These findings provide novel insights into microbial succession in the respiratory tract in infancy and link early-life profiles to microbiota stability and respiratory health characteristics. New prospective studies should elucidate potential implications of our findings for early diagnosis and prevention of respiratory infections. Clinical trial registered with www.clinicaltrials.gov (NCT00189020).

Cervicovaginal microbiota not dominated by lactobacilli may facilitate transmission of HIV and other sexually transmitted infections (STIs), as well as miscarriages, preterm births and sepsis in pregnant women. However, little is known about the exact nature of the microbiological changes that cause these adverse outcomes. In this study, cervical samples of 174 Rwandan female sex workers were analyzed cross-sectionally using a phylogenetic microarray. Furthermore, HIV-1 RNA concentrations were measured in cervicovaginal lavages of 58 HIV-positive women among them. We identified six microbiome clusters, representing a gradient from low semi-quantitative abundance and diversity dominated by Lactobacillus crispatus (cluster R-I, with R denoting 'Rwanda') and L. iners (R-II) to intermediate (R-V) and high abundance and diversity (R-III, R-IV and R-VI) dominated by a mixture of anaerobes, including Gardnerella, Atopobium and Prevotella species. Women in cluster R-I were less likely to have HIV (P ¼ 0.03), herpes simplex virus type 2 (HSV-2; Po0.01), and high-risk human papillomavirus (HPV; Po0.01) and had no bacterial STIs (P ¼ 0.15). Statistically significant trends in prevalence of viral STIs were found from low prevalence in cluster R-I, to higher prevalence in clusters R-II and R-V, and highest prevalence in clusters R-III/R-IV/R-VI. Furthermore, only 10% of HIV-positive women in clusters R-I/R-II, compared with 40% in cluster R-V, and 42% in clusters R-III/ R-IV/R-VI had detectable cervicovaginal HIV-1 RNA (P trend ¼ 0.03). We conclude that L. crispatusdominated, and to a lesser extent L. iners-dominated, cervicovaginal microbiota are associated with a lower prevalence of HIV/STIs and a lower likelihood of genital HIV-1 RNA shedding.

Smart premise selection is essential when using automated reasoning as a tool for large-theory formal proof development. A good method for premise selection in complex mathematical libraries is the application of machine learning to large corpora of proofs. This work develops learning-based premise selection in two ways. First, a newly available minimal dependency analysis of existing high-level formal mathematical proofs is used to build a large knowledge base of proof dependencies, providing precise data for ATP-based re-verification and for training premise selection algorithms. Second, a new machine learning algorithm for premise selection based on kernel methods is proposed and implemented. To evaluate the impact of both techniques, a benchmark consisting of 2078 large-theory mathematical problems is constructed,extending the older MPTP Challenge benchmark. The combined effect of the techniques results in a 50% improvement on the benchmark over the Vampire/SInE state-of-the-art system for automated reasoning in large theories.Comment: 26 page

A cross-sectional observational study was conducted to evaluate interindividual biochemical variation in unstimulated whole saliva in a population of 268 systemically healthy young students, 18-30 yr of age, with no apparent caries lesions or periodontal disease. Salivary flow rate, protein content, pH, buffering capacity, mucins MUC5B and MUC7, albumin, secretory IgA, cystatin S, lactoferrin, chitinase, amylase, lysozyme, and proteases were measured using ELISAs and enzymatic activity assays. Significant differences were found between male and female subjects. Salivary pH, buffering capacity, protein content, MUC5B, secretory IgA, and chitinase activity were all lower in female subjects compared with male subjects, whereas MUC7 and lysozyme activity were higher in female subjects. There was no significant difference between sexes in salivary flow rate, albumin, cystatin S, amylase, and protease activity. Principal component analysis (PCA) and spectral clustering (SC) were used to assess intervariable relationships within the data set and to identify subgroups. Spectral clustering identified two clusters of participants, which were subsequently described. This study provides a comprehensive overview of the distribution and inter-relations of a set of important salivary biochemical variables in a systemically healthy young adult population, free of apparent caries lesions and periodontal disease. It highlights significant gender differences in salivary biochemistry.

Oral contraceptive and injectable use were associated with several STIs but not with VMB composition. The increased herpes simplex virus-2 prevalence among injectable users might explain the potentially higher HIV risk in these women, but more research is needed to confirm these results and elucidate biological mechanisms.