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BACKGROUND: Resistance testing is increasingly accepted as a tool in guiding the selection of human immunodeficiency virus type 1 (HIV-1) antiretroviral therapy in HIV-1 infected individuals who fail their current regimen. OBJECTIVES: To descriptively compare the correlation between virologic treatment response and results using three genotypic HIV-1 drug resistance interpretation systems: the VERSANT HIV-1 Resistance Assay (LiPA) system and two sequence-based interpretation systems. STUDY DESIGN: Specimens from 213 HIV-1-infected subjects, either starting (n=104) or switching to (n=109) a regimen of three or four antiretroviral drugs, were collected retrospectively at baseline and after 3 months of uninterrupted therapy. The correlation between viral load change and the number of predicted active drugs in the treatment regimen was assessed. An interpretation algorithm was recently developed to process VERSANT HIV-1 Resistance Assay (LiPA) data. The number of active drugs predicted using this algorithm was rank correlated with the viral load change over a 3-month treatment period. For comparison, a similar calculation was made using two sequence-based algorithms (REGA version 5.5 and VGI GuideLines Rules 4.0), both applied on the same sequences. RESULTS: Statistically significant (p<0.05) correlation coefficients for each of the three HIV-1 drug resistance interpretation systems were observed in the treatment-experienced subjects on a 3-drug regimen (-0.39, -0.38, and -0.42, respectively) as well as on a 4-drug regimen (-0.33, -0.31, and -0.37, respectively). However, no significant correlation was observed in treatment-naive subjects, probably due to the very low frequency of drug resistance in these subjects. CONCLUSION: All three genotypic drug resistance interpretation systems (LiPA version 1, REGA version 5.5, and VGI GuideLines Rules 4.0) were statistically significantly correlated with virologic therapy response as measured by viral load testing.

A geographically-based framework for landuse suitability assessment and land capability classification in Ibulao watershed, Philippines was developed and used in this study. Landuse suitability assessment was based primarily on soil erosion, the results of which were compared with the outcome of suitability assessments based on two land classification systems in the Philippines. The Ibulao watershed was subdivided into 10-ha cells, and each cell was independently evaluated with the aid of a geographic information system called MAP. The soil erosion rates for each cell were estimated using the MUSLE. The surface runoff and peak runoff rates were simulated using an infiltration-kinematic routing model, an event-based stochastic rainfall duration model, and the CREAMS model. The land capability classification was based on erosion index representing the inherent soil erodibility of a cell computed on the basis of runoff erosivity factor, soil erodibility factor, and the slope length-gradient factor. The results of capability classification were used to identify the different alternative uses of any cell in the watershed. The framework described in this study for landuse suitability assessment and land capability classification illustrated potentials for applications to the management and allocation of land resources in the Philippines. An erosion-based landuse assessment and land capability classification appears to be a better alternative to a slope-based system as far as the following are concerned: (1) identification of landuses which would not jeopardize the long term productivity and stability of an area; (2) a more accurate and meaningful land capability description and classification; and (3) making more lands available for various alternative uses by using criteria such as soil erosion which can easily be manipulated.