Primary resistance of HIV to antiretrovirals among individuals recently diagnosed at voluntary counselling and testing centres in the metropolitan region of Recife, Pernambuco

Determining the prevalence and type of antiretroviral (ARV) resistance among ARV-naïve individuals is important to assess the potential responses of these individuals to first-line regimens. The prevalence of primary resistance and the occurrence of recent infections among individuals with human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS) were identified among recently diagnosed patients at five sexually transmitted disease/AIDS testing and counselling centres in the metropolitan region of Recife (RMR), Pernambuco, Brazil, between 2007-2009. One-hundred and eight samples were analysed using the Calypte® BED assay. Males predominated (56%), as did patients aged 31-50 years. Twenty-three percent presented evidence of a recent HIV infection. The median CD4+ T lymphocyte count was 408 cells/mm³ and the median viral load was 3.683 copies/mL. The prevalence of primary resistance was 4.6% (confidence interval 95% = 1-8.2%) based on criteria that excluded common polymorphisms in accordance with the surveillance drug resistance mutation criteria. The prevalence of resistance to non-nucleoside reverse transcriptase, nucleoside/nucleotide reverse transcriptase and protease inhibitors were 3.8%, 1.5% and 0.8%, respectively. Fifty-seven percent of strains were from clade B, 37.7% were clade F and 3.1% were clade C; there were no statistically significant differences with respect to resistance between clades. Recent infection tended to be more common in men (p = 0.06) and in municipalities in the south of the RMR (Jaboatão dos Guararapes and Cabo de Santo Agostinho) (p = 0.046). The high prevalence of recent infection and the high prevalence of non-B strains in this poor Brazilian region merit further attention.

A new rapid colourimetric method for testing Mycobacterium tuberculosis susceptibility to isoniazid and rifampicin: a crystal violet decolourisation assay

The aim of this study was to investigate the performance of a new and accurate method for the detection of isoniazid (INH) and rifampicin (RIF) resistance among Mycobacterium tuberculosis isolates using a crystal violet decolourisation assay (CVDA). Fifty-five M. tuberculosis isolates obtained from culture stocks stored at -80ºC were tested. After bacterial inoculation, the samples were incubated at 37ºC for seven days and 100 µL of CV (25 mg/L stock solution) was then added to the control and sample tubes. The tubes were incubated for an additional 24-48 h. CV (blue/purple) was decolourised in the presence of bacterial growth; thus, if CV lost its colour in a sample containing a drug, the tested isolate was reported as resistant. The sensitivity, specificity, positive predictive value, negative predictive value and agreement for INH were 92.5%, 96.4%, 96.1%, 93.1% and 94.5%, respectively, and 88.8%, 100%, 100%, 94.8% and 96.3%, respectively, for RIF. The results were obtained within eight-nine days. This study shows that CVDA is an effective method to detect M. tuberculosis resistance to INH and RIF in developing countries. This method is rapid, simple and inexpensive. Nonetheless, further studies are necessary before routine laboratory implementation.

Sensitivity and specificity of parallel or serial serological testing for detection of canine Leishmania infection

In Brazil, human and canine visceral leishmaniasis (CVL) caused byLeishmania infantum has undergone urbanisation since 1980, constituting a public health problem, and serological tests are tools of choice for identifying infected dogs. Until recently, the Brazilian zoonoses control program recommended enzyme-linked immunosorbent assays (ELISA) and indirect immunofluorescence assays (IFA) as the screening and confirmatory methods, respectively, for the detection of canine infection. The purpose of this study was to estimate the accuracy of ELISA and IFA in parallel or serial combinations. The reference standard comprised the results of direct visualisation of parasites in histological sections, immunohistochemical test, or isolation of the parasite in culture. Samples from 98 cases and 1,327 noncases were included. Individually, both tests presented sensitivity of 91.8% and 90.8%, and specificity of 83.4 and 53.4%, for the ELISA and IFA, respectively. When tests were used in parallel combination, sensitivity attained 99.2%, while specificity dropped to 44.8%. When used in serial combination (ELISA followed by IFA), decreased sensitivity (83.3%) and increased specificity (92.5%) were observed. Serial testing approach improved specificity with moderate loss in sensitivity. This strategy could partially fulfill the needs of public health and dog owners for a more accurate diagnosis of CVL.

Selecting statistical models to study the relationship between soybean yield and soil physical properties

Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.

Improvement of a testing apparatus for dynamometry: procedures for penetrometry and influence of strain rate to quantify the tensile strength of soil aggregates

Soil penetration resistance (PR) and the tensile strength of aggregates (TS) are commonly used to characterize the physical and structural conditions of agricultural soils. This study aimed to assess the functionality of a dynamometry apparatus by linear speed and position control automation of its mobile base to measure PR and TS. The proposed equipment was used for PR measurement in undisturbed samples of a clayey "Nitossolo Vermelho eutroférrico" (Kandiudalfic Eutrudox) under rubber trees sampled in two positions (within and between rows). These samples were also used to measure the volumetric soil water content and bulk density, and determine the soil resistance to penetration curve (SRPC). The TS was measured in a sandy loam "Latossolo Vermelho distrófico" (LVd) - Typic Haplustox - and in a very clayey "Nitossolo Vermelho distroférrico" (NVdf) - Typic Paleudalf - under different uses: LVd under "annual crops" and "native forest", NVdf under "annual crops" and "eucalyptus plantation" (> 30 years old). To measure TS, different strain rates were applied using two dynamometry testing devices: a reference machine (0.03 mm s-1), which has been widely used in other studies, and the proposed equipment (1.55 mm s-1). The determination coefficient values of the SRPC were high (R² > 0.9), regardless of the sampling position. Mean TS values in LVd and NVdf obtained with the proposed equipment did not differ (p > 0.05) from those of the reference testing apparatus, regardless of land use and soil type. Results indicate that PR and TS can be measured faster and accurately by the proposed procedure.

Implications of the variability in soil penetration resistance for statistical analysis

Soil penetration resistance (PR) is a measure of soil compaction closely related to soil structure and plant growth. However, the variability in PR hampers the statistical analyses. This study aimed to evaluate the variability of soil PR on the efficiency of parametric and nonparametric analyses in indentifying significant effects of soil compaction and to classify the coefficient of variation of PR into low, medium, high and very high. On six dates, the PR of a typical dystrophic Red Ultisol under continuous no-tillage for 16 years was measured. Three tillage and/or traffic conditions were established with the application of: (i) no chiseling or additional traffic, (ii) additional compaction, and (iii) chiseling. On each date, the nineteen PR data (measured at every 1.5 cm to a depth of 28.5 cm) were grouped in layers with different thickness. In each layer, the treatment effects were evaluated by variance (ANOVA) and Kruskal-Wallis analyses in a completely randomized design, and the coefficients of variation of all analyses were classified (low, intermediate, high and very high). The ANOVA performed better in discriminating the compaction effects, but the rejection rate of null hypothesis decreased from 100 to 80 % when the coefficient of variation increased from 15 to 26 %. The values of 15 and 26 % were the thresholds separating the low/intermediate and the high/very high coefficient variation classes of PR in this Ultisol.

Evaluation of statistical and geostatistical models of digital soil properties mapping in tropical mountain regions

Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR) and geostatistical (ordinary kriging and co-kriging). The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap). Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI), soil wetness index (SWI), normalized difference vegetation index (NDVI), and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.