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Cereal cyst nematodes cause serious yield losses of wheat in Hunaghuai winter wheat growing region in China. Beauveria bassiana 08F04 isolated from the surface of cysts is a promising biological control agent for cereal cyst nematodes. As the colonization capacity is a crucial criteria to assess biocontrol effectiveness for a microbial agent candidate, we aimed to label B. bassiana 08F04 for efficient monitoring of colonization in the soil. The binary pCAM-gfp plasmid containing sgfp and hph was integrated into B. bassiana 08F04 using the Agrobacterium tumefaciens-mediated transformation. The transformation caused a significant change in mycelial and conidial yields, and in extracellular chitinase activity in some transformants. The cultural filtrates of some transformants also decreased acetylcholinesterase activity and the survival of Heterodera filipjevi second-stage juveniles relative to the wild-type strain. One transformant (G10) had a growth rate and biocontrol efficacy similar to the wild-type strain, so it was used for a pilot study of B. bassiana colonization conducted over 13 weeks. Real-time PCR results and CFU counts revealed that the population of G10 increased quickly over the first 3 weeks, then decreased slowly over the following 4 weeks before stabilizing. In addition, the application of wild-type B. bassiana 08F04 and transformant G10 significantly reduced the number of H. filipjevi females in roots by 64.4% and 60.2%, respectively. The results of this study have practical applications for ecological, biological and functional studies of B. bassiana 08F04 and for bionematicide registration.Data saturation is the most commonly employed concept for estimating sample sizes in qualitative research. Tiplaxtinin price Over the past 20 years, scholars using both empirical research and mathematical/statistical models have made significant contributions to the question How many qualitative interviews are enough? This body of work has advanced the evidence base for sample size estimation in qualitative inquiry during the design phase of a study, prior to data collection, but it does not provide qualitative researchers with a simple and reliable way to determine the adequacy of sample sizes during and/or after data collection. Using the principle of saturation as a foundation, we describe and validate a simple-to-apply method for assessing and reporting on saturation in the context of inductive thematic analyses. Following a review of the empirical research on data saturation and sample size estimation in qualitative research, we propose an alternative way to evaluate saturation that overcomes the shortcomings and challenges associated with existing methods identified in our review. Our approach includes three primary elements in its calculation and assessment Base Size, Run Length, and New Information Threshold. We additionally propose a more flexible approach to reporting saturation. To validate our method, we use a bootstrapping technique on three existing thematically coded qualitative datasets generated from in-depth interviews. Results from this analysis indicate the method we propose to assess and report on saturation is feasible and congruent with findings from earlier studies.The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its associated disease, COVID-19, has demonstrated the devastating impact of a novel, infectious pathogen on a susceptible population. Here, we explain the basic concepts of herd immunity and discuss its implications in the context of COVID-19.In December 2019, the Coronavirus disease 2019 (COVID-19), caused by a novel coronavirus SARS-CoV-2, emerged in Wuhan, Hubei province, China1 and soon spread across the world. In this ongoing pandemic, public health concerns and the urgent need for effective therapeutic measures require a deep understanding of its epidemiology, transmissibility and pathogenesis. Here we analyzed the clinical, molecular and immunological data from 326 confirmed cases of COVID-19 in Shanghai. Genomic sequences of SARS-CoV-2 assembled from 112 quality samples together with sequences in the Global Initiative on Sharing All Influenza Data (GISAID) showed a stable evolution and suggested two major lineages with differential exposure history during the early phase of the outbreak in Wuhan. Nevertheless, they exhibited similar virulence and clinical outcomes. Lymphocytopenia, especially the reduced CD4+ and CD8+ T cell counts upon admission, was predictive of disease progression. High levels of IL-6 and IL-8 during treatment were observed in patients with severe or critical disease and correlated with decreased lymphocyte count. The determinants of disease severity seemed to stem mostly from host factors such as age, lymphocytopenia, and its associated cytokine storm, whereas viral genetic variation did not significantly affect the outcomes.Drug resistant bacterial infections have led to a global health crisis. Although much effort is placed on the development of new antibiotics or variants that are less subject to existing resistance mechanisms, history shows that this strategy by itself is unlikely to solve the problem of drug resistance. Here, we discuss inhibiting evolution as a strategy that, in combination with antibiotics, may resolve the problem. Although mutagenesis is the main driver of drug resistance development, attacking the drivers of genetic diversification in pathogens has not been well explored. Bacteria possess active mechanisms that increase the rate of mutagenesis, especially at times of stress, such as during replication within eukaryotic host cells, or exposure to antibiotics. We highlight how the existence of these pro-mutagenic proteins (evolvability factors) presents an opportunity that can be capitalized upon for the effective inhibition of drug resistance development. To help move this idea to move from concept to execution, we first describe a set of criteria that an "optimal" evolvability factor would likely have to meet to be a viable therapeutic target. We then discuss the intricacies of some of the known mutagenic mechanisms, and evaluate their potential as drug targets to inhibit evolution. In principle, and as suggested by recent studies, we argue that the inhibition of these and other evolvability factors should reduce resistance development. Finally, we discuss the challenges of transitioning anti-evolution drugs from the laboratory to the clinic.