Salmonella sp.
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1019062 | ENA |
REPOSITORIES: ENA
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Project description:A novel coronavirus pneumonia, first identified in Wuhan City and referred to as COVID-19 by the World Health Organization, has been quickly spreading to other cities and countries. To control the epidemic, the Chinese government mandated a quarantine of the Wuhan city on January 23, 2020. To explore the effectiveness of the quarantine of the Wuhan city against this epidemic, transmission dynamics of COVID-19 have been estimated. A well-mixed "susceptible exposed infectious recovered" (SEIR) compartmental model was employed to describe the dynamics of the COVID-19 epidemic based on epidemiological characteristics of individuals, clinical progression of COVID-19, and quarantine intervention measures of the authority. Considering infected individuals as contagious during the latency period, the well-mixed SEIR model fitting results based on the assumed contact rate of latent individuals are within 6-18, which represented the possible impact of quarantine and isolation interventions on disease infections, whereas other parameter were suppose as unchanged under the current intervention. The present study shows that, by reducing the contact rate of latent individuals, interventions such as quarantine and isolation can effectively reduce the potential peak number of COVID-19 infections and delay the time of peak infection.
2024-09-02 | BIOMD0000000970 | BioModels
Project description:The role of geospatial disparities in the dynamics of the COVID-19 pandemic is poorly understood. We developed a spatially-explicit mathematical model to simulate transmission dynamics of COVID-19 disease infection in relation with the uneven distribution of the healthcare capacity in Ohio, U.S. The results showed substantial spatial variation in the spread of the disease, with localized areas showing marked differences in disease attack rates. Higher COVID-19 attack rates experienced in some highly connected and urbanized areas (274 cases per 100,000 people) could substantially impact the critical health care response of these areas regardless of their potentially high healthcare capacity compared to more rural and less connected counterparts (85 cases per 100,000). Accounting for the spatially uneven disease diffusion linked to the geographical distribution of the critical care resources is essential in designing effective prevention and control programmes aimed at reducing the impact of COVID-19 pandemic.
2024-09-02 | BIOMD0000000969 | BioModels
Project description:Objective: Coronavirus disease 2019 (COVID-19) is a pandemic respiratory illness spreading from person-to-person caused by a novel coronavirus and poses a serious public health risk. The goal of this study was to apply a modified susceptible-exposed-infectious-recovered (SEIR) compartmental mathematical model for prediction of COVID-19 epidemic dynamics incorporating pathogen in the environment and interventions. The next generation matrix approach was used to determine the basic reproduction number R0. The model equations are solved numerically using fourth and ffth order Runge–Kutta methods. Results: We found an R0 of 2.03, implying that the pandemic will persist in the human population in the absence of strong control measures. Results after simulating various scenarios indicate that disregarding social distancing and hygiene measures can have devastating effects on the human population. The model shows that quarantine of contacts and isolation of cases can help halt the spread on novel coronavirus.
2024-09-02 | BIOMD0000000964 | BioModels
Project description:SARS-CoV-2, a highly contagious and infectious virus is responsible for causing this COVID-19 pandemic, which has a substantial impact on global health and economy. The spectrum of clinical manifestations of COVID-19 ranges from mild or non-severe state to severe life-threatening condition in some group of people. Many patients are likely to undergo non-severe to severe transition during their infection period. For this study, we have collected blood samples of different time points from patients showing both non-severe to severe and severe to recovered transition. The clinical information of the patient’s condition is obtained from their medical records. We have investigated the proteome of different time points of the patient’s sample to analyse their trend in prognosis of the disease.
2021-05-27 | PXD023521 | Pride
Project description:Over 5 million people around the world have tested positive for the beta coronavirus SARS-CoV- 2 as of May 29, 2020, a third of which in the United States alone. These infections are associated with the development of a disease known as COVID-19, which is characterized by several symptoms, including persistent dry cough, shortness of breath, chills, muscle pain, headache, loss of taste or smell, and gastrointestinal distress. COVID-19 has been characterized by elevated mortality (over 100 thousand people have already died in the US alone), mostly due to thromboinflammatory complications that impair lung perfusion and systemic oxygenation in the most severe cases. While the levels of pro-inflammatory cytokines such as interleukin-6 (IL-6) have been associated with the severity of the disease, little is known about the impact of IL-6 levels on the proteome of COVID-19 patients. The present study provides the first proteomics analysis of sera from COVID-19 patients, stratified by circulating levels of IL-6, and correlated to markers of inflammation and renal function. As a function of IL-6 levels, we identified significant dysregulation in serum levels of various coagulation factors, accompanied by increased levels of anti-fibrinolytic components, including several serine protease inhibitors (SERPINs). These were accompanied by up-regulation of the complement cascade and antimicrobial enzymes, especially in subjects with the highest levels of IL- 6, which is consistent with an exacerbation of the acute phase response in these subjects. Although our results are observational, they highlight a clear increase in the levels of inhibitory components of the fibrinolytic cascade in severe COVID-19 disease, providing potential clues related to the etiology of coagulopathic complications in COVID-19 and paving the way for potential therapeutic interventions, such as the use of pro-fibrinolytic agents.
2020-07-29 | PXD020601 | Pride
Project description:Male sex belongs to one of the risk factors for severe COVID-19 outcome. However, underlying mechanisms that could affect sex dependent disease outcome are yet unknown. Here, we identified the CYP19A1 gene encoding for the testosterone-to-estradiol metabolizing enzyme CYP19A1 (alias aromatase) as a host factor that contributes to worsened disease outcome in male hamsters. SARS-CoV-2 infection increases CYP19A1 transcription most prominently in the lungs of male animals, which correlates with reduced circulating testosterone and increased circulating estradiol levels. Dysregulated sex hormone levels in male golden hamsters are associated with reduced lung function compared to females. Treatment of SARS-CoV-2 infected hamsters with letrozole, a clinically approved CYP19A1 inhibitor, supported recovery of dysregulated sex hormone levels and was associated with improved lung function in male but not female animals compared to placebo controls. Whole-lung transcriptome analysis in letrozole treated versus placebo treated control groups revealed key pathways associated with improved lung health in males. To seek translation of these findings into humans, we analyzed autopsy-derived lung samples of COVID-19 cases from three independent study sites. We found that CYP19A1 transcription and protein expression is strongly elevated in the lungs of men who died with COVID-19 as compared to females or non-COVID-19 controls. Our findings highlight the role of the lung as a yet unrecognized but critical organ involved in metabolic responses against respiratory virus infections. Furthermore, inhibition of CYP19A1 by the clinically approved drug letrozole may pose a new therapeutic strategy to reduce poor long-term COVID-19 outcome.
2022-01-21 | E-MTAB-11162 | biostudies-arrayexpress
Project description:The coronavirus disease 2019 (COVID-19) pandemic has placed epidemic modeling at the forefront of worldwide public policy making. Nonetheless, modeling and forecasting the spread of COVID-19 remains a challenge. Here, we detail three regional scale models for forecasting and assessing the course of the pandemic. This work demonstrates the utility of parsimonious models for early-time data and provides an accessible framework for generating policy-relevant insights into its course. We show how these models can be connected to each other and to time series data for a particular region. Capable of measuring and forecasting the impacts of social distancing, these models highlight the dangers of relaxing nonpharmaceutical public health interventions in the absence of a vaccine or antiviral therapies.
2024-09-02 | BIOMD0000000956 | BioModels
Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen responsible for the coronavirus disease-19 (COVID-19), an infectious disease characterized by a broad spectrum of symptoms, from mild to severe. Even though the COVID-19 impact on the proteome, metabolome, and lipidome has been largely investigated in different bio-fluids, to date the circulating peptidome remains unexplored. Thus, the present study aimed to apply an untargeted peptidomic approach to provide insight into alterations of circulating peptides in the development and severity of SARS-CoV-2 infection. The circulating peptidome from COVID-19 severe and mildly symptomatic patients and negative controls was characterized using LC-MS/MS analysis for identification and quantification purposes. Database search and statistical analysis allowed a complete characterization of the plasma peptidome and the detection of the most significant modulated peptides that were impacted by the infection. Our results highlighted not only that peptide abundance inversely correlates with disease severity but also the involvement of biomolecules belonging to inflammatory, immune-response, and coagulation proteins/processes. Moreover, our data suggested a possible involvement of changes in protein degradation patterns. In the present research, for the first time, the untargeted peptidomic approach enabled the identification of circulating peptides potentially playing a crucial role in the progression of COVID-19.
2023-03-11 | PXD036020 | Pride
Project description:COVID-19 Health Surveillance FVG
| PRJEB46661 | ENA