Objective: The aim of this study was to evaluate tropism prediction performances of three algorithms [geno2pheno false-positive rate 10% (G2P10), position-specific scoring matrix (PSSM) and a combination of the 11/25 and net charge rules] and to investigate the viral and host factors potentially involved in the X4 or R5 prediction in human immunodeficiency virus-1 (HIV-1) patients. Methods: Viral tropism was determined in 179 HIV-1-infected patients eligible for CCR5 antagonist therapy. HIV-1 RNA or DNA was extracted and amplified for env gp120 sequencing. In parallel, demographic, viral, immunological and clinical determinants were analyzed. Results: According to the G2P10 algorithm, 48 patients harbored X4 or X4R5 virus. The tropism prediction was concordant for 87.7 and 88.2% of samples when comparing G2P10 with PSSM or with a combination of the 11/25 and net charge rules, respectively. X4 prediction was significantly associated with more than 35 amino acids in the V3 domain (p < 0.0001) and loss of an N-linked glycosylation site (p < 0.0001). Of the factors studied, only the nadir CD4 T-cell count was significantly associated with X4 tropism (p = 0.01). Conclusion: We determined that the X4 virus detection is closely linked to the nadir CD4 T-cell count below 100 cells/mm3 that must be taken into account when considering a CCR5 antagonist therapy switch.
Gram-negative folliculitis usually involves the face and develops in patients with acne or rosacea during long-term antibiotic therapy. Numerous pathogens have been found, but not, until now, Acinetobacter baumanii which has previously been recognized as an important cause of nosocomial infections and hospital outbreaks. We report here a case of A. baumanii folliculitis of the face, neck, arms and upper part of trunk in a patient with AIDS responding to intravenous treatment with ticarcillin-clavulanic acid. The bacterium was not found on healthy skin and the source of the infection remained unknown.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.