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Register a new userImmunological determinants of clinical outcomes in COVID-19: A quantitative perspective
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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a variable clinical presentation that ranges from asymptomatic, to severe disease with cytokine storm. The mortality rates also differ across the globe, ranging from 0.5-13%. This variation is likely due to both pathogen and host factors. Host factors may include genetic differences in the immune response genes as well as variation in HLA and KIR allotypes. To better understand what impact these genetic variants in immune response genes may have in the differences observed in the immune response to SARS-CoV-2, a quantitative analysis of a dynamical systems model that considers both, the magnitude of viral growth, and the subsequent innate and adaptive response required to achieve control of infection is considered. Based on this broad quantitative framework it may be posited that the spectrum of symptomatic to severely symptomatic presentations of COVID19 represents the balance between innate and adaptive immune responses. In asymptomatic patients, prompt and adequate adaptive immune response quells infection, whereas in those with severe symptoms a slower inadequate adaptive response leads to a runaway cytokine cascade fueled by ongoing viral replication. Polymorphisms in the various components of the innate and adaptive immune response may cause altered immune response kinetics that would result in variable severity of illness. Understanding how this genetic variation may alter the response to SARS-CoV-2 infection is critical to develop successful treatment strategies.
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Diabetes is considered as an critical comorbidity linked with the latest coronavirus disease 2019 (COVID-19) which spreads through Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov-2). The diabetic patients have higher threat of infection from novel corona virus. Depending on the region in the globe, 20% to 50% of patients infected with COVID-19 pandemic had diabetes. The current article discussed the risk associated with diabetic patients and also recommendation for controlling diabetes during this pandemic situation. The article also discusses the case study of COVID-19 at various regions around the globe and the preventive actions taken by various countries to control the effect from the virus. The article presents several smart healthcare solutions for the diabetes patients to have glucose insulin control for the protection against COVID-19.
Patients infected with SARS-CoV-2 show a wide spectrum of clinical manifestations ranging from mild febrile illness and cough up to acute respiratory distress syndrome, multiple organ failure and death. Data from patients with severe clinical manifestations compared to patients with mild symptoms indicate that highly dysregulated exuberant inflammatory responses correlate with severity of disease and lethality. Significantly elevated cytokine levels, i.e. cytokine storm, seem to play a central role in severity and lethality in COVID-19. We have previously shown that excessive cytokine release induced by highly pathogenic avian H5N1 influenza A virus was reduced by application of proteasome inhibitors. In the present study we present experimental data of a central cellular pro-inflammatory signal pathways, NF-kappaB, in the context of published clinical data from COVID-19 patients and develop a hypothesis for a therapeutic approach aiming at the simultaneous inhibition of whole cascades of pro-inflammatory cytokines and chemokines via blocking the nuclear translocation of NF-kappaB by proteasome inhibitors. The simultaneous inhibition of multiple cytokines/chemokines using clinically approved proteasome inhibitors is expected to have a higher therapeutic potential compared to single target approaches to prevent cascade (i.e. triggering, synergistic, and redundant) effects of multiple induced cytokines and may provide an additional therapeutic option to be explored for treatment of critical stage COVID-19 patients.
This paper introduces a new basic risk model that could also be utilized by Covid-19 warning apps a priori, before an action is performed. Today the common warning apps estimate risk a posteriori and give no advice on particular scenarios. The new model also has the advantage that the individual risks behind the decision-making process would be uniform (in contrast to some current regulations) and it could help to understand the risks better and could also help to reduce risks a priori. It could be easily implemented on a single app screen, needing only some individual preferences to be set and a handful of adjustments to the particular scenario that shall be assessed. The disadvantage as of any simplified semi-quantitative risk models is that calibration is not easy (as some calibration points may even contradict) and that cumulative effects are hard to integrate e. g. the joint effect of combined scenarios. But, in principle calibration is feasible and it may be a good decision to calibrate the model conservatively.
We have developed a mathematical model of regulation of expression of the Escherichia coli lac operon, and have investigated bistability in its steady-state induction behavior in the absence of external glucose. Numerical analysis of equations describing regulation by artificial inducers revealed two natural bistability parameters that can be used to control the range of inducer concentrations over which the model exhibits bistability. By tuning these bistability parameters, we found a family of biophysically reasonable systems that are consistent with an experimentally determined bistable region for induction by thio-methylgalactoside (Ozbudak et al. Nature 427:737, 2004). The model predicts that bistability can be abolished when passive transport or permease export becomes sufficiently large; the former case is especially relevant to induction by isopropyl-beta, D-thiogalactopyranoside. To model regulation by lactose, we developed similar equations in which allolactose, a metabolic intermediate in lactose metabolism and a natural inducer of lac, is the inducer. For biophysically reasonable parameter values, these equations yield no bistability in response to induction by lactose; however, systems with an unphysically small permease-dependent export effect can exhibit small amounts of bistability for limited ranges of parameter values. These results cast doubt on the relevance of bistability in the lac operon within the natural context of E. coli, and help shed light on the controversy among existing theoretical studies that address this issue. The results also suggest an experimental approach to address the relevance of bistability in the lac operon within the natural context of E. coli.
The sudden outbreak of the Coronavirus disease (COVID-19) swept across the world in early 2020, triggering the lockdowns of several billion people across many countries, including China, Spain, India, the U.K., Italy, France, Germany, and most states of the U.S. The transmission of the virus accelerated rapidly with the most confirmed cases in the U.S., and New York City became an epicenter of the pandemic by the end of March. In response to this national and global emergency, the NSF Spatiotemporal Innovation Center brought together a taskforce of international researchers and assembled implemented strategies to rapidly respond to this crisis, for supporting research, saving lives, and protecting the health of global citizens. This perspective paper presents our collective view on the global health emergency and our effort in collecting, analyzing, and sharing relevant data on global policy and government responses, geospatial indicators of the outbreak and evolving forecasts; in developing research capabilities and mitigation measures with global scientists, promoting collaborative research on outbreak dynamics, and reflecting on the dynamic responses from human societies.
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