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Table 1. Host range of viruses that infect humans

in Molecular Clocks and Evolutionary Relationships: Possible Distortions Due to Horizontal Gene Flow
by Michael Syvanen
"... In PAGE 3: ... There appears to be a decreasing probability of cross - s pecies viral infection with in creasing evolutionary distance. This can be seen more clearly if we consider that group of viruses that are important in human disease ( Table1 ). Considerable effort has been spent ascertaining the host ranges c these viruses .... ..."

Table 1. Well-documented cases of B virus infection in humans.

in and the B Virus Working Group a
by Cercopithecine Herpesvirus, Jeffrey I. Cohen, David S. Davenport, John A. Stewart, Scott Deitchman, Julia K. Hilliard, Louisa E. Chapman, Major Article

Table 1: Smartphone viruses categorization based on infection vector.

in SmartSiren: Virus Detection and Alert for Smartphones
by Jerry Cheng, Starsky H. Y. Wong, Hao Yang, Songwu Lu
"... In PAGE 2: ... The benefit of our approach is that it provides a generic view on how a virus penetrates into a smartphone and how easily it can spread in the smartphone population. We have identified five categories of infection vectors for smartphone virus, which are listed in Table1 in a decreasing order of their expected spreading capability. Table 1 also gives some representative viruses currently in existence for each infection vector.... In PAGE 2: ... We have identified five categories of infection vectors for smartphone virus, which are listed in Table 1 in a decreasing order of their expected spreading capability. Table1 also gives some representative viruses currently in existence for each infection vector. Below, we will describe these infection vectors in more detail.... ..."

Table 1: Smartphone viruses categorization based on infection vector.

in SmartSiren: Virus Detection and Alert for Smartphones
by Jerry Cheng, Starsky H. Y. Wong, Hao Yang, Songwu Lu
"... In PAGE 2: ... The beneflt of our approach is that it provides a generic view on how a virus penetrates into a smartphone and how easily it can spread in the smartphone population. We have identifled flve categories of infection vectors for smartphone virus, which are listed in Table1 in a decreasing order of their expected spreading capability. Table 1 also gives some representative viruses currently in existence for each infection vector.... In PAGE 2: ... We have identifled flve categories of infection vectors for smartphone virus, which are listed in Table 1 in a decreasing order of their expected spreading capability. Table1 also gives some representative viruses currently in existence for each infection vector. Below, we will describe these infection vectors in more detail.... ..."

Table. Prevalence of deer-tick virus infection in adult Ixodes dammini sampled from deer or vegetation during November 1995 from Massachusetts and Connecticut No. No.

in Dispatches A New Tick-borne Encephalitis-like Virus Infecting New England
by Deer Ticks, Ixodes Dammini

Table 7.2: Parameter values for the virus morbidity experiment. A virus mor- bidity value of 0.5 represents a virus that on average kills within two epochs of infection.

in Modelling Epidemic Spread using Cellular Automata
by Shih Ching Fu

TABLE 2. Age-specific CD4+ T-lymphocye count and percent of total lymphocytes as criteria for severe immunosuppression in persons infected with human immunodeficiency virus (HIV)

in Measles, Mumps, and Rubella --- Vaccine Use and Strategies for Elimination of Measles, Rubella, and Congenital Rubella Syndrome and Control of Mumps:
by Recommendations Of The, Surveillance Division, John R. Livengood, Andrew G. Dean, M. Hewitt, Robert S. Black, Morie M. Higgins

Table 4: Probability of failing to detect a modi cation to the boot sector when infected with the Kilroy virus: NS = 128, l = 32, r = 9. Pf is the probability of failing to detect the virus. NR is the number of detectors. Each reported number is the mean of 30 trials. The number in parenthesis is the standard deviation .

in A Change-Detection Algorithm Inspired by the Immune System
by Stephanie Forrest, Alan S. Perelson, Lawrence Allen, Rajesh Cherukuri
"... In PAGE 20: ... The negative-selection algorithm can be applied to this problem by viewing the boot sector as self, generating detectors for a clean copy of the boot sector, and subsequently monitoring the boot sector for changes. Table4 shows the results of our experiments with the boot sector virus. With as few as ve detectors, the virus was detected every time.... ..."

(Table 1). This finding is in agreement with the observation that replacement of the middle isoleucine in the zipper motif by a nonconservative amino acid interferes with virus infec- tivity (9). The loss of virus infectivity in both studies could be attributed to the direct effect of a mutation in this region or a global conformational change induced by the amino acid substitutions. However, the recent finding that a synthetic peptide containing the zipper motif of gp4l blocked HIV-1 infectivity and syncytium-forming activity (36) supports the notion that the zipper motif at the N-terminal region of gp4l has a direct role in the HIV-1 life cycle. Further supporting this conclusion is the observation that the antiviral effect of the synthetic peptide was abolished once the middle isoleu- cine residue in the zipper motif was replaced by a proline residue.

in Mutational Analysis of the Leucine Zipper-Like Motif of the Human Immunodeficiency Virus Type 1 Envelope
by Transmembrane Glycoprotein, Steve S. -l. Chen, Chun-nan Lee, Twoan-ruoh Lee, F Kenneth Mcintosh 1992

TABLE 2. Differential Diagnosis of Kawasaki Disease: Dis- eases and Disorders With Similar Clinical Findings Viral infections (eg, measles, adenovirus, enterovirus, Epstein- Barr virus)

in A Statement for Health Professionals From the Committee on Rheumatic Fever, Endocarditis, and Kawasaki Disease, Council on Cardiovascular
by Matthew E. Levison, Md Thomas, J. Pallasch, Dds Donald, A. Falace, Kathryn A. Taubert, Disease In The Young, American Heart Association
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