Risk ratios, odds ratios, and hazard ratios are three common, but often misused, statistical measures in clinical research. In this paper, the authors dissect what each of these terms define, and provide examples from the medical literature to illustrate each of these statistical measures. Finally, the correct and incorrect methods to use these measures are summarized.

T cells recognise foreign antigen presented by antigen presenting cells at extremely low concentrations, and are able to discriminate between different ligands with high specificity. McKeithan's kinetic proofreading model is often invoked to explain this sensitivity and specificity of the T cell. In this paper, we analyse the strengths and limitations of this model, and suggest that it does not seem adequate to explain the observed degree of T cell sensitivity, specificity and robustness.

Abst ract : The start of the post-genomic era provides a useful juncture for reflection on the state of antibody engineering, which will be a critical technology for relating function and pathology to genomic sequence in biology and medicine. The phenomenal progress in deciphering the human genome [1,2] has given significant impetus to the application of engineered antibodies in proteomics. Thus, advances in phage display antibody libraries can now help to define novel gene function and the measurement of abnormal protein expression in pathological states. Furthermore, intrabody and antibody engineering provide vehicles for the development of molecular medicines of the future. In addition to these new directions, antibody engineering has begun to show concrete success in its longterm efforts to develop targeted immunotherapies for cancer and other diseases. The cornerstones of clinical development are the detailed academic clinical trials that continue to push the boundaries of engineered antibodies into the real world [3]. The field displays a healthy impatience for practical results, as research Engineered antibodies take center stage.

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