Asymptomatic Transmission, the Achilles' Heel of Current Strategies to Control Covid-19.
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ABSTRACT:
SUBMITTER: Gandhi M
PROVIDER: S-EPMC7200054 | biostudies-literature | 2020 May
REPOSITORIES: biostudies-literature
Publications
Asymptomatic Transmission, the Achilles' Heel of Current Strategies to Control Covid-19.
Gandhi Monica M Yokoe Deborah S DS Havlir Diane V DV
The New England journal of medicine 20200424 22
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Project description:The unique cytokine signature of COVID-19 might provide clues to disease mechanisms and possible future therapies. Here, we propose a pathogenic model in which the alarmin cytokine, interleukin (IL)-33, is a key player in driving all stages of COVID-19 disease (ie, asymptomatic, mild-moderate, severe-critical, and chronic-fibrotic). In susceptible individuals, IL-33 release by damaged lower respiratory cells might induce dysregulated GATA-binding factor 3-expressing regulatory T cells, thereby breaking immune tolerance and eliciting severe acute respiratory syndrome coronavirus 2-induced autoinflammatory lung disease. Such disease might be initially sustained by IL-33-differentiated type-2 innate lymphoid cells and locally expanded γδ T cells. In severe COVID-19 cases, the IL-33-ST2 axis might act to expand the number of pathogenic granulocyte-macrophage colony-stimulating factor-expressing T cells, dampen antiviral interferon responses, elicit hyperinflammation, and favour thromboses. In patients who survive severe COVID-19, IL-33 might drive pulmonary fibrosis by inducing myofibroblasts and epithelial-mesenchymal transition. We discuss the therapeutic implications of these hypothetical pathways, including use of therapies that target IL-33 (eg, anti-ST2), T helper 17-like γδ T cells, immune cell homing, and cytokine balance.
| S-EPMC7546716 | biostudies-literature
Project description:One of the major challenges in controlling the coronavirus disease 2019 (COVID-19) outbreak is its asymptomatic transmission. The pathogenicity and virulence of asymptomatic COVID-19 remain mysterious. On the basis of the genotyping of 75775 SARS-CoV-2 genome isolates, we reveal that asymptomatic infection is linked to SARS-CoV-2 11083G>T mutation (i.e., L37F at nonstructure protein 6 (NSP6)). By analyzing the distribution of 11083G>T in various countries, we unveil that 11083G>T may correlate with the hypotoxicity of SARS-CoV-2. Moreover, we show a global decaying tendency of the 11083G>T mutation ratio indicating that 11083G>T hinders the SARS-CoV-2 transmission capacity. Artificial intelligence, sequence alignment, and network analysis are applied to show that NSP6 mutation L37F may have compromised the virus's ability to undermine the innate cellular defense against viral infection via autophagy regulation. This assessment is in good agreement with our genotyping of the SARS-CoV-2 evolution and transmission across various countries and regions over the past few months.
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Project description:IntroductionSARS-CoV-2 RNA is excreted in feces of most patients, therefore viral load in wastewater can be used as a surveillance tool to develop an early warning system to help and manage future pandemics.MethodsWe collected wastewater from 24 random locations at Bangkok city center and 26 nearby suburbs from July to December 2020. SARS-CoV-2 RNA copy numbers were measured using real-time polymerase chain reaction (PCR).ResultsSARS-CoV-2 RNA was detected in wastewater from both the city center and suburbs. Except for July, there were no significant differences in copy numbers between the city center and suburbs. Between October and November, a sharp rise in copy number was observed in both places followed by two to three times increase in December, related to SARS-CoV-2 cases reported for same month.ConclusionsOur study provided the first dataset related to SARS-CoV-2 viral RNA in the wastewater of Bangkok. Our results suggest that wastewater could be used as a complementary source for detecting viral RNA and predicting upcoming outbreaks and waves.
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Project description:Over the last century, scientists have embraced the idea of mobilizing antitumor immune responses in patients with cancer. In the last decade, we have seen the rebirth of cancer immunotherapy and its validation in a series of high profile clinical trials following the discovery of several immune-regulatory receptors. Recent studies point toward the tumor mutational load and resulting neoantigen burden as being crucial to tumor cell recognition by the immune system, highlighting a potentially targetable Achilles' heel in cancer. In this review, we explore the key mechanisms that underpin the recognition of cancerous cells by the immune system and discuss how we may advance immunotherapeutic strategies to target the cancer mutanome to stimulate tumor-specific immune responses, ultimately, to improve the clinical outcome for patients with cancer.
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Project description:The spread of the novel severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) emerged suddenly at the end of 2019 and the disease came to be known as coronavirus disease 2019 (COVID‑19). To date, there is no specific therapy established to treat COVID‑19. Identifying effective treatments is urgently required to treat patients and stop the transmission of SARS‑CoV‑2 in humans. For the present review, >100 publications on therapeutic agents for COVID‑19, including in vitro and in vivo animal studies, case reports, retrospective analyses and meta‑analyses were retrieved from PubMed and analyzed, and promising therapeutic agents that may be used to combat SARS‑CoV‑2 infection were highlighted. Since the outbreak of COVID‑19, different drugs have been repurposed for its treatment. Existing drugs, including chloroquine (CQ), its derivative hydroxychloroquine (HCQ), remdesivir and nucleoside analogues, monoclonal antibodies, convalescent plasma, Chinese herbal medicine and natural compounds for treating COVID‑19 evaluated in experimental and clinical studies were discussed. Although early clinical studies suggested that CQ/HCQ produces antiviral action, later research indicated certain controversy regarding their use for treating COVID‑19. The molecular mechanisms of these therapeutic agents against SARS‑CoV2 have been investigated, including inhibition of viral interactions with angiotensin‑converting enzyme 2 receptors in human cells, viral RNA‑dependent RNA polymerase, RNA replication and the packaging of viral particles. Potent therapeutic options were reviewed and future challenges to accelerate the development of novel therapeutic agents to treat and prevent COVID‑19 were acknowledged.
| S-EPMC8548951 | biostudies-literature
Project description:COVID-19 has globally spread to over 4 million people and the epidemic situation in Japan is very serious. The purpose of this research was to assess the risk of COVID-19 epidemic dissemination in Japan by estimating the current state of epidemic dissemination and providing some epidemic prevention and control recommendations. Firstly, the period from 6 January to 31 March 2020 was divided into four stages and the relevant parameters were estimated according to the imported cases in Japan. The basic reproduction number of the current stage is 1.954 (95% confidence interval (CI) 1.851-2.025), which means COVID-19 will spread quickly, and the self-healing rate of Japanese is about 0.495 (95% CI 0.437-0.506), with small variations in the four stages. Secondly, the results were applied to the actual reported cases from 1 to 5 April 2020, verifying the reliability of the estimated data using the accumulated reported cases located within the 95% confidence interval and the relative error of forecast data of five days being less than 2 . 5 % . Thirdly, considering the medical resources in Japan, the times the epidemic beds and ventilators become fully occupied are predicted as 5 and 15 May 2020, respectively. Keeping with the current situation, the final death toll in Japan may reach into the millions. Finally, based on experience with COVID-19 prevention and control in China, robust measures such as nationwide shutdown, store closures, citizens isolating themselves at home, and increasing PCR testing would quickly and effectively prevent COVID-19 spread.
| S-EPMC7312241 | biostudies-literature
Project description:SARS-CoV-2 has caused over 100 million deaths and continues to spread rapidly around the world. Asymptomatic transmission of SARS-CoV-2 is the Achilles' heel of COVID-19 public health control measures. Phylogenomic data on SARS-CoV-2 could provide more direct information about asymptomatic transmission. In this study, using a novel MINERVA sequencing technology, we traced asymptomatic transmission of COVID-19 patients in Beijing, China. One hundred and seventy-eight close contacts were quarantined, and 14 COVID-19 patients were laboratory confirmed by RT-PCR. We provide direct phylogenomic evidence of asymptomatic transmission by constructing the median joining network in the cluster. These data could help us to determine whether the current symptom-based screening should cover asymptomatic persons.
| S-EPMC7982642 | biostudies-literature
Project description:Mycobacterial pathogens adapt to environmental stresses such as nutrient deprivation by entering a non-replicative antibiotic-tolerant state of persistence. Using a biochemically-validated data-driven approach, we identified an adaptive metabolic network underlying the mycobacterial response to starvation in M. tuberculosis, M. bovis BCG and M. smegmatis. All three species show a strong Mg+2-dependence for surviving complete nutrient deprivation, accompanied by a broad phenotypic antibiotic resistance. Multivariate analysis of RNA-seq, metabolic phenotyping and biochemical data revealed substantial metabolic remodelling involving a shift to triacylglycerol utilization with adaptation to the consequent ketoacidosis by upregulation of cytochrome P450s. Paradoxically, the ketosis-driven P450 upregulation generated substantial levels of reactive oxygen species (ROS) yet conferred hypersensitivity to killing by hydrogen peroxide-induced inactivation of the P450s that reduced ROS levels. This emergent property of starvation-induced mycobacterial persistence represents a potentially exploitable vulnerability.
2016-08-25 | GSE66883 | GEO
Project description:BackgroundThe assessment of calibration performance of risk prediction models based on regression or more flexible machine learning algorithms receives little attention.Main textHerein, we argue that this needs to change immediately because poorly calibrated algorithms can be misleading and potentially harmful for clinical decision-making. We summarize how to avoid poor calibration at algorithm development and how to assess calibration at algorithm validation, emphasizing balance between model complexity and the available sample size. At external validation, calibration curves require sufficiently large samples. Algorithm updating should be considered for appropriate support of clinical practice.ConclusionEfforts are required to avoid poor calibration when developing prediction models, to evaluate calibration when validating models, and to update models when indicated. The ultimate aim is to optimize the utility of predictive analytics for shared decision-making and patient counseling.
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