SAMBA HIV semiquantitative test, a new point-of-care viral-load-monitoring assay for resource-limited settings.

Routine viral-load (VL) testing of HIV-infected individuals on antiretroviral therapy (ART) is used to monitor treatment efficacy. However, due to logistical challenges, implementation of VL has been difficult in resource-limited settings. The aim of this study was to evaluate the performance of the SAMBA semi-Q (simple amplification-based assay semiquantitative test for HIV-1) in London, Malawi, and Uganda. The SAMBA semi-Q can distinguish between patients with VLs above and below 1,000 copies/ml. The SAMBA semi-Q was validated with diluted clinical samples and blinded plasma samples collected from HIV-1-positive individuals. SAMBA semi-Q results were compared with results from the Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 test, v2.0. Testing of 96 2- to 10-fold dilutions of four samples containing HIV-1 subtype C as well as 488 samples from patients in the United Kingdom, Malawi, and Uganda yielded an overall accuracy for the SAMBA semi-Q of 99% (95% confidence interval [CI], 93.8 to 99.9%) and 96.9% (95% CI 94.9 to 98.3%), respectively, compared to to the Roche test. Analysis of VL data from patients in Malawi and Uganda showed that the SAMBA cutoff of 1,000 copies/ml appropriately distinguished treated from untreated individuals. Furthermore, analysis of the viral loads of 232 patients on ART in Malawi and Uganda revealed similar patterns for virological control, defined as either <1,000 copies/ml (SAMBA cutoff) or <5,000 copies/ml (WHO 2010 criterion; WHO, Antiretroviral Therapy for HIV Infection in Adults and Adolescents: Recommendations for a Public Health Approach, 2010). This study suggests that the SAMBA semi-Q has adequate concurrency with the gold standard measurements for viral load. This test can allow VL monitoring of patients on ART at the point of care in resource-limited settings.

Genome-wide maps of recombination and chromosome segregation in human oocytes and embryos show selection for maternal recombination rates.

Crossover recombination reshuffles genes and prevents errors in segregation that lead to extra or missing chromosomes (aneuploidy) in human eggs, a major cause of pregnancy failure and congenital disorders. Here we generate genome-wide maps of crossovers and chromosome segregation patterns by recovering all three products of single female meioses. Genotyping >4 million informative SNPs from 23 complete meioses allowed us to map 2,032 maternal and 1,342 paternal crossovers and to infer the segregation patterns of 529 chromosome pairs. We uncover a new reverse chromosome segregation pattern in which both homologs separate their sister chromatids at meiosis I; detect selection for higher recombination rates in the female germ line by the elimination of aneuploid embryos; and report chromosomal drive against non-recombinant chromatids at meiosis II. Collectively, our findings show that recombination not only affects homolog segregation at meiosis I but also the fate of sister chromatids at meiosis II.