Using Context Information to Re-architect a System

Successful software systems cope with complexity by organizing classes into packages. However, a particular organization may be neither straightforward nor obvious for a given developer. As a consequence, classes can be misplaced, leading to duplicated code and ripple effects with minor changes effecting multiple packages. We claim that contextual information is the key to rearchitecture a system. Exploiting contextual information, we propose a technique to detect misplaced classes by analyzing how client packages access the classes of a given provider package. We define locality as a measure of the degree to which classes reused by common clients appear in the same package. We then use locality to guide a simulated annealing algorithm to obtain optimal placements of classes in packages. The result is the identification of classes that are candidates for relocation. We apply the technique to three applications and validate the usefulness of our approach via developer interviews.

Generation of a recombinant Gag virus-like-particle panel for the evaluation of p24 antigen detection by diagnostic HIV tests.

BACKGROUND Detection of HIV-1 p24 antigen permits early identification of primary HIV infection and timely intervention to limit further spread of the infection. Principally, HIV screening should equally detect all viral variants, but reagents for a standardised test evaluation are limited. Therefore, we aimed to create an inexhaustible panel of diverse HIV-1 p24 antigens. METHODS We generated a panel of 43 recombinantly expressed virus-like particles (VLPs), containing the structural Gag proteins of HIV-1 subtypes A-H and circulating recombinant forms (CRF) CRF01_AE, CRF02_AG, CRF12_BF, CRF20_BG and group O. Eleven 4th generation antigen/antibody tests and five antigen-only tests were evaluated for their ability to detect VLPs diluted in human plasma to p24 concentrations equivalent to 50, 10 and 2 IU/ml of the WHO p24 standard. Three tests were also evaluated for their ability to detect p24 after heat-denaturation for immune-complex disruption, a pre-requisite for ultrasensitive p24 detection. RESULTS Our VLP panel exhibited an average intra-clade p24 diversity of 6.7%. Among the 4th generation tests, the Abbott Architect and Siemens Enzygnost Integral 4 had the highest sensitivity of 97.7% and 93%, respectively. Alere Determine Combo and BioRad Access were least sensitive with 10.1% and 40.3%, respectively. Antigen-only tests were slightly more sensitive than combination tests. Almost all tests detected the WHO HIV-1 p24 standard at a concentration of 2 IU/ml, but their ability to detect this input for different subtypes varied greatly. Heat-treatment lowered overall detectability of HIV-1 p24 in two of the three tests, but only few VLPs had a more than 3-fold loss in p24 detection. CONCLUSIONS The HIV-1 Gag subtype panel has a broad diversity and proved useful for a standardised evaluation of the detection limit and breadth of subtype detection of p24 antigen-detecting tests. Several tests exhibited problems, particularly with non-B subtypes.

Performance of HBsAg point-of-care tests for detection of diagnostic escape-variants in clinical samples

BACKGROUND Hepatitis B viruses (HBV) harboring mutations in the a-determinant of the Hepatitis B surface antigen (HBsAg) are associated with reduced reactivity of HBsAg assays. OBJECTIVES To evaluate the sensitivity and specificity of three HBsAg point-of-care tests for the detection of HBsAg of viruses harboring HBsAg mutations. STUDY DESIGN A selection of 50 clinical plasma samples containing HBV with HBsAg mutations was used to evaluate the performance of three HBsAg point-of-care tests (Vikia(®), bioMérieux, Marcy-L'Étoile, France. Alere Determine HBsAg™, Iverness Biomedical Innovations, Köln, Germany. Quick Profile™, LumiQuick Diagnostics, California, USA) and compared to the ARCHITECT HBsAg Qualitative(®) assay (Abbott Laboratories, Sligo, Ireland). RESULTS The sensitivity of the point-of-care tests ranged from 98% to 100%. The only false-negative result occurred using the Quick Profile™ assay with a virus harboring a D144A mutation. CONCLUSIONS The evaluated point-of-care tests revealed an excellent sensitivity in detecting HBV samples harboring HBsAg mutations.