Mariana Galvão Ferrarini; Aguiar-Pulido; Eric T. Dawson; Andrea Guarracino; Andreas Gruber; Lukas Heumos; Alexander Kanitz; Amit Kumar Lal; Brett E. Pickett; Rita Rebollo; +15 more
Mariana Galvão Ferrarini; Aguiar-Pulido; Eric T. Dawson; Andrea Guarracino; Andreas Gruber; Lukas Heumos; Alexander Kanitz; Amit Kumar Lal; Brett E. Pickett; Rita Rebollo; Ruiz-Arenas C; Olaitan Igbagbo Awe; Sarbjit Singh Bedi; Ben Busby; Georgaki M; James C; Itziar Martinez Gonzalez; Meldal B; Scheila G. Mucha; Noushin Nabavi; Neiro J; Núria Queralt-Rosinach; Philippe Rocca-Serra; de Oliveira Ds; Tsagiopoulou M;
As part of the virtual BioHackathon 2020, we formed a working group that focused on the analysis of gene expression in the context of COVID-19. More specifically, we performed transcriptome analyses on published datasets in order to better understand the interaction between the human host and the SARS-CoV-2 virus.The ideas proposed during this hackathon were divided into five projects. Projects 1 and 2 aimed to identify human genes that are important in the process of viral infection of human cells. Projects 3 and 4 aimed to take the candidate genes identified in projects 1 and 2, as well as by independent studies, and relate them to clinical information and to possible therapeutic interventions. Finally, Project 5 aimed to package and containerize software and workflows used and generated here in a reusable manner, ultimately providing scalable and reproducible workflows.
AbstractExtracellular vesicles (EVs) emerge as essential mediators of intercellular communication. DNA vaccines encoding antigens presented on EVs efficiently induce T-cell responses and EV-based vaccines containing the Spike (S) proteins of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) are highly immunogenic in mice. Thus, EVs may serve as vaccine platforms against emerging diseases, going beyond traditional strategies, with the antigen displayed identically to the original protein embedded in the viral membrane and presented as such to the immune system. Compared to their viral and pseudotyped counterparts, EV-based vaccines overcome many safety issues including pre-existing immunity against these vectors. Here, we applied our technology in natural EV’s engineering, to express the S proteins of SARS-CoV-2 embedded in the EVs, which mimic the virus with its fully native spikes. Immunizations with a two component CoVEVax vaccine, comprising DNA vector (DNAS-EV) primes, allowing in situ production of Spike harbouring EVs, and a boost using S-EVs produced in mammalian cells, trigger potent neutralizing and cellular responses in mice, in the absence of any adjuvants. CoVEVax would be the prototype of vaccines, where the sole exchange of the envelope proteins on EVs leads to the generation of new vaccine candidates against emerging viruses.
This paper aims at reconstructing the evolution of all the available COVID-19 vaccines trials extracted from the COVID-NMA database by applying the phylomemy reconstruction process. We visualize the textual contents of 1,794 trials descriptions and explore their collective structure along with their semantic dynamics. We map the continuous progress of the main COVID-19 vaccine platforms from their early-stage trials in February 2020 to their most recent combinations driven by the rise of variants of concern, third dose issues and heterologous vaccinations. This paper brings insights for the global coordination between research teams especially in crisis situations such as the COVID-19 pandemic.
Background: Senegal reported the first COVID-19 case on March 2, 2020. A nationwide cross-sectional epidemiological survey was conducted to capture the true extent of COVID-19 exposure. Methods: Multi-stage random cluster sampling of households was carried out between October 24 and November 26, 2020, at the end of the first wave of COVID-19 transmission. Anti-SARS-CoV-2 antibodies (IgG and/or IgM) were screened using three distinct ELISA assays. Adjusted prevalence for the survey design were calculated for each test separately, and thereafter combined. Crude, adjusted prevalence based on tests performances and weighted prevalence by sex-age strata were estimated to assess the seroprevalence. Findings: Of the 1,463 participants included in this study, 58·8% were women and the mean age of participants was 29·2 years (range 0·25–82·0). The national seroprevalence was estimated at 28 . 4% (95% CI: 26·1-30·8). There was substantial regional variability. Four regions recorded the highest seroprevalence: Ziguinchor (56·7%), Sedhiou (48·0%), Dakar (44·0%) and Kaolack (32·7%) whereas, Louga (11·1%) and Matam (11·2%), located in the Center-North, were less impacted in our analysis. All age groups were impacted and the prevalence of SARS-CoV-2 was comparable in symptomatic and asymptomatic groups. We estimated 4,744,392 SARS-CoV-2 (95% CI: 4,360,164 – 5,145,327) potential infected in Senegal compared to 16,089 COVID-19 RT-PCR laboratory-confirmed cases reported at the time of the survey. Interpretation: These results provide an estimate of SARS-CoV-2 virus dissemination in the Senegalese population. Preventive and control measures need to be reinforced in the country and especially in the south border regions. Funding Information: This work was supported by US Centers for Disease Control and Prevention (CDC), the Senegalese Ministry of Health, the Senegalese National Statistics and Demography Agency (ANSD), the WHO Unity program and the COVID-19 Task-force of the International Pasteur Institute Network (IPIN, REPAIR project). Declaration of Interests: We declare no competing interests. Ethics Approval Statement: All participants have consented to participate in the study. For people younger than 18 years, a legal representative provided informed consent. The study was approved by the Senegalese National Ethics Committee for Research in Health (reference number N°0176/MSAS/DPRS/CNERS, 10 October 2020).
By using panel data of 15 Chinese manufacturing industries over the 2005-2014 period from OECD TiVA and WIOD databases, the impact of China's GVCs participation on labor productivity is estimated. We find that while the productivity elasticity of the share of sector's foreign value added relative to sector's exports known as sector backward linkages is negative, that relative to China's gross exports named structure backward linkage is positive. As the annual average growth rates of both backward linkages are negative, China's backward linkages have contributed to productivity growth of 6.41% per year on average. We find that the positive productivity elasticity of the share of domestic intermediate goods embodied in exports of third countries relative to sector's exports, named sector forward linages together with a positive annual average growth rate, and that relative to China's exports named structure forward linkages together with a negative annual average growth rate, have increased productivity of 1.97% per year on average. We find finally that GVCs position is improved from 0.3 in 2005 to 0.7 in 2014. China's GVCs participation exerted positive productivity effects via optimizing resource allocation inside sectors towards more efficiency ones, via moving up from low productivity backward linkages to higher productivity forward linkages and via improving its position. This diminished the risk to be entrenched in low-profitability low productivity growth GVCs activities in China. However, the productivity contribution of backward linkages 3 times higher than that of forward linkage suggests that the future positive productivity impact of GVCs moving up may be much more difficult in a less favorable context (trade war between China and USA, reindustrialization and trade protection related to Covid-19 for example).
La pandémie de Covid-19 a bouleversé non seulement l'économie de la plupart des pays, mais aussi le domaine scientifique médical. Les opinions publiques se sont immiscées dans les choix des essais thérapeutiques comme le montrent les controverses autour des protocoles utilisant l'hydroxychloroquine. Le choix du public pour ces traitements est expliqué comme l'application d'un "pari de Pascal". Cet article analyse la formation du système de croyance des individus en appliquant la théorie de l'ambiguïté et la théorie de l'entropie d'information. Il montre que les choix du public sont le fruit de stratégies communication choisies par les promoteurs de tel ou tel traitement.
The Covid-19 pandemic upset both the economies of most countries, but also the field of medical science. As never, public opinion has interfered in the choice of therapeutic trials as evidenced by the controversies surrounding protocols using hydroxychloroquine. The public's choice for these treatments is explained as the application of a kind of individual "Pascal's wager". This article analyses the formation of the belief system of individuals by applying ambiguity theory's insights and information entropy. It shows that the public's choices are the result of efficient communication strategies chosen by these treatments' promoters.
The worldwide COVID-19 pandemic has affected the tourism sector by closing borders, reducing both the transportation of tourists and tourist demand. Developing countries, such as Tanzania, where the tourism sector contributes a high share to gross domestic product, are facing considerable economic consequences. Tourism interlinks domestic sectors such as transport, accommodation, beverages and food, and retail trade and thus plays an important role in household income. Our study assessed the macroeconomic impacts of COVID-19 on the tourism sector and the Tanzanian economy as a case study of an impacted developing economy. We used a computable general equilibrium model framework to simulate the economic impacts resulting from the COVID-19 pandemic and quantitatively analysed the economic impacts.
International audience; The disruption of supplies during the Covid-19 crisis has led to shortages but has also shown the adaptability of some companies, which have succeeded in adapting their production chains quickly to produce goods experiencing shortages: hydroalcoholic gel, masks, and medical gowns. These productive jumps from product A to product B are feasible because of the know-how proximity between the two classes of products. The proximities were computed from the analysis of co-exports and resulted in the construction of the product space. Based on the product space, as well as the customer-supplier relationships resulting from the input-output matrices, we propose a recommender system for companies. The goal is to promote distributed manufacturing by recommending a list of local suppliers to each company. As there is not always a local supplier for a desired product class, we consider the proximity between products to identify, in the absence of a supplier, a substitute supplier able to adapt its production tools to provide the required product. Our experiments are based on French data, from which we build a graph of synergies illustrating the potential productive links between companies. Finally, we show that our approach offers new perspectives to determine the level of territories' industrial resilience considering potential productive jumps.