No abstract

No abstract

No abstract

No abstract

Transmitted human immunodeficiency virus drug resistance in Europe is stable at around 8%. The impact of baseline mutation patterns on susceptibility to antiretroviral drugs should be addressed using clinical guidelines. The impact on baseline susceptibility is largest for nonnucleoside reverse transcriptase inhibitors.

Human immunodeficiency virus type 1 (HIV-1) tropism can be assessed using phenotypic assays, but this is quite laborious, expensive, and time-consuming and can be made only in sophisticated laboratories. More accessible albeit reliable tools for testing of HIV-1 tropism are needed in view of the prompt introduction of CCR5 antagonists in clinical practice. Bioinformatics tools based on V3 sequences might help to predict HIV-1 tropism; however, most of these methods have been designed by taking only genetic information derived from HIV-1 subtype B into consideration. The aim of this study was to evaluate the performances of several genotypic tools to predict HIV-1 tropism in non-B subtypes, as data on this issue are scarce. Plasma samples were tested using a new phenotypic tropism assay (Phenoscript-tropism; Eurofins), and results were compared with estimates of coreceptor usage using eight different genotypic predictor softwares (Support Vector Machine [SVM], C4.5, C4.5 with positions 8 to 12 only, PART, Charge Rule, geno2pheno coreceptor, Position-Specific Scoring Matrix X4R5 [PSSM X4R5 ], and PSSM sinsi ). A total of 150 samples were tested, with 115 belonging to patients infected with non-B subtypes and 35 drawn from subtype B-infected patients, which were taken as controls. When non-B subtypes were tested, the concordances between the results obtained using the phenotypic assay and distinct genotypic tools were as follows: 78.8% for SVM, 77.5% for C4.5, 82.5% for C4.5 with positions 8 to 12 only, 82.5% for PART, 82.5% for Charge Rule, 82.5% for PSSM X4R5 , 83.8% for PSSM sinsi , and 71.3% for geno2pheno. When clade B viruses were tested, the best concordances were seen for PSSM X4R5 (91.4%), PSSM sinsi (88.6%), and geno2pheno (88.6%). The sensitivity for detecting X4 variants was lower for non-B than for B viruses, especially in the case of PSSM sinsi (38.4% versus 100%, respectively), SVM wetcat (46% versus 100%, respectively), and PART (30% versus 90%, respectively). In summary, while inferences of HIV-1 coreceptor usage using genotypic tools seem to be reliable for clade B viruses, their performances are poor for non-B subtypes, in which they particularly fail to detect X4 variants.

Both probiotics exerted intestinal anti-inflammatory effects in DSS-mouse colitis, maybe due to their ability to restore the intestinal microbiota homeostasis and modulate the immune response. L. fermentum showed a greater beneficial effect compared to L. salivarius, which makes it more interesting for future studies.

The vaginal microbiota has importance in preserving vaginal health and defending the host against disease. The advent of new molecular techniques and computer science has allowed researchers to discover microbial composition in depth and associate the structure of vaginal microbial communities. There is a consensus that vaginal flora is grouped into a restricted number of communities, although the structure of the community is constantly changing. Certain Community-State Types (CSTs) are more associated with poor reproductive outcomes and sexually transmitted diseases (STDs) meanwhile, CSTs dominated by Lactobacillus species—particularly Lactobacillus crispatus—are more related to vaginal health. In this work, we have reviewed how modifiable and non-modifiable factors may affect normal vaginal microbiota homeostasis—including sexual behavior, race or ethnicity, and hygiene. Special interest has been given to how the use of probiotics, diet intake, and use of hormone replacement therapies (HRTs) can potentially impact vaginal microbiota composition.