a b s t r a c tCo-infections by multiple pathogens have important implications in many aspects of health, epidemiology and evolution. However, how to disentangle the non-linear dynamics of the immune response when two infections take place at the same time is largely unexplored. Using data sets of the immune response during influenza-pneumococcal coinfection in mice, we employ here topological data analysis to simplify and visualise high dimensional data sets.We identified persistent shapes of the simplicial complexes of the data in the three infection scenarios: single viral infection, single bacterial infection, and co-infection. The immune response was found to be distinct for each of the infection scenarios and we uncovered that the immune response during the co-infection has three phases and two transition points. During the first phase, its dynamics is inherited from its response to the primary (viral) infection. The immune response has an early shift (few hours post coinfection) and then modulates its response to react against the secondary (bacterial) infection. Between 18 and 26 h post co-infection the nature of the immune response changes again and does no longer resembles either of the single infection scenarios.
The R package, snpsal, developed in this study facilitates rapid and accurate estimation of the fetal karyotype from SNP array data for POC with MCC. © 2017 John Wiley & Sons, Ltd.
1Co-infections by multiple pathogens have important implications in many aspects of 2 health, epidemiology and evolution. However, how to disentangle the contributing 3 factors of the immune response when two infections take place at the same time is 4 largely unexplored. Using data sets of the immune response during 5 influenza-pneumococcal co-infection in mice, we employ here topological data analysis 6 to simplify and visualise high dimensional data sets. 7 We identified persistent shapes of the simplicial complexes of the data in the three 8 infection scenarios: single viral infection, single bacterial infection, and co-infection. 9The immune response was found to be distinct for each of the infection scenarios and we 10 uncovered that the immune response during the co-infection has three phases and two 11 transition points. During the first phase, its dynamics is inherited from its response to 12 the primary (viral) infection. The immune response has an early (few hours post 13 co-infection) and then modulates its response to finally react against the secondary 14 (bacterial) infection. Between 18 to 26 hours post co-infection the nature of the immune 15 response changes again and does no longer resembles either of the single infection 16 scenarios. 17 Author summary 18The mapper algorithm is a topological data analysis technique used for the qualitative 19 analysis, simplification and visualisation of high dimensional data sets. It generates a 20 low-dimensional image that captures topological and geometric information of the data 21 set in high dimensional space, which can highlight groups of data points of interest and 22 can guide further analysis and quantification. 23To understand how the immune system evolves during the co-infection between 24 viruses and bacteria, and the role of specific cytokines as contributing factors for these 25 severe infections, we use Topological Data Analysis (TDA) along with an extensive 26 semi-unsupervised parameter value grid search, and k-nearest neighbour analysis. 27 We find persistent shapes of the data in the three infection scenarios, single viral and 28 bacterial infections and co-infection. The immune response is shown to be distinct for 29 each of the infections scenarios and we uncover that the immune response during the 30 August 2, 2019 1/15 co-infection has three phases and two transition points, a previously unknown property 31 regarding the dynamics of the immune response during co-infection. 32Introduction 33 Co-infection is the simultaneous infection of a host by two or more phathogens. We are 34 continuously exposed to multiple potential pathogens; many people are chronically (e.g. 35 HIV) or latently (e.g. herpes viruses) infected, and we all carry potential pathogens in 36 our colonising microbial flora. This means that nearly every new infection is some sort 37 of co-infection, and globally, co-infections are the norm rather than the exception [1]. 38There is an impressive number of combinations of pathogens that derive synergy 39 from contemporan...
Although plants have several advantages for foreign protein production, cultivation of transgenic plants in artificial plant growth facilities involves the use of a great amount of electricity for lightning and air conditioning, reducing cost-effectiveness. Protein production in plants grown in darkness can overcome this problem, but the amount of protein produced in the dark is unknown. In this study, the total amount of soluble protein produced in rice seedlings germinated and grown in light or darkness were examined at several time points after germination and under different temperature, nutritional, and seedling density conditions. Our results indicate that rice seedlings grown in darkness produce a comparable amount of total soluble protein to those grown in light. Furthermore, we found that the best conditions for protein production in dark-grown rice seedlings are large seeds germinated and grown for 10–12 days at 28 °C supplemented with Murashige and Skoog medium and 30 g/l sucrose in dense planting. Therefore, our results suggest that foreign proteins can be produced in rice seedlings in the dark, with a reduced electricity use and an increase in cost-effectiveness.
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