Klebsiella pneumoniae
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA985895 | ENA |
REPOSITORIES: ENA
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Project description:A multicenter Italian retrospective study on COVID-19 pandemic condition and advanced Gastro - Intestinal Cancer.
Are in Italy increased the new diagnosis of GI cancer in advanced stage in the 2020 compared with 2019, as a consequence of COVID-19?
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Project description:The ongoing COVID-19 pandemic caused by SARS-CoV-2 has affected millions of people worldwide and has significant implications for public health. Host transcriptomics profiling provides comprehensive understanding of how the virus interacts with host cells and how the host responds to the virus. COVID-19 disease alters the host transcriptome, affecting cellular pathways and key molecular functions. To contribute to the global effort to understand the virus’s effect on host cell transcriptome, we have generated a dataset from nasopharyngeal swabs of 35 individuals infected with SARS-CoV-2 from the Campania region in Italy during the three outbreaks, with different clinical conditions. This dataset will help to elucidate the complex interactions among genes and can be useful in the development of effective therapeutic pathways
2023-05-25 | E-MTAB-13028 | biostudies-arrayexpress
Project description:In Italy, 128,948 confirmed cases and 15,887 deaths of people who tested positive for SARS-CoV-2 were registered as of 5 April 2020. Ending the global SARS-CoV-2 pandemic requires implementation of multiple population-wide strategies, including social distancing, testing and contact tracing. We propose a new model that predicts the course of the epidemic to help plan an effective control strategy. The model considers eight stages of infection: susceptible (S), infected (I), diagnosed (D), ailing (A), recognized (R), threatened (T), healed (H) and extinct (E), collectively termed SIDARTHE. Our SIDARTHE model discriminates between infected individuals depending on whether they have been diagnosed and on the severity of their symptoms. The distinction between diagnosed and non-diagnosed individuals is important because the former are typically isolated and hence less likely to spread the infection. This delineation also helps to explain misperceptions of the case fatality rate and of the epidemic spread. We compare simulation results with real data on the COVID-19 epidemic in Italy, and we model possible scenarios of implementation of countermeasures. Our results demonstrate that restrictive social-distancing measures will need to be combined with widespread testing and contact tracing to end the ongoing COVID-19 pandemic.
2024-09-02 | BIOMD0000000955 | BioModels
Project description:Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), whose outbreak in 2019 led to an ongoing pandemic with devastating consequences for the global economy and human health. According to World Health Organization, COVID-19 has affected more than 481 million people worldwide, with 6 million confirmed deaths. The joint efforts of the scientific community have undoubtedly increased the pace of production of COVID-19 vaccines, but there is still so much uncharted ground to cover regarding the mechanisms of SARS-CoV-2 infection, replication and host response. This issues can be approached by proteomics with unprecedented capacity paving the way for the development of more efficient strategies for patient care. In this study, we present a deep proteome analysis that has been performed on a series of COVID-19 patients aiming to identify proteins assessing the dynamics of the disease at different age ranges
2022-08-11 | PXD034045 | Pride
Project description:The on-going COVID-19 pandemic requires a deeper understanding of the long-term antibody responses that persist following SARS-CoV-2 infection. To that end, we determined epitope-specific IgG antibody responses in COVID-19 convalescent sera collected at 5 months post-diagnosis and compared that to sera from naïve individuals. Each serum sample was reacted with a high-density peptide microarray representing the complete proteome of SARS-CoV-2 as 15 mer peptides with 11 amino acid overlap and homologs of spike glycoprotein, nucleoprotein, membrane protein, and envelope small membrane protein from related human coronaviruses. Binding signatures were compared between COVID-19 convalescent patients and naïve individuals using the web service tool EPIphany.
2022-02-05 | E-MTAB-10740 | biostudies-arrayexpress
Project description:The objective of the study was to characterize the immunoreactivity profiles of IgG-reactive epitopes in COVID-19 patients with distinct disease trajectories as well as SARS-CoV-2-naïve sera, using a high-density SARS-CoV-2 whole proteome peptide microarray. The microarray comprised of a total of 5347 individual peptides, each consisting of 15 amino acids with an overlap of 13 amino acids printed in duplicate. The microarray also had a panel of the most relevant mutations from SARS-CoV-2 variants of concern like omicron, alpha, beta, gamma, delta, and others. This study consisted of 29 participants, including 10 naïve controls (5 pre-pandemic and 5 SARS-CoV-2 seronegative) and 19 RT-PCR-confirmed COVID-19 patients. The COVID-19 patients were stratified into two distinct cohorts based on their disease trajectories: the severe cohort (S), in which the patients presented moderate COVID-19 symptoms initially but eventually progressed toward severity; and the recovered cohort (R), in which severe COVID-19 patients progressed toward recovery. Our findings contribute to a deeper understanding of the immunopathogenesis of COVID-19 in patients with different disease trajectories, the effect of mutations on immunoreactivity, and potential cross-reactivity due to exposure to common cold viruses.
2025-03-31 | E-MTAB-14495 | biostudies-arrayexpress
Project description:Background: During gestation, stressors to the fetus, including viral exposure or maternal psychological distress, can fundamentally alter the neonatal epigenome, and may be associated with long-term impaired developmental outcomes. The impact of in utero exposure to the COVID-19 pandemic on the newborn epigenome has yet to be described. Methods: This study aimed to determine whether there are unique epigenetic signatures in newborns who experienced otherwise healthy pregnancies that occurred during the COVID-19 pandemic (Project RESCUE). The pre-pandemic control and pandemic cohorts (Project RESCUE) included in this study are part of a prospective observational and longitudinal cohort study that evaluates the impact of elevated prenatal maternal stress during the COVID-19 pandemic on early childhood neurodevelopment. Using buccal swabs collected at birth, differential DNA methylation analysis was performed using the Infinium MethylationEPIC arrays and linear regression analysis. Pathway analysis and gene ontology enrichment were performed on resultant gene lists. Results: Widespread differential methylation was found between neonates exposed in utero to the pandemic and pre-pandemic neonates. In contrast, there were no apparent epigenetic differences associated with maternal COVID-19 infection during pregnancy. Differential methylation was observed among genomic sites that underpin important neurological pathways that have been previously reported in the literature to be differentially methylated because of prenatal stress, such as NR3C1. Conclusions: The present study reveals that the onset and continuation of the COVID-19 pandemic has fundamentally altered the epigenomes of newborns born during this time, even in otherwise healthy pregnancies, which should be considered in current and future epigenetic studies and may act as a critical biomarker of stress.
2023-11-08 | GSE229463 | GEO
Project description:Background: In December 2019, an outbreak of coronavirus disease (later named as COVID-19) was identified in Wuhan, China and, later on, detected in other parts of China. Our aim is to evaluate the effectiveness of the evolution of interventions and self-protection measures, estimate the risk of partial lifting control measures and predict the epidemic trend of the virus in the mainland of China excluding Hubei province based on the published data and a novel mathematical model.
Methods: A novel COVID-19 transmission dynamic model incorporating the intervention measures implemented in China is proposed. COVID-19 daily data of the mainland of China excluding Hubei province, including the cumulative confirmed cases, the cumulative deaths, newly confirmed cases and the cumulative recovered cases between 20 January and 3 March 2020, were archived from the National Health Commission of China (NHCC). We parameterize the model by using the Markov Chain Monte Carlo (MCMC) method and estimate the control reproduction number (Rc), as well as the effective daily reproduction ratio- Re(t), of the disease transmission in the mainland of China excluding Hubei province.
Results: The estimation outcomes indicate that Rc is 3.36 (95% CI: 3.20-3.64) and Re(t) has dropped below 1 since 31 January 2020, which implies that the containment strategies implemented by the Chinese government in the mainland of China are indeed effective and magnificently suppressed COVID-19 transmission. Moreover, our results show that relieving personal protection too early may lead to a prolonged disease transmission period and more people would be infected, and may even cause a second wave of epidemic or outbreaks. By calculating the effective reproduction ratio, we prove that the contact rate should be kept at least less than 30% of the normal level by April, 2020.
Conclusions: To ensure the pandemic ending rapidly, it is necessary to maintain the current integrated restrict interventions and self-protection measures, including travel restriction, quarantine of entry, contact tracing followed by quarantine and isolation and reduction of contact, like wearing masks, keeping social distance, etc. People should be fully aware of the real-time epidemic situation and keep sufficient personal protection until April. If all the above conditions are met, the outbreak is expected to be ended by April in the mainland of China apart from Hubei province.
2024-09-02 | BIOMD0000000981 | BioModels