Download PDF Egress (Annotated)

Free download. Book file PDF easily for everyone and every device. You can download and read online Egress (Annotated) file PDF Book only if you are registered here. And also you can download or read online all Book PDF file that related with Egress (Annotated) book. Happy reading Egress (Annotated) Bookeveryone. Download file Free Book PDF Egress (Annotated) at Complete PDF Library. This Book have some digital formats such us :paperbook, ebook, kindle, epub, fb2 and another formats. Here is The CompletePDF Book Library. It's free to register here to get Book file PDF Egress (Annotated) Pocket Guide.

Fire Technology. This overview of the information and literature provides insight to the problems relating to means of egress. To provide a comprehensive as well as critical review of the field, the reader is especially referred to the reviews and assessments of the U. National Bureau of Standards relating to the technical basis for egress standards. Also mentioned are other broadly oriented publications, along with those describing large-scale studies of human movement related to egress.

A basic list of references is suggested. For additional insight several excerpts relating to the controversial unit exit width concept are provided from U. Unable to display preview.

Download preview PDF. Skip to main content. Advertisement Hide. Development of knowledge about means of egress. This is a preview of subscription content, log in to check access. Stahl, F. Google Scholar. Then, all values for a given gene, across all sample sets WCL, PM, AD, and Towne , were averaged generating a single metric representing cumulative change in expression.

Site Stats

Genes with changes in expression between -1 and 1 represent minor conflicts between datasets but majority consensus, while values of 0 represent major conflicts between the datasets. The list of key regulators was then manually annotated and each gene was assigned a function in intracellular trafficking based on evidence from primary literature.

Genes were also assigned a value of 1 if they positively regulated the annotated process, -1 if they were inhibitory, or 0 if the reported regulatory roles were inconclusive. Lastly, the change in expression metric was multiplied by the binary positive or negative regulatory metric resulting in an aggregate measure of the change in flux along particular pathways. These cumulative measures were then mapped onto the individual pathways detailed in Figure 1 resulting in the trafficking schematic detailed in Figure 4G. Cells were fixed and shipped to Dr. Hong Yi at the Robert P. To generate a model of ERC trafficking within HCMV infected cells, we used two previously published datasets which analyzed the transcriptional and proteomic expression profiles of cellular genes at multiple time points throughout infection Gurczynski et al.


  • LinkedIn 101 Crash Course.
  • Patterns and Processes in Forest Landscapes: Multiple Use and Sustainable Management.
  • Development of knowledge about means of egress;
  • Enable all egress traffic on a specific deployment · Issue # · istio/istio · GitHub.
  • Dance Of Freedom.
  • Managing Networking!

Due to the large amount of information contained within each dataset, we used a series of significance-based filtration steps to focus our analysis Figure 2. Gene curation scheme for the transcriptional and proteomic datasets. The proteomic dataset right was similarly filtered. The resulting lists of 3, and 3, unique genes curated from the transcriptional and proteomic datasets, respectively, were used for gene ontological analysis.

EGRESS ANNOTATED Original (PDF)

The transcriptional dataset was obtained using arrays that included 47, individual mRNA-targeting probes mapping to over 28, host genes. Because of our interest in changes to normal cellular processes, we performed a SAM analysis, which enables identification of genes whose transcript levels differ significantly relative to mock-infected cells under the assorted infection conditions. The resultant dataset contained 10, probes. From the original dataset, 4, mRNA probes remained, mapping to 3, unique genes. The proteomic data also underwent filtration.

The initial dataset contained protein abundance data based on liquid chromatography coupled tandem mass spectrometry using HCMV Merlin infected fibroblasts MOI For our analysis, and to improve comparability between the datasets, we only used abundance data from the mock, 12 hpi, and 96 hpi samples. This resulted in a final list of 3, proteins representing 3, unique genes.

Following the fold-change and significance-based filtration of the transcriptional and proteomic datasets, we sought to identify the cellular processes most affected during HCMV infection, with an emphasis on ERC-related systems. To achieve this, we employed GO classification of biological processes to annotate the gene lists generated from each dataset and look for trends in targets of regulatory modifications.

Of the genes identified in the transcriptional dataset, Of the genes identified from the proteomic dataset, 2, Based on overrepresentation of GO terms, network maps were created highlighting the impact of HCMV induced changes in global regulatory schemes at the transcriptional and proteomic levels insets, Figure 3A and Supplementary Figure S1 , respectively.

argo-karaganda.kz/scripts/wiwybep/1347.php

Nuclear egress protein 1

Gene ontology-based analysis of transcriptional and proteomic regulation during HCMV infection. A Network map of overrepresented GO terms following significance filtration of the transcriptional dataset. Descendant nodes are terms nested within a given parent node; relationships between parent nodes and descendant nodes are indicated by directional arrows representing the shift from general to more specific classifiers. Genes are classified based on the deepest level of annotation available and node areas are proportional to the number of genes classified by each term with some genes being classified by more than one term at a given level in the hierarchy; specific values have been listed for nodes of interest.

A comparable network map based on overrepresentation of GO annotations in the filtered proteomics dataset may be found in Supplementary Figure S1. B Comparison of gene annotation between the transcriptional and proteomic datasets. Values represent the number of overrepresented genes per term. Of the successfully annotated genes, Of the annotated transcript-associated genes, 8. The differences in representation within these groups can likely be ascribed to these processes being modulated at the transcriptional and protein levels through mechanisms such as mRNA and protein stability, translation efficiency, and post-translational modifications.

Based on the GO analysis, we looked closer at the relationships between the transcriptional and proteomic datasets Figure 4. Because we were interested in comparing patterns in regulation between the two datasets, we removed any genes represented in only one of the original datasets. The final transcriptional dataset included 1, probes for both AD and Towne- infected samples.

The final proteomic dataset included 1, proteins in the WCL fraction and proteins in the PM fraction. Expression profiles of cellular genes required for transport are modulated as a function of time during HCMV infection. A,B Heatmaps of transcript A and protein B abundances demonstrating fluctuations over the course of infection.

Managing Networking | Cluster Administration | OpenShift Container Platform

Rows are individually normalized based on standard deviation around the mean log 2 abundances z -score; graphs at right-hand side. Right-hand side labels indicate genes that are i upregulated over the course of infection, ii downregulated over the course of infection, or iii up- or downregulated early in infection but return to mock-like levels late in infection. B Regions without color indicate missing data. Thicker arrows indicate the predicted flow of traffic relative to uninfected cells see Supplementary Table S1 for more information. Because virion envelopment and egress occur late in infection, we employed heatmaps to display changes in the abundance of gene products from the transcriptional and proteomic datasets as a function of time after infection Figures 4A,B.

Apollo 15 Command Module Onboard Voice Transcription: Some Intriguing Remarks

Within each row, data for individual genes were normalized around the mean log 2 abundance and clustering was done based on the similarity of expression patterns. Regions within the protein-based heatmap clustered first on the completeness of the data, then on patterns of abundance. Within each dataset, three distinct regulatory profiles are apparent relative to mock: i upregulation over the course of infection, ii downregulation over the course of infection, and iii up- or downregulation early in infection that returns to mock-like levels late in infection right-hand side labels, Figures 4A,B.

These regulatory patterns occurred across a wide range of abundances in the transcriptional data, a feature which was obscured in the proteomic data as a result of the format used to report values in the raw dataset, thus the protein-associated plot shows very little variation right-hand side graphs, Figures 4A,B. The datasets were initially compared within themselves via linear regression to establish a baseline for comparison.

Overall, the observed patterns demonstrate the multi-faceted and coherent effect HCMV infection has on shaping the expression of host genes involved in cytoplasmic trafficking. Finally, the observed changes in relative gene expression were mapped onto pathways connecting the major components of the ERC Figure 4G. In the absence of quantitative rate-specific data for transport through the ERC, the magnitude of impact for each change in gene expression was assumed to be equivalent.

Consistent with prior observations of cargo sequestration near the center of the cVAC during infection Hook et al.


  • Prinz Eugen: Heros und Neurose (German Edition)!
  • Gene Ontology and GO Annotations.
  • Mathematical Methods and Modelling in Hydrocarbon Exploration and Production: 7 (Mathematics in Industry).

Conversely, other pathways, such as the SV-associated exocytosis, appeared to be favored during infection suggesting a potential mechanism of virion egress. Due to the accumulated evidence that SV-associated pathways are involved in virion egress, we compared the relative abundances of transcripts Figure 5A and proteins Figure 5B for genes known to regulate SV exocytosis Figure 5C.

Because many of the events related to SV docking and fusion at the cell surface are mediated through low abundance, membrane-bound proteins, sensitivity limitations prevented several from being detected in the PM fraction of the proteomic dataset. In contrast to the apparent decrease in exocytic, but not endocytic, transport via early and recycling endosomes Figure 4G , expression of SV exocytosis regulatory genes shifted in a direction indicative of upregulation of the pathway as a whole Supplementary Table S1 and Figure 5C.

Interestingly, the data suggest elevated activity for both individual- and compound-exocytic pathways. Samples for which protein data was unavailable are marked as not determined ND.

Nuclear egress protein 2

C Schematic outlining trafficking events required for SV exocytosis. Images in panels iii and vi show an enlarged view of the areas indicated in panels ii and v , respectively. To assess the potential relevance of these observations, we examined a collection of electron micrographs previously obtained by our laboratory Das et al.

Of 89 enveloped virions, While it is unclear whether single- and multiple-virion vesicles are capable of delivering infectious payload to the PM, the quantity of each and the apparent integrity of the contained virions suggest that both single and compound vesicles may play a role in HCMV virion egress. Despite the public health burden imposed by HCMV, there is a deficiency in the number and target diversity of licensed treatment options. A major factor contributing to these inadequacies is the lack of information regarding HCMV maturation, particularly during cytoplasmic stages of the viral replication cycle.