Genome-wide CRISPR Screens Reveal Host Factors Critical for SARS-CoV-2 Infection

1. Download : Download high-res image (212KB)
2. Download : Download full-size image

     

A simulation approach for power calculation in large cohort studies based on multistate models

Realistic power calculations for large cohort studies and nested case control studies are essential for successfully answering important and complex research questions in epidemiology and clinical medicine. For this, we provide a methodical framework for general realistic power calculations via simulations that we put into practice by means of an R‐based template. We consider staggered recruitment and individual hazard rates, competing risks, interaction effects, and the misclassification of covariates. The study cohort is assembled with respect to given age‐, gender‐, and community distributions. Nested case‐control analyses with a varying number of controls enable comparisons of power with a full cohort analysis. Time‐to‐event generation under competing risks, including delayed study‐entry times, is realized on the basis of a six‐state Markov model. Incidence rates, prevalence of risk factors and prefixed hazard ratios allow for the assignment of age‐dependent transition rates given in the form of Cox models. These provide the basis for a central simulation‐algorithm, which is used for the generation of sample paths of the underlying time‐inhomogeneous Markov processes. With the inclusion of frailty terms into the Cox models the Markov property is specifically biased. An “individual Markov process given frailty” creates some unobserved heterogeneity between individuals. Different left‐truncation‐ and right‐censoring patterns call for the use of Cox models for data analysis. p‐values are recorded over repeated simulation runs to allow for the desired power calculations. For illustration, we consider scenarios with a “testing” character as well as realistic scenarios. This enables the validation of a correct implementation of theoretical concepts and concrete sample size recommendations against an actual epidemiological background, here given with possible substudy designs within the German National Cohort.     

Effect of feeding boxes on the behavior of stereotyping amur tigers (Panthera tigris altaica) in the Zurich Zoo,Zurich, Switzerland

The stereotyped pacing shown by the two Amur tigers in the Zurich Zoo was hypothesized as being caused by permanently frustrated appetitive foraging behavior. Several electrically controlled feeding boxes were installed and access to each box was possible only twice a day for 15 min at semi‐random times. The boxes had to be opened actively by the tigers. Two trials were carried out: one with solitary confinement, and one with paired confinement. During box feeding, the female's stereotyped pacing was significantly reduced from 16% (solitary confinement, conventional feeding) and 7% (paired confinement, conventional feeding) to 1% (solitary confinement) and less than 0.01% (paired confinement) of the daily observed time. The female's sleeping increased significantly in both solitary and paired confinement. The male only showed a significant reduction in stereotyped pacing behavior when kept with the female (conventional feeding: 10%; box feeding: <0.01% of the daily observed time). On days with a box‐feeding regime in paired confinement, the male spent 25% (83 min) of the observed time with active behavior at the feeding boxes. The results support the hypothesis that permanently frustrated appetitive foraging behavior causes stereotyped pacing in adult tigers. Zoo Biol 21:573–584, 2002. © 2002 Wiley‐Liss, Inc.     

Construction and Characterization of a CTLA-4-Targeted scFv–Melittin Fusion Protein as a Potential Immunosuppressive Agent for Organ Transplant

Immunotoxins with selective cytotoxicity are frequently used as therapeutic immunosuppressive agents in solid-organ transplantation because of their efficiency and high specificity. In this study, we present a new recombinant immunotoxin termed anti-CTLA-4-scFv–melittin prepared from Escherichia coli aimed at clearing activated T cells at the same time avoiding all-round decline in systematic immunity. This fusion protein is composed of anti-CTLA-4-scFv unit and melittin analog unit with properties of low immunogenicity and selective cytotoxicity to CTLA-4-positive T cells. In preliminary biological activity assays, our results confirmed the feasibility of activated T cell clearance strategy and there were significant differences in cell survival rates between CTLA-4-positive group and control group at all experimental concentrations of the immunotoxin. The selective cytotoxicity, low immunogenicity, and low production cost make it an attractive alternate to traditional immunosuppressants.     

Predicting Metabolic Pathways of Small Molecules and Enzymes Based on Interaction Information of Chemicals and Proteins

Metabolic pathway analysis, one of the most important fields in biochemistry, is pivotal to understanding the maintenance and modulation of the functions of an organism. Good comprehension of metabolic pathways is critical to understanding the mechanisms of some fundamental biological processes. Given a small molecule or an enzyme, how may one identify the metabolic pathways in which it may participate? Answering such a question is a first important step in understanding a metabolic pathway system. By utilizing the information provided by chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions, a novel method was proposed by which to allocate small molecules and enzymes to 11 major classes of metabolic pathways. A benchmark dataset consisting of 3,348 small molecules and 654 enzymes of yeast was constructed to test the method. It was observed that the first order prediction accuracy evaluated by the jackknife test was 79.56% in identifying the small molecules and enzymes in a benchmark dataset. Our method may become a useful vehicle in predicting the metabolic pathways of small molecules and enzymes, providing a basis for some further analysis of the pathway systems.     

Effects of SOX2 on Proliferation,Migration and Adhesion of Human Dental Pulp Stem Cells

As a key factor for cell pluripotent and self-renewing phenotypes, SOX2 has attracted scientists’ attention gradually in recent years. However, its exact effects in dental pulp stem cells (DPSCs) are still unclear. In this study, we mainly investigated whether SOX2 could affect some biological functions of DPSCs. DPSCs were isolated from the dental pulp of human impacted third molar. SOX2 overexpressing DPSCs (DPSCs-SOX2) were established through retroviral infection. The effect of SOX2 on cell proliferation, migration and adhesion ability was evaluated with CCK-8, trans-well system and fibronectin-induced cell attachment experiment respectively. Whole genome expression of DPSCs-SOX2 was analyzed with RNA microarray. Furthermore, a rescue experiment was performed with SOX2-siRNA in DPSC-SOX2 to confirm the effect of SOX2 overexpression in DPSCs. We found that SOX2 overexpression could result in the enhancement of cell proliferation, migration, and adhesion in DPSCs obviously. RNA microarray analysis indicated that some key genes in the signal pathways associated with cell cycle, migration and adhesion were upregulated in different degree, and the results were further confirmed with qPCR and western-blot. Finally, DPSC-SOX2 transfected with SOX2-siRNA showed a decrease of cell proliferation, migration and adhesion ability, which further confirmed the biological effect of SOX2 in human DPSCs. This study indicated that SOX2 could improve the cell proliferation, migration and adhesion ability of DPSCs through regulating gene expression about cell cycle, migration and adhesion, and provided a novel strategy to develop seed cells with strong proliferation, migration and adhesion ability for tissue engineering.