Biomedical subjects
Publications and source records attributed to Jonathan Ball.
In this commentary, recent papers covering pandemic influenza, acute respiratory distress syndrome and cardiovascular issues are discussed.
Human immunodeficiency virus type 1 (HIV-1) R5 isolates that predominantly use CCR5 as a coreceptor are frequently described as macrophage tropic. Here, we compare macrophage tropism conferred by HIV-1 R5 envelopes that were derived directly by PCR from patient tissue. This approach avoids potentially selective culture protocols used in virus isolation. Envelopes were amplified (i) from blood and semen of adult patients and (ii) from plasma of pediatric patients. The phenotypes of these envelopes were compared to those conferred by an extended panel of envelopes derived from brain and lymph node that we reported previously. Our results show that R5 envelopes vary by up to 1,000-fold in their capacity to confer infection of primary macrophages. Highly macrophage-tropic envelopes were predominate in brain but were infrequent in semen, blood, and lymph node samples. We also confirmed that the presence of N283 in the C2 CD4 binding site of gp120 is associated with HIV-1 envelopes from the brain but absent from macrophage-tropic envelopes amplified from blood and semen. Finally, we compared infection of macrophages, CD4(+) T cells, and peripheral blood mononuclear cells (PBMCs) conferred by macrophage-tropic and non-macrophage-tropic envelopes in the context of full-length replication competent viral clones. Non-macrophage-tropic envelopes conferred low-level infection of macrophages yet infected CD4(+) T cells and PBMCs as efficiently as highly macrophage-tropic brain envelopes. The lack of macrophage tropism for the majority of the envelopes amplified from lymph node, blood, and semen is striking and contrasts with the current consensus that R5 primary isolates are generally macrophage tropic. The extensive variation in R5 tropism reported here is likely to have an important impact on pathogenesis and on the capacity of HIV-1 to transmit.
Controversies abound in the areas of blood transfusion, albumin, lipoproteins in sepsis and pulmonary artery catheters. We are also making too many errors, but at least there is a new nitric oxide therapy in the offing.
This review introduces logistic regression, which is a method for modelling the dependence of a binary response variable on one or more explanatory variables. Continuous and categorical explanatory variables are considered.
This review introduces some commonly used methods for assessing the performance of a diagnostic test. The sensitivity, specificity and likelihood ratio of a test are discussed. The uses of the receiver operating characteristic curve and the area under the curve are explained.
This review introduces methods of analyzing data arising from studies where the response variable is the length of time taken to reach a certain end-point, often death. The Kaplan-Meier methods, log rank test and Cox's proportional hazards model are described.
Relative risk and odds ratio have been introduced in earlier reviews (see Statistics reviews 3, 6 and 8). This review describes the calculation and interpretation of their confidence intervals. The different circumstances in which the use of either the relative risk or odds ratio is appropriate and their relative merits are discussed. A method of measuring the impact of exposure to a risk factor is introduced. Measures of the success of a treatment using data from clinical trials are also considered.
This review introduces nonparametric methods for testing differences between more than two groups or treatments. Three of the more common tests are described in detail, together with multiple comparison procedures for identifying specific differences between pairs of groups.
This review introduces one-way analysis of variance, which is a method of testing differences between more than two groups or treatments. Multiple comparison procedures and orthogonal contrasts are described as methods for identifying specific differences between pairs of treatments.
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This review introduces methods for investigating relationships between two qualitative (categorical) variables. The chi2 test of association is described, together with the modifications needed for small samples. The test for trend, in which at least one of the variables is ordinal, is also outlined. Risk measurement is discussed. The calculation of confidence intervals for proportions and differences between proportions are described. Situations in which samples are matched are considered.
The present review introduces methods of analyzing the relationship between two quantitative variables. The calculation and interpretation of the sample product moment correlation coefficient and the linear regression equation are discussed and illustrated. Common misuses of the techniques are considered. Tests and confidence intervals for the population parameters are described, and failures of the underlying assumptions are highlighted.
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The present review introduces nonparametric methods. Three of the more common nonparametric methods are described in detail, and the advantages and disadvantages of nonparametric versus parametric methods in general are discussed.
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The present review introduces the commonly used t-test, used to compare a single mean with a hypothesized value, two means arising from paired data, or two means arising from unpaired data. The assumptions underlying these tests are also discussed.
The present review introduces the notion of statistical power and the hazard of under-powered studies. The problem of how to calculate an ideal sample size is also discussed within the context of factors that affect power, and specific methods for the calculation of sample size are presented for two common scenarios, along with extensions to the simplest case.