's willingness. Instead, perception indirectly influences the willingness by shaping people's judgment about the necessity of traveling. Switching from direct to indirect influence, perception's effect is enlarged, which partially prevents people from returning to normal life even if the governmental ban is removed in a zero-COVID community.

Tracking of Mutational Signature of SARS-CoV-2 Omicron on Distinct Continents and Little Difference was Found.

The Omicron variant is currently ravaging the world, raising serious concern globally. Monitoring genomic variations and determining their influence on biological features are critical for tracing its ongoing transmission and facilitating effective measures. Based on large-scale sequences from different continents, this study found that: (i) The genetic diversity of Omicron is much lower than that of the Delta variant. Still, eight deletions (Del 1-8) and 1 insertion, as well as 130 SNPs, were detected on the Omicron genomes, with two deletions (Del 3 and 4) and 38 SNPs commonly detected on all continents and exhibiting high-occurring frequencies. (ii) Four groups of tightly linked SNPs (linkage I-IV) were detected, among which linkage I, containing 38 SNPs, with 6 located in the RBD, increased its occurring frequency remarkably over time. (iii) The third codons of the Omicron shouldered the most mutation pressures, while the second codons presented the least flexibility. (iv) Four major mutants with amino acid substitutions in the RBD were detected, and further structural analysis suggested that the substitutions did not alter the viral receptor binding ability greatly. It was inferred that though the Omicron genome harbored great changes in antigenicity and remarkable ability to evade immunity, it was immune-pressure selected. This study tracked mutational signatures of Omicron variant and the potential biological significance of the SNPs, and the linkages await further functional verification.

The effect of information-driven resource allocation on the propagation of epidemic with incubation period.

In the pandemic of COVID-19, there are exposed individuals who are infected but lack distinct clinical symptoms. In addition, the diffusion of related information drives aware individuals to spontaneously seek resources for protection. The special spreading characteristic and coevolution of different processes may induce unexpected spreading phenomena. Thus we construct a three-layered network framework to explore how information-driven resource allocation affects SEIS (susceptible-exposed-infected-susceptible) epidemic spreading. The analyses utilizing microscopic Markov chain approach reveal that the epidemic threshold depends on the topology structure of epidemic network and the processes of information diffusion and resource allocation. Conducting extensive Monte Carlo simulations, we find some crucial phenomena in the coevolution of information diffusion, resource allocation and epidemic spreading. Firstly, when E-state (exposed state, without symptoms) individuals are infectious, long incubation period results in more E-state individuals than I-state (infected state, with obvious symptoms) individuals. Besides, when E-state individuals have strong or weak infectious capacity, increasing incubation period has an opposite effect on epidemic propagation. Secondly, the short incubation period induces the first-order phase transition. But enhancing the efficacy of resources would convert the phase transition to a second-order type. Finally, comparing the coevolution in networks with different topologies, we find setting the epidemic layer as scale-free network can inhibit the spreading of the epidemic.

UBR5 Acts as an Antiviral Host Factor against MERS-CoV via Promoting Ubiquitination and Degradation of ORF4b.

Within the past 2 decades, three highly pathogenic human coronaviruses have emerged, namely, severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The health threats and economic burden posed by these tremendously severe coronaviruses have paved the way for research on their etiology, pathogenesis, and treatment. Compared to SARS-CoV and SARS-CoV-2, MERS-CoV genome encoded fewer accessory proteins, among which the ORF4b protein had anti-immunity ability in both the cytoplasm and nucleus. Our work for the first time revealed that ORF4b protein was unstable in the host cells and could be degraded by the ubiquitin proteasome system. After extensive screenings, it was found that UBR5 (ubiquitin protein ligase E3 component N-recognin 5), a member of the HECT E3 ubiquitin ligases, specifically regulated the ubiquitination and degradation of ORF4b. Similar to ORF4b, UBR5 can also translocate into the nucleus through its nuclear localization signal, enabling it to regulate ORF4b stability in both the cytoplasm and nucleus. Through further experiments, lysine 36 was identified as the ubiquitination site on the ORF4b protein, and this residue was highly conserved in various MERS-CoV strains isolated from different regions. When UBR5 was knocked down, the ability of ORF4b to suppress innate immunity was enhanced and MERS-CoV replication was stronger. As an anti-MERS-CoV host protein, UBR5 targets and degrades ORF4b protein through the ubiquitin proteasome system, thereby attenuating the anti-immunity ability of ORF4b and ultimately inhibiting MERS-CoV immune escape, which is a novel antagonistic mechanism of the host against MERS-CoV infection. IMPORTANCE ORF4b was an accessory protein unique to MERS-CoV and was not present in SARS-CoV and SARS-CoV-2 which can also cause severe respiratory disease. Moreover, ORF4b inhibited the production of antiviral cytokines in both the cytoplasm and the nucleus, which was likely to be associated with the high lethality of MERS-CoV. However, whether the host proteins regulate the function of ORF4b is unknown. Our study first determined that UBR5, a host E3 ligase, was a potential host anti-MERS-CoV protein that could reduce the protein level of ORF4b and diminish its anti-immunity ability by inducing ubiquitination and degradation. Based on the discovery of ORF4b-UBR5, a critical molecular target, further increasing the degradation of ORF4b caused by UBR5 could provide a new strategy for the clinical development of drugs for MERS-CoV.

Dynamic Patient Admission Control With Time-Varying and Uncertain Demands in COVID-19 Pandemic

In the coronavirus epidemic, many Chinese hospitals have established buffer zones to prevent the spread and transmission of the virus. The buffer zone is a monitored and separate area where the patients who need hospitalizations after the quick treatments in the emergency department can temporarily wait for the Covid-19 test and receive some healthcare services to stabilize their conditions. Because the beds in the buffer zones are limited, the managers face the patient admission control problem for the buffer zone. This management and control problem is challenging since the patient arrivals are uncertain, and the patients’ conditions are different. In this paper, we build the infinite- and finite-horizon Markov decision process (MDP) models for this problem. We use the uniformization method to discretize the patient flow. We propose various iteration algorithms to solve the MDP models and obtain the optimal and threshold policies. Numerical experiments validate the advantages of the policies obtained by the algorithms in this paper over the current policies of hospitals. Note to Practitioners—The ongoing COVID-19 pandemic has been causing enormous damage to people’s health, jobs, and well-being. COVID-19 has affected almost all countries globally and has changed the operation mode of the healthcare system, especially the hospitals. The hospitals are the frontlines of healthcare service and the battle with the COVID-19 pandemic. This article is motivated by our collaborations with hospitals in Shanghai, China. In China, many hospitals establish buffer zones: a monitored area where the patients who need hospitalizations after the quick treatments in the emergency department can temporarily wait for the Covid-19 test and receive some healthcare services to stabilize their conditions. Because the zone’s capacity is limited, the managers must make dynamic patient admission control decisions according to multiple factors, such as patients’ health conditions and the usage of beds in the zone. We propose two MDP models to solve this complex problem. Several iteration algorithms are designed to solve the MDP models and obtain the optimal and threshold policies. Based on hospitals’ real-life data, we show the methods presented in this paper can help hospital managers make more reasonable decisions. Although we focus on the hospital’s buffer zone in China, the methodology and approach for this problem can be extended to other practical hospital management scenarios in the coronavirus pandemic. For example, For example, some hospitals have admission control problems for coronavirus patients due to hospital capacity limitations. The hospital has to decide if a patient is accepted as an inpatient or suggested to home quarantine. In such a case, the admission control problem can also be solved by the methodologies in the paper. [ FROM AUTHOR] Copyright of IEEE Transactions on Automation Science & Engineering is the property of IEEE and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Host E3 ligase HUWE1 attenuates the proapoptotic activity of the MERS-CoV accessory protein ORF3 by promoting its ubiquitin-dependent degradation.

With the outbreak of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), coronaviruses have begun to attract great attention across the world. Of the known human coronaviruses, however, Middle East respiratory syndrome coronavirus (MERS-CoV) is the most lethal. Coronavirus proteins can be divided into three groups: nonstructural proteins, structural proteins, and accessory proteins. While the number of each of these proteins varies greatly among different coronaviruses, accessory proteins are most closely related to the pathogenicity of the virus. We found for the first time that the ORF3 accessory protein of MERS-CoV, which closely resembles the ORF3a proteins of severe acute respiratory syndrome coronavirus and SARS-CoV-2, has the ability to induce apoptosis in cells in a dose-dependent manner. Through bioinformatics analysis and validation, we revealed that ORF3 is an unstable protein and has a shorter half-life in cells compared to that of severe acute respiratory syndrome coronavirus and SARS-CoV-2 ORF3a proteins. After screening, we identified a host E3 ligase, HUWE1, that specifically induces MERS-CoV ORF3 protein ubiquitination and degradation through the ubiquitin-proteasome system. This results in the diminished ability of ORF3 to induce apoptosis, which might partially explain the lower spread of MERS-CoV compared to other coronaviruses. In summary, this study reveals a pathological function of MERS-CoV ORF3 protein and identifies a potential host antiviral protein, HUWE1, with an ability to antagonize MERS-CoV pathogenesis by inducing ORF3 degradation, thus enriching our knowledge of the pathogenesis of MERS-CoV and suggesting new targets and strategies for clinical development of drugs for MERS-CoV treatment.

The COVID-19 infection in children and its association with the immune system, prenatal stress, and neurological complications.

The Coronavirus disease 2019 (COVID-19)" caused by the "severe acute respiratory syndrome corona virus 2 (SARS-CoV-2)" has caused huge losses to the world due to the unavailability of effective treatment options. It is now a serious threat to humans as it causes severe respiratory disease, neurological complications, and other associated problems. Although COVID-19 generally causes mild and recoverable symptoms in children, it can cause serious severe symptoms and death causing complications. Most importantly, SARS-CoV-2 can cause neurological complications in children, such as shortness of breath, myalgia, stroke, and encephalopathy. These problems are highly linked with cytokine storm and proinflammatory responses, which can alter the physiology of the blood-brain barrier and allow the virus to enter the brain. Despite the direct infection caused by the virus entry into the brain, these neurological complications can result from indirect means such as severe immune responses. This review discusses viral transmission, transport to the brain, the associated prenatal stress, and neurological and/or immunological complications in children.

Adsorption of uremic toxins using biochar for dialysate regeneration.

Numerous studies have shown that patients with COVID-19 have a high incidence of renal dysfunction. However, the dialysis supplies, including dialysates, are also severely inadequate in hospitals at the pandemic centers. Therefore, there is an urgent need to develop materials that can efficiently and rapidly remove toxins and thus regenerate dialysate to make this vital resource remains readily available. In this work, by simple carbonization and activation treatment, the porous activated carbon from waste rubber seed shell (RAC) was prepared. The adsorption results showed that the maximum adsorption capacities of the obtained RAC for creatinine and uric acid were 430 mg/g and 504 mg/g, respectively. Significantly, the adsorption process can be close to the equilibrium state within 0.5 h, which proved the ultra-fast adsorption response capacity of RAC. Further, the thermodynamics analysis results showed that both the creatinine and uric acid adsorption processes were monolayer, exothermic, and spontaneous. The adsorption kinetics results indicated that the adsorption process of the two uremic toxins followed the pseudo-second-order rate model and was dominated by chemisorption. The instrument analysis results reflected the efficient adsorption of the RAC for the above uremic toxins which might be due to the dipole-dipole interaction between the dipolar oxygen-containing groups of the surface of RAC and the dipoles of the toxins. Moreover, the formed hydrogen bonds between the oxygen groups and the toxins also played an important role. In all, the as-prepared RAC has the potential to efficiently remove major toxins from the dialysate and can be used in in vitro dialysis of numerous patients during the current COVID-19 pandemic.

Allocating resources for epidemic spreading on metapopulation networks

• Proposing a coevolution model for resource allocation and epidemic spreading on metapopulation network. • Develop a mathematical framework to analyze the dynamical system and obtain the epidemic threshold concerning external factors. • The disease can be controlled effectively when resources are allocated unbiased. • There exists an appropriate small value of mobility rate that is propitious to control the disease through numerical analysis and simulations. A practical resource allocation strategy is the prerequisite for disease control during a pandemic affected by various external factors, such as the information about the epidemic state, the interregional population mobility, and the geographical factors. Understanding the influence of these factors on resource allocation and epidemic spreading is the premise for designing an optimal resource allocation strategy. To this end, we study the interaction of resource allocation and epidemic spreading in the scope of the metapopulation model by incorporating the factors of geographic proximity, the information of the epidemic state, the willingness of resource allocation, and the population mobility simultaneously. We develop a mathematical framework based on the Markovian chain approach to analyze the dynamical system and obtain the epidemic threshold concerning external factors. Combining extensive Monte Carlo simulations, we find that the disease can be controlled effectively when resources are allocated unbiased in terms of the geographical factor during a pandemic. Specifically, the spreading size is the lowest, and the epidemic threshold is the largest when resources are allocated unbiasedly between neighbor nodes and other nodes. In addition, when studying the effects of resource allocation on the epidemic threshold, we find the same results, i.e., information-aware resource allocation with unbiased in terms of the geographical factor will raise the epidemic threshold. At last, we study the effects of mobility rate on the dynamical property and find an appropriate small value of mobility rate that is propitious to control the disease through numerical analysis and simulations. Our findings will have a direct application in the development of strategies to suppress the spread of the disease and guide the behavior of individuals during a pandemic. [ABSTRACT FROM AUTHOR] Copyright of Applied Mathematics & Computation is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Admission Rothman Index, Aspirin, and Intermediate Dose Anticoagulation Effects on Outcomes in COVID-19: A Multi-Site Propensity Matched Analysis

Introduction: Venous thromboembolism and in-situ small vessel thrombosis are increased in hospitalized patients with COVID-19 in several patient cohorts. Endotheliopathy and activation of both platelets and coagulation predict critical illness and death. For these reasons the use of anti-platelet agents and increased-intensity anticoagulation in the care of hospitalized patients with COVID-19 is under intense study in several clinical trials. We sought to examine the impact of aspirin and anticoagulation on hospitalization outcomes.Methods: We examined outcomes in a large multi-site cohort of consecutive, hospitalized, COVID-19 laboratory confirmed patients under a risk-stratified treatment algorithm from March 13 through June 18, with a focus on efficacy of aspirin and/or increased-intensity anticoagulation. Out of 4150 identified hospitalized patients with COVID-19, we created 3 study cohorts. The overall cohort (2785 patients) excluded pediatric patients, those with incomplete electronic data, and those with multiple admissions. The aspirin (1956 patients) and anticoagulation (1623 patients) cohorts were nested within the overall cohort;the former excluded patients on any home anti-platelet therapy or those who received non-aspirin anti-platelet therapy in the hospital, while the latter excluded patients who did not receive prophylactic or intermediate dose anticoagulation in the hospital. The primary outcome was in-hospital death. Secondary outcomes were time-to-death with a competing risk (time-to-hospital-discharge), escalation to ICU, length-of-stay and use of mechanical ventilation. Variables examined included age, gender, BMI, race, Rothman Index (RI), D-dimer (DD) and patient co-morbidities including cardiovascular disease, chronic kidney disease, and prior VTE. The aspirin and anticoagulation cohorts underwent propensity score (PS) matching utilizing variables found to be significant in multivariable regression modeling in the overall cohort with 638 and 386 patients, respectively.Results: Univariate followed by multivariable regression modeling in the 2785 patient overall cohort established a novel role for RI, and independent roles for age, BMI, and maximum DD, in predicting severity of illness. In all cohorts the 50th and lower percentile of admission RI was predictive of mortality in multivariable modeling (i.e. aspirin: 3rd and 4th admission RI quartiles with HR = 0.18 for both, p<0.001 for both). In PS matched patients, aspirin was associated with a significant decrease in mortality (OR 0.65 [0.42, 0.98], p=0.044) and a significant increase in mechanical ventilation (OR 1.49 [1.03, 2.18], p=0.037) and ICU status (OR = 1.45 [1.06, 1.98], p=0.021). In PS matched patients in the anticoagulation cohort, intermediate versus prophylactic dose anticoagulation was associated with a marginal decrease in mortality (OR 0.60, p=0.053). In the aspirin cohort examining in-hospital death and discharge as competing risks, the use of aspirin was associated with decreased mortality (p=0.042) and had no effect on discharge (p=0.31). In the anticoagulation cohort a similar competing risk model showed the use of intermediate rather than prophylactic anticoagulation decreased mortality (p=0.046) and had no effect on discharge (p = 0.21).Conclusion: We show in a large cohort of consecutively hospitalized patients with COVID-19 treated under a risk-stratified algorithm the prognostic utility of the admission RI in assessing outcomes in hospitalized patients with COVID-19 and a potential benefit of aspirin therapy on in-hospital death from COVID-19. A potential albeit marginal benefit of intermediate dose anticoagulation over prophylactic dose anticoagulation merits further study with results of clinical trials awaited.Figure

Clinical characteristics and potential factors for recurrence of positive SARS-CoV-2 RNA in convalescent patients: a retrospective cohort study.

BACKGROUND: The recurrence of positive SARS-CoV-2 RT-PCR is frequently found in discharged COVID-19 patients but its clinical significance remains unclear. The potential cause, clinical characteristics and infectiousness of the recurrent positive RT-PCR patients need to be answered. METHODS: A single-centered, retrospective study of 51 discharged COVID-19 patients was carried out at a designated hospital for COVID-19. The demographic data, clinical records and laboratory findings of 25 patients with recurrent positive RT-PCR from hospitalization to follow-up were collected and compared to 26 patients with negative RT-PCR discharged regularly during the same period. Discharged patients' family members and close contacts were also interviewed by telephone to evaluate patients' potential infectiousness. RESULTS: The titer of both IgG and IgM antibodies was significantly lower (p = 0.027, p = 0.011) in patients with recurrent positive RT-PCR. Median duration of viral shedding significantly prolonged in patients with recurrent positive RT-PCR (36.0 days vs 9.0 days, p = 0.000). There was no significant difference in demographic features, clinical features, lymphocyte subsets count and inflammatory cytokines levels between the two groups of patients. No fatal case was noted in two groups. As of the last day of follow-up, none of the discharged patients' family members or close contact developed any symptoms of COVID-19. CONCLUSIONS: Patients with low levels of IgG and IgM are more likely to have recurrent positive SARS-CoV-2 RT-PCR results and lead to a prolonged viral shedding. The recurrent positive of SARS-CoV-2 RT-PCR may not indicate the recurrence or aggravation of COVID-19. The detection of SARS-CoV-2 by RT-PCR in the patients recovered from COVID-19 is not necessarily correlated with the ability of transmission.

Intermediate-dose anticoagulation, aspirin, and in-hospital mortality in COVID-19: A propensity score-matched analysis.

Thrombotic complications occur at high rates in hospitalized patients with COVID-19, yet the impact of intensive antithrombotic therapy on mortality is uncertain. We examined in-hospital mortality with intermediate- compared to prophylactic-dose anticoagulation, and separately with in-hospital aspirin compared to no antiplatelet therapy, in a large, retrospective study of 2785 hospitalized adult COVID-19 patients. In this analysis, we established two separate, nested cohorts of patients (a) who received intermediate- or prophylactic-dose anticoagulation ("anticoagulation cohort", N = 1624), or (b) who were not on home antiplatelet therapy and received either in-hospital aspirin or no antiplatelet therapy ("aspirin cohort", N = 1956). To minimize bias and adjust for confounding factors, we incorporated propensity score matching and multivariable regression utilizing various markers of illness severity and other patient-specific covariates, yielding treatment groups with well-balanced covariates in each cohort. The primary outcome was cumulative incidence of in-hospital death. Among propensity score-matched patients in the anticoagulation cohort (N = 382), in a multivariable regression model, intermediate- compared to prophylactic-dose anticoagulation was associated with a significantly lower cumulative incidence of in-hospital death (hazard ratio 0.518 [0.308-0.872]). Among propensity-score matched patients in the aspirin cohort (N = 638), in a multivariable regression model, in-hospital aspirin compared to no antiplatelet therapy was associated with a significantly lower cumulative incidence of in-hospital death (hazard ratio 0.522 [0.336-0.812]). In this propensity score-matched, observational study of COVID-19, intermediate-dose anticoagulation and aspirin were each associated with a lower cumulative incidence of in-hospital death.