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1.
J Med Chem ; 64(19): 14332-14343, 2021 10 14.
Article in English | MEDLINE | ID: covidwho-1621195

ABSTRACT

In addition to a variety of viral-glycoprotein receptors (e.g., heparan sulfate, Niemann-Pick C1, etc.), dendritic cell-specific intercellular adhesion molecule-3-grabbing nonintegrin (DC-SIGN), from the C-type lectin receptor family, plays one of the most important pathogenic functions for a wide range of viruses (e.g., Ebola, human cytomegalovirus (HCMV), HIV-1, severe acute respiratory syndrome coronavirus 2, etc.) that invade host cells before replication; thus, its inhibition represents a relevant extracellular antiviral therapy. We report two novel p-tBu-calixarene glycoclusters 1 and 2, bearing tetrahydroxamic acid groups, which exhibit micromolar inhibition of soluble DC-SIGN binding and provide nanomolar IC50 inhibition of both DC-SIGN-dependent Jurkat cis-cell infection by viral particle pseudotyped with Ebola virus glycoprotein and the HCMV-gB-recombinant glycoprotein interaction with monocyte-derived dendritic cells expressing DC-SIGN. A unique cooperative involvement of sugar, linker, and calixarene core is likely behind the strong avidity of DC-SIGN for these low-valent systems. We claim herein new promising candidates for the rational development of a large spectrum of antiviral therapeutics.


Subject(s)
Calixarenes/chemistry , Cell Adhesion Molecules/antagonists & inhibitors , Glycoconjugates/metabolism , Glycoproteins/antagonists & inhibitors , Hydroxamic Acids/chemistry , Lectins, C-Type/antagonists & inhibitors , Phenols/chemistry , Receptors, Cell Surface/antagonists & inhibitors , Viral Proteins/antagonists & inhibitors , Antiviral Agents/chemistry , Antiviral Agents/metabolism , Antiviral Agents/pharmacology , Cell Adhesion Molecules/metabolism , Cell Line , Cytomegalovirus/metabolism , Dendritic Cells/cytology , Dendritic Cells/metabolism , Ebolavirus/physiology , Glycoconjugates/chemistry , Glycoconjugates/pharmacology , Glycoproteins/genetics , Glycoproteins/metabolism , Humans , Jurkat Cells , Lectins, C-Type/metabolism , Models, Biological , Protein Binding , Receptors, Cell Surface/metabolism , Recombinant Proteins/biosynthesis , Recombinant Proteins/chemistry , Recombinant Proteins/isolation & purification , Viral Proteins/genetics , Viral Proteins/metabolism
2.
Bull Math Biol ; 84(2): 30, 2022 01 10.
Article in English | MEDLINE | ID: covidwho-1616222

ABSTRACT

The COVID-19 pandemic has adversely affected the entire world. The effective implementation of vaccination strategy is critical to prevent the resurgence of the pandemic, especially during large-scale population migration. We establish a multiple patch coupled model based on the transportation network among the 31 provinces in China, under the combined strategies of vaccination and quarantine during large-scale population migration. Based on the model, we derive a critical quarantine rate to control the pandemic transmission and a vaccination rate to achieve herd immunity. Furthermore, we evaluate the influence of passenger flow on the effective reproduction number during the Chinese-Spring-Festival travel rush. Meanwhile, the spread of the COVID-19 pandemic is investigated for different control strategies, viz. global control and local control. The impact of vaccine-related parameters, such as the number, the effectiveness and the immunity period of vaccine, are explored. It is believed that the articulated models as well as the presented simulation results could be beneficial to design of feasible strategies for preventing COVID-19 transmission during the Chinese-Spring-Festival travel rush or the other future events involving large-scale population migration.


Subject(s)
COVID-19 , Quarantine , China/epidemiology , Holidays , Humans , Mathematical Concepts , Models, Biological , Pandemics/prevention & control , SARS-CoV-2 , Travel , Vaccination
3.
J Biol Dyn ; 16(1): 14-28, 2022 12.
Article in English | MEDLINE | ID: covidwho-1612382

ABSTRACT

COVID-19 is a disease caused by infection with the virus 2019-nCoV, a single-stranded RNA virus. During the infection and transmission processes, the virus evolves and mutates rapidly, though the disease has been quickly controlled in Wuhan by 'Fangcang' hospitals. To model the virulence evolution, in this paper, we formulate a new age structured epidemic model. Under the tradeoff hypothesis, two special scenarios are used to study the virulence evolution by theoretical analysis and numerical simulations. Results show that, before 'Fangcang' hospitals, two scenarios are both consistent with the data. After 'Fangcang' hospitals, Scenario I rather than Scenario II is consistent with the data. It is concluded that the transmission pattern of COVID-19 in Wuhan obey Scenario I rather than Scenario II. Theoretical analysis show that, in Scenario I, shortening the value of L (diagnosis period) can result in an enormous selective pressure on the evolution of 2019-nCoV.


Subject(s)
COVID-19 , China/epidemiology , Humans , Models, Biological , SARS-CoV-2 , Virulence
4.
BMC Infect Dis ; 21(1): 1145, 2021 Nov 09.
Article in English | MEDLINE | ID: covidwho-1608950

ABSTRACT

BACKGROUND: The global spread of the novel coronavirus pneumonia is still continuing, and a new round of more serious outbreaks has even begun in some countries. In this context, this paper studies the dynamics of a type of delayed reaction-diffusion novel coronavirus pneumonia model with relapse and self-limiting treatment in a temporal-spatial heterogeneous environment. METHODS: First, focus on the self-limiting characteristics of COVID-19, incorporate the relapse and self-limiting treatment factors into the diffusion model, and study the influence of self-limiting treatment on the diffusion of the epidemic. Second, because the traditional Lyapunov stability method is difficult to determine the spread of the epidemic with relapse and self-limiting treatment, we introduce a completely different method, relying on the existence conditions of the exponential attractor of our newly established in the infinite-dimensional dynamic system to determine the diffusion of novel coronavirus pneumonia. Third, relapse and self-limiting treatment have led to a change in the structure of the delayed diffusion COVID-19 model, and the traditional basic reproduction number [Formula: see text] no longer has threshold characteristics. With the help of the Krein-Rutman theorem and the eigenvalue method, we studied the threshold characteristics of the principal eigenvalue and found that it can be used as a new threshold to describe the diffusion of the epidemic. RESULTS: Our results prove that the principal eigenvalue [Formula: see text] of the delayed reaction-diffusion COVID-19 system with relapse and self-limiting treatment can replace the basic reproduction number [Formula: see text] to describe the threshold effect of disease transmission. Combine with the latest official data and the prevention and control strategies, some numerical simulations on the stability and global exponential attractiveness of the diffusion of the COVID-19 epidemic in China and the USA are given. CONCLUSIONS: Through the comparison of numerical simulations, we find that self-limiting treatment can significantly promote the prevention and control of the epidemic. And if the free activities of asymptomatic infected persons are not restricted, it will seriously hinder the progress of epidemic prevention and control.


Subject(s)
COVID-19 , Epidemics , Basic Reproduction Number , Humans , Models, Biological , SARS-CoV-2
5.
Bull Math Biol ; 84(2): 28, 2022 01 04.
Article in English | MEDLINE | ID: covidwho-1608940

ABSTRACT

The spread of COVID-19 in Wuhan was successfully curbed under the strategy of "Joint Prevention and Control Mechanism." To understand how this measure stopped the epidemics in Wuhan, we establish a compartmental model with time-varying parameters over different stages. In the early stage of the epidemic, due to resource limitations, the number of daily reported cases may lower than the actual number. We employ a dynamic-based approach to calibrate the accumulated clinically diagnosed data with a sudden jump on February 12 and 13. The model simulation shows reasonably good match with the adjusted data which allows the prediction of the cumulative confirmed cases. Numerical results reveal that the "Joint Prevention and Control Mechanism" played a significant role on the containment of COVID-19. The spread of COVID-19 cannot be inhibited if any of the measures was not effectively implemented. Our analysis also illustrates that the Fangcang Shelter Hospitals are very helpful when the beds in the designated hospitals are insufficient. Comprised with Fangcang Shelter Hospitals, the designated hospitals can contain the transmission of COVID-19 more effectively. Our findings suggest that the combined multiple measures are essential to curb an ongoing epidemic if the prevention and control measures can be fully implemented.


Subject(s)
COVID-19 , China/epidemiology , Humans , Mathematical Concepts , Models, Biological , SARS-CoV-2
6.
Cells ; 10(12)2021 11 28.
Article in English | MEDLINE | ID: covidwho-1598211

ABSTRACT

Drug repositioning is one of the leading strategies in modern therapeutic research. Instead of searching for completely novel substances and demanding studies of their biological effects, much attention has been paid to the evaluation of commonly used drugs, which could be utilized for more distinct indications than they have been approved for. Since treatment approaches for cancer, one of the most extensively studied diseases, have still been very limited, great effort has been made to find or repurpose novel anticancer therapeutics. One of these are cardiac glycosides, substances commonly used to treat congestive heart failure or various arrhythmias. Recently, the antitumor properties of cardiac glycosides have been discovered and, therefore, these compounds are being considered for anticancer therapy. Their mechanism of antitumor action seems to be rather complex and not fully uncovered yet, however, autophagy has been confirmed to play a key role in this process. In this review article, we report on the up-to-date knowledge of the anticancer activity of cardiac glycosides with special attention paid to autophagy induction, the molecular mechanisms of this process, and the potential employment of this phenomenon in clinical practice.


Subject(s)
Autophagy , Cardiac Glycosides/pharmacology , Animals , Apoptosis/drug effects , Autophagy/drug effects , Biomarkers/metabolism , Humans , Models, Biological , Sodium-Potassium-Exchanging ATPase/metabolism
7.
Nutrients ; 13(12)2021 Dec 17.
Article in English | MEDLINE | ID: covidwho-1580555

ABSTRACT

Widespread overeating has been found during the 2019 coronavirus (COVID-19) pandemic. The present study investigated whether pre-pandemic restrained eating (RE) predicted overeating during the pandemic, and further explored the behavioral (mortality threat, negative affect) mechanisms underlying this association. An eight-month longitudinal survey was conducted with a large sample of 616 undergraduates from Southwest university. From September 2019 to April 2020, three measurements were conducted. RE was tested before the pandemic (T1), and data of mortality threat, negative affect, and overeating were collected at the middle (T2) and end of (T3) the COVID-19 crisis in China. The correlation results showed that baseline RE was positively associated with mortality threat, negative affect, and overeating at T2 and T3. Moreover, negative affect and mortality threat were positively correlated with overeating. Results from longitudinal mediation showed that baseline RE would positively predict T3 overeating through T2 negative affect, but not T2 mortality threat. This study supports and extends the counterregulatory eating hypothesis that RE positively predicts future overeating, especially through negative emotions. These findings further reveal the core psychological mechanism underlying this positive RE-overeating relation in the context of COVID-19, indicating that the individuals with higher RE could not cope with negative affect adequately, contributing to more overeating.


Subject(s)
COVID-19 , Feeding Behavior , Hyperphagia , Models, Biological , SARS-CoV-2 , Adolescent , Adult , COVID-19/epidemiology , COVID-19/physiopathology , China/epidemiology , Female , Humans , Hyperphagia/epidemiology , Hyperphagia/physiopathology , Longitudinal Studies , Male
8.
Viruses ; 13(12)2021 12 17.
Article in English | MEDLINE | ID: covidwho-1580425

ABSTRACT

BACKGROUND: The SARS-CoV-2 spike protein mediates attachment of the virus to the host cell receptor and fusion between the virus and the cell membrane. The S1 subunit of the spike glycoprotein (S1 protein) contains the angiotensin converting enzyme 2 (ACE2) receptor binding domain. The SARS-CoV-2 variants of concern contain mutations in the S1 subunit. The spike protein is the primary target of neutralizing antibodies generated following infection, and constitutes the viral component of mRNA-based COVID-19 vaccines. METHODS: Therefore, in this work we assessed the effect of exposure (24 h) to 10 nM SARS-CoV-2 recombinant S1 protein on physiologically relevant human bronchial (bro) and alveolar (alv) lung mucosa models cultured at air-liquid interface (ALI) (n = 6 per exposure condition). Corresponding sham exposed samples served as a control. The bro-ALI model was developed using primary bronchial epithelial cells and the alv-ALI model using representative type II pneumocytes (NCI-H441). RESULTS: Exposure to S1 protein induced the surface expression of ACE2, toll like receptor (TLR) 2, and TLR4 in both bro-ALI and alv-ALI models. Transcript expression analysis identified 117 (bro-ALI) and 97 (alv-ALI) differentially regulated genes (p ≤ 0.01). Pathway analysis revealed enrichment of canonical pathways such as interferon (IFN) signaling, influenza, coronavirus, and anti-viral response in the bro-ALI. Secreted levels of interleukin (IL) 4 and IL12 were significantly (p < 0.05) increased, whereas IL6 decreased in the bro-ALI. In the case of alv-ALI, enriched terms involving p53, APRIL (a proliferation-inducing ligand) tight junction, integrin kinase, and IL1 signaling were identified. These terms are associated with lung fibrosis. Further, significantly (p < 0.05) increased levels of secreted pro-inflammatory cytokines IFNγ, IL1ꞵ, IL2, IL4, IL6, IL8, IL10, IL13, and tumor necrosis factor alpha were detected in alv-ALI, whereas IL12 was decreased. Altered levels of these cytokines are also associated with lung fibrotic response. CONCLUSIONS: In conclusion, we observed a typical anti-viral response in the bronchial model and a pro-fibrotic response in the alveolar model. The bro-ALI and alv-ALI models may serve as an easy and robust platform for assessing the pathogenicity of SARS-CoV-2 variants of concern at different lung regions.


Subject(s)
Lung/metabolism , Respiratory Mucosa/metabolism , SARS-CoV-2/pathogenicity , Spike Glycoprotein, Coronavirus/metabolism , Angiotensin-Converting Enzyme 2/metabolism , Bronchi/metabolism , Cytokines/metabolism , Gene Expression Profiling , Humans , Models, Biological , Protein Interaction Domains and Motifs , Recombinant Proteins/chemistry , Recombinant Proteins/metabolism , SARS-CoV-2/metabolism , Spike Glycoprotein, Coronavirus/chemistry , Toll-Like Receptor 2/metabolism , Toll-Like Receptor 4/metabolism
9.
Drug Deliv ; 29(1): 10-17, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-1577575

ABSTRACT

Aerosol therapy is used to deliver medical therapeutics directly to the airways to treat respiratory conditions. A potential consequence of this form of treatment is the release of fugitive aerosols, both patient derived and medical, into the environment and the subsequent exposure of caregivers and bystanders to potential viral infections. This study examined the release of these fugitive aerosols during a standard aerosol therapy to a simulated adult patient. An aerosol holding chamber and mouthpiece were connected to a representative head model and breathing simulator. A combination of laser and Schlieren imaging was used to non-invasively visualize the release and dispersion of fugitive aerosol particles. Time-varying aerosol particle number concentrations and size distributions were measured with optical particle sizers at clinically relevant positions to the simulated patient. The influence of breathing pattern, normal and distressed, supplemental air flow, at 0.2 and 6 LPM, and the addition of a bacterial filter to the exhalation port of the mouthpiece were assessed. Images showed large quantities of fugitive aerosols emitted from the unfiltered mouthpiece. The images and particle counter data show that the addition of a bacterial filter limited the release of these fugitive aerosols, with the peak fugitive aerosol concentrations decreasing by 47.3-83.3%, depending on distance from the simulated patient. The addition of a bacterial filter to the mouthpiece significantly reduces the levels of fugitive aerosols emitted during a simulated aerosol therapy, p≤ .05, and would greatly aid in reducing healthcare worker and bystander exposure to potentially harmful fugitive aerosols.


Subject(s)
Aerosols , COVID-19 , Drug Delivery Systems , Infectious Disease Transmission, Patient-to-Professional/prevention & control , Nebulizers and Vaporizers , Respiratory Therapy , Aerosols/administration & dosage , Aerosols/adverse effects , COVID-19/prevention & control , COVID-19/transmission , Computer Simulation , Drug Delivery Systems/instrumentation , Drug Delivery Systems/methods , Equipment Design , Humans , Infection Control/methods , Models, Biological , Particle Size , Respiratory Therapy/adverse effects , Respiratory Therapy/instrumentation , Respiratory Therapy/methods , SARS-CoV-2
10.
Sci Rep ; 11(1): 23928, 2021 12 14.
Article in English | MEDLINE | ID: covidwho-1585797

ABSTRACT

Identification of transcriptional regulatory mechanisms and signaling networks involved in the response of host cells to infection by SARS-CoV-2 is a powerful approach that provides a systems biology view of gene expression programs involved in COVID-19 and may enable the identification of novel therapeutic targets and strategies to mitigate the impact of this disease. In this study, our goal was to identify a transcriptional regulatory network that is associated with gene expression changes between samples infected by SARS-CoV-2 and those that are infected by other respiratory viruses to narrow the results on those enriched or specific to SARS-CoV-2. We combined a series of recently developed computational tools to identify transcriptional regulatory mechanisms involved in the response of epithelial cells to infection by SARS-CoV-2, and particularly regulatory mechanisms that are specific to this virus when compared to other viruses. In addition, using network-guided analyses, we identified kinases associated with this network. The results identified pathways associated with regulation of inflammation (MAPK14) and immunity (BTK, MBX) that may contribute to exacerbate organ damage linked with complications of COVID-19. The regulatory network identified herein reflects a combination of known hits and novel candidate pathways supporting the novel computational pipeline presented herein to quickly narrow down promising avenues of investigation when facing an emerging and novel disease such as COVID-19.


Subject(s)
COVID-19/genetics , Gene Expression Profiling/methods , SARS-CoV-2/pathogenicity , Sequence Analysis, RNA/methods , A549 Cells , Cell Line , Epithelial Cells/chemistry , Epithelial Cells/cytology , Epithelial Cells/virology , Gene Expression Regulation , Humans , Models, Biological , Systems Biology
11.
PLoS Comput Biol ; 17(12): e1009629, 2021 12.
Article in English | MEDLINE | ID: covidwho-1581906

ABSTRACT

Identifying order of symptom onset of infectious diseases might aid in differentiating symptomatic infections earlier in a population thereby enabling non-pharmaceutical interventions and reducing disease spread. Previously, we developed a mathematical model predicting the order of symptoms based on data from the initial outbreak of SARS-CoV-2 in China using symptom occurrence at diagnosis and found that the order of COVID-19 symptoms differed from that of other infectious diseases including influenza. Whether this order of COVID-19 symptoms holds in the USA under changing conditions is unclear. Here, we use modeling to predict the order of symptoms using data from both the initial outbreaks in China and in the USA. Whereas patients in China were more likely to have fever before cough and then nausea/vomiting before diarrhea, patients in the USA were more likely to have cough before fever and then diarrhea before nausea/vomiting. Given that the D614G SARS-CoV-2 variant that rapidly spread from Europe to predominate in the USA during the first wave of the outbreak was not present in the initial China outbreak, we hypothesized that this mutation might affect symptom order. Supporting this notion, we found that as SARS-CoV-2 in Japan shifted from the original Wuhan reference strain to the D614G variant, symptom order shifted to the USA pattern. Google Trends analyses supported these findings, while weather, age, and comorbidities did not affect our model's predictions of symptom order. These findings indicate that symptom order can change with mutation in viral disease and raise the possibility that D614G variant is more transmissible because infected people are more likely to cough in public before being incapacitated with fever.


Subject(s)
COVID-19/diagnosis , COVID-19/virology , Models, Biological , SARS-CoV-2 , COVID-19/epidemiology , China/epidemiology , Computational Biology , Cough/etiology , Diarrhea/etiology , Fever/etiology , Humans , Japan/epidemiology , Mutation , Nausea/etiology , Pandemics , SARS-CoV-2/genetics , SARS-CoV-2/pathogenicity , Time Factors , United States/epidemiology , Vomiting/etiology
12.
Ann Med ; 53(1): 181-188, 2021 12.
Article in English | MEDLINE | ID: covidwho-1575964

ABSTRACT

OBJECTIVE: To illustrate the effect of corticosteroids and heparin, respectively, on coronavirus disease 2019 (COVID-19) patients' CD8+ T cells and D-dimer. METHODS: In this retrospective cohort study involving 866 participants diagnosed with COVID-19, patients were grouped by severity. Generalized additive models were established to explore the time-course association of representative parameters of coagulation, inflammation and immunity. Segmented regression was performed to examine the influence of corticosteroids and heparin upon CD8+ T cell and D-dimer, respectively. RESULTS: There were 541 moderate, 169 severe and 156 critically ill patients involved in the study. Synchronous changes of levels of NLR, D-dimer and CD8+ T cell in critically ill patients were observed. Administration of methylprednisolone before 14 DFS compared with those after 14 DFS (ß = 0.154%, 95% CI=(0, 0.302), p=.048) or a dose lower than 40 mg per day compared with those equals to 40 mg per day (ß = 0.163%, 95% CI=(0.027, 0.295), p=.020) significantly increased the rising rate of CD8+ T cell in 14-56 DFS. CONCLUSIONS: The parameters of coagulation, inflammation and immunity were longitudinally correlated, and an early low-dose corticosteroid treatment accelerated the regaining of CD8+ T cell to help battle against SARS-Cov-2 in critical cases of COVID-19.


Subject(s)
CD8-Positive T-Lymphocytes/drug effects , COVID-19/drug therapy , Glucocorticoids/administration & dosage , Inflammation/drug therapy , Adult , Aged , Aged, 80 and over , Blood Coagulation/drug effects , Blood Coagulation/immunology , CD8-Positive T-Lymphocytes/immunology , COVID-19/blood , COVID-19/diagnosis , COVID-19/immunology , Dose-Response Relationship, Drug , Female , Fibrin Fibrinogen Degradation Products/analysis , Fibrin Fibrinogen Degradation Products/immunology , Heparin/administration & dosage , Humans , Inflammation/blood , Inflammation/diagnosis , Inflammation/immunology , Linear Models , Longitudinal Studies , Lymphocyte Count , Male , Methylprednisolone/administration & dosage , Middle Aged , Models, Biological , Retrospective Studies , SARS-CoV-2/immunology , SARS-CoV-2/isolation & purification , Severity of Illness Index , Time Factors , Time-to-Treatment , Young Adult
13.
Cells ; 10(12)2021 12 01.
Article in English | MEDLINE | ID: covidwho-1551568

ABSTRACT

The COVID-19 pandemic is a global challenge, demanding researchers address different approaches in relation to prevention, diagnostics and therapeutics. Amongst the many tactics of tackling these therapeutic challenges, small extracellular vesicles (sEVs) or exosomes are emerging as a new frontier in the field of ameliorating viral infections. Exosomes are part of extracellular vesicles (EVs)-spherical biological structures with a lipid bilayer of a diameter of up to 5000 nm, which are released into the intercellular space by most types of eukaryotic cells, both in physiological and pathological states. EVs share structural similarities to viruses, such as small size, common mechanisms of biogenesis and mechanisms for cell entry. The role of EVs in promoting the viral spread by evading the immune response of the host, which is exhibited by retroviruses, indicates the potential for further investigation and possible manipulation of these processes when tackling the spread and treatment of COVID-19. The following paper introduces the topic of the use of exosomes in the treatment of viral infections, and presents the future prospects for the use of these EVs.


Subject(s)
COVID-19/therapy , Extracellular Vesicles/metabolism , Animals , COVID-19/epidemiology , COVID-19/virology , Exosomes/metabolism , Humans , Models, Biological , SARS-CoV-2/physiology
14.
Cells ; 10(12)2021 12 01.
Article in English | MEDLINE | ID: covidwho-1542432

ABSTRACT

Autoimmune disorders are often associated with low platelet count or thrombocytopenia. In immune-induced thrombocytopenia (IIT), a common mechanism is increased platelet activity, which can have an increased risk of thrombosis. In addition, or alternatively, auto-antibodies suppress platelet formation or augment platelet clearance. Effects of the auto-antibodies are linked to the unique structural and functional characteristics of platelets. Conversely, prior platelet activation may contribute to the innate and adaptive immune responses. Extensive interplay between platelets, coagulation and complement activation processes may aggravate the pathology. Here, we present an overview of the reported molecular causes and consequences of IIT in the most common forms of autoimmune disorders. These include idiopathic thrombocytopenic purpura (ITP), systemic lupus erythematosus (SLE), antiphospholipid syndrome (APS), drug-induced thrombocytopenia (DITP), heparin-induced thrombocytopenia (HIT), COVID-19 vaccine-induced thrombosis with thrombocytopenia (VITT), thrombotic thrombocytopenia purpura (TTP), and hemolysis, the elevated liver enzymes and low platelet (HELLP) syndrome. We focus on the platelet receptors that bind auto-antibodies, the immune complexes, damage-associated molecular patterns (DAMPs) and complement factors. In addition, we review how circulating platelets serve as a reservoir of immunomodulatory molecules. By this update on the molecular mechanisms and the roles of platelets in the pathogenesis of autoimmune diseases, we highlight platelet-based pathways that can predispose for thrombocytopenia and are linked thrombotic or bleeding events.


Subject(s)
Platelet Activation , Purpura, Thrombocytopenic, Idiopathic/blood , Animals , Humans , Models, Biological , Signal Transduction
15.
Cells ; 10(12)2021 11 24.
Article in English | MEDLINE | ID: covidwho-1542427

ABSTRACT

Hyperactivation of immune responses resulting in excessive release of pro-inflammatory mediators in alveoli/lung structures is the principal pathological feature of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The cytokine hyperactivation in COVID-19 appears to be similar to those seen in rheumatoid arthritis (RA), an autoimmune disease. Emerging evidence conferred the severity and risk of COVID-19 to RA patients. Amid the evidence of musculoskeletal manifestations involving immune-inflammation-dependent mechanisms and cases of arthralgia and/or myalgia in COVID-19, crosstalk between COVID-19 and RA is often debated. The present article sheds light on the pathological crosstalk between COVID-19 and RA, the risk of RA patients in acquiring SARS-CoV-2 infection, and the aspects of SARS-CoV-2 infection in RA development. We also conferred whether RA can exacerbate COVID-19 outcomes based on available clinical readouts. The mechanistic overlapping in immune-inflammatory features in both COVID-19 and RA was discussed. We showed the emerging links of angiotensin-converting enzyme (ACE)-dependent and macrophage-mediated pathways in both diseases. Moreover, a detailed review of immediate challenges and key recommendations for anti-rheumatic drugs in the COVID-19 setting was presented for better clinical monitoring and management of RA patients. Taken together, the present article summarizes available knowledge on the emerging COVID-19 and RA crosstalk and their mechanistic overlaps, challenges, and therapeutic options.


Subject(s)
Arthritis, Rheumatoid/complications , Arthritis, Rheumatoid/therapy , COVID-19/complications , COVID-19/therapy , Animals , COVID-19/virology , Humans , Inflammation/pathology , Macrophages/metabolism , Models, Biological , SARS-CoV-2/physiology
16.
Biochem J ; 478(14): 2789-2791, 2021 07 30.
Article in English | MEDLINE | ID: covidwho-1526112

ABSTRACT

Post-translational modifications (PTMs) on histone proteins are known as epigenetic marks that demarcate the status of chromatin. These modifications are 'read' by specific reader proteins, which in turn recruit additional factors to modulate chromatin accessibility and the activity of the underlying DNA. Accumulating evidence suggests that these modifications are not restricted solely to histones, many non-histone proteins may function in a similar way through mimicking the histones. In this commentary, we briefly discuss a systematic study of the discovery of histone H3 N-terminal mimicry proteins (H3TMs), and their implications in chromatin regulation and drug discoveries.


Subject(s)
Chromatin/metabolism , DNA/metabolism , Histones/metabolism , Protein Processing, Post-Translational , Animals , Chromatin/genetics , Chromatin Assembly and Disassembly , DNA/genetics , Humans , Lysine/metabolism , Methylation , Models, Biological
17.
Sci Rep ; 11(1): 22497, 2021 11 18.
Article in English | MEDLINE | ID: covidwho-1526100

ABSTRACT

The dynamics of epidemics depend on how people's behavior changes during an outbreak. At the beginning of the epidemic, people do not know about the virus, then, after the outbreak of epidemics and alarm, they begin to comply with the restrictions and the spreading of epidemics may decline. Over time, some people get tired/frustrated by the restrictions and stop following them (exhaustion), especially if the number of new cases drops down. After resting for a while, they can follow the restrictions again. But during this pause the second wave can come and become even stronger then the first one. Studies based on SIR models do not predict the observed quick exit from the first wave of epidemics. Social dynamics should be considered. The appearance of the second wave also depends on social factors. Many generalizations of the SIR model have been developed that take into account the weakening of immunity over time, the evolution of the virus, vaccination and other medical and biological details. However, these more sophisticated models do not explain the apparent differences in outbreak profiles between countries with different intrinsic socio-cultural features. In our work, a system of models of the COVID-19 pandemic is proposed, combining the dynamics of social stress with classical epidemic models. Social stress is described by the tools of sociophysics. The combination of a dynamic SIR-type model with the classical triad of stages of the general adaptation syndrome, alarm-resistance-exhaustion, makes it possible to describe with high accuracy the available statistical data for 13 countries. The sets of kinetic constants corresponding to optimal fit of model to data were found. These constants characterize the ability of society to mobilize efforts against epidemics and maintain this concentration over time and can further help in the development of management strategies specific to a particular society.


Subject(s)
COVID-19 , Models, Biological , Pandemics , SARS-CoV-2 , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/transmission , Humans
18.
Sovrem Tekhnologii Med ; 12(4): 6-11, 2021.
Article in English | MEDLINE | ID: covidwho-1527050

ABSTRACT

The aim of the study was to modernize the existing prognostic regression models in the context of expanding knowledge about the new coronavirus infection. Materials and Methods: The modification of models and the increase in their predictive ability are based on collecting the available data from international and Russian databases. We calculated the traditional descriptive statistics and used the linear regression analysis for modeling. The work was performed using the IBM SPSS Statistics 26.0 and the R 3.6.0 (RStudio) software. Results: Manifestations of the COVID-19 epidemic process in several countries were studied; special attention was put to the number of deaths associated with the infection. A significant proportion of severe cases were noted among patients both in Russia and elsewhere. Considering that the disease incidence has reached its peak in China and Italy, we were able to improve the previously published (Sovremennye tehnologii v medicine 2020, Vol. 12, No.2) regression models and to compare their performance. The first modified model is based on the absolute increase in new cases of the infection: its regression coefficient is 0.16 (95% CI 0.137-0.181). In the extended version of the updated model, we additionally considered cases of aggravated COVID-19: the regression coefficients were 0.128 (95% CI 0.103-0.153) for model 2 and 0.053 (95% CI 0.029-0.077) for model 1.1; p=0.0001. Conclusion: Based on the most recent data (from January to May 2020) on the incidence of COVID-19 in the world, we have developed more specific versions of the basic and extended regression models of lethal outcomes. The resulting models are optimized and extrapolated to the current epidemiological situation; they will allow us to improve our analytical approach. For that purpose, data collection is currently ongoing.


Subject(s)
COVID-19 , Models, Biological , SARS-CoV-2 , COVID-19/epidemiology , COVID-19/transmission , Humans , Incidence
20.
Clin Transl Sci ; 14(6): 2348-2359, 2021 11.
Article in English | MEDLINE | ID: covidwho-1526356

ABSTRACT

Coronavirus disease 2019 (COVID-19) global pandemic is caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) viral infection, which can lead to pneumonia, lung injury, and death in susceptible populations. Understanding viral dynamics of SARS-CoV-2 is critical for development of effective treatments. An Immune-Viral Dynamics Model (IVDM) is developed to describe SARS-CoV-2 viral dynamics and COVID-19 disease progression. A dataset of 60 individual patients with COVID-19 with clinical viral load (VL) and reported disease severity were assembled from literature. Viral infection and replication mechanisms of SARS-CoV-2, viral-induced cell death, and time-dependent immune response are incorporated in the model to describe the dynamics of viruses and immune response. Disease severity are tested as a covariate to model parameters. The IVDM was fitted to the data and parameters were estimated using the nonlinear mixed-effect model. The model can adequately describe individual viral dynamics profiles, with disease severity identified as a covariate on infected cell death rate. The modeling suggested that it takes about 32.6 days to reach 50% of maximum cell-based immunity. Simulations based on virtual populations suggested a typical mild case reaches VL limit of detection (LOD) by 13 days with no treatment, a moderate case by 17 days, and a severe case by 41 days. Simulations were used to explore hypothetical treatments with different initiation time, disease severity, and drug effects to demonstrate the usefulness of such modeling in informing decisions. Overall, the IVDM modeling and simulation platform enables simulations for viral dynamics and treatment efficacy and can be used to aid in clinical pharmacokinetic/pharmacodynamic (PK/PD) and dose-efficacy response analysis for COVID-19 drug development.


Subject(s)
Antiviral Agents/pharmacology , COVID-19/drug therapy , Drug Development/methods , Host Microbial Interactions/immunology , Models, Biological , Antiviral Agents/therapeutic use , COVID-19/diagnosis , COVID-19/immunology , COVID-19/virology , Cell Death/drug effects , Cell Death/immunology , Datasets as Topic , Dose-Response Relationship, Drug , Host Microbial Interactions/drug effects , Humans , Nonlinear Dynamics , SARS-CoV-2/drug effects , SARS-CoV-2/immunology , Severity of Illness Index , Treatment Outcome , Viral Load
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