No abstract

We present QIIME 2, an open-source microbiome data science platform accessible to users spanning the microbiome research ecosystem, from scientists and engineers to clinicians and policy makers. QIIME 2 provides new features that will drive the next generation of microbiome research. These include interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.

In the version of this article initially published, some reference citations were incorrect. The three references to Jupyter Notebooks should have cited Kluyver et al. instead of Gonzalez et al. The reference to Qiita should have cited Gonzalez et al. instead of Schloss et al. The reference to mothur should have cited Schloss et al. instead of McMurdie & Holmes. The reference to phyloseq should have cited McMurdie & Holmes instead of Huber et al. The reference to Bioconductor should have cited Huber et al. instead of Franzosa et al. And the reference to the biobakery suite should have cited Franzosa et al. instead of Kluyver et al. The errors have been corrected in the HTML and PDF versions of the article.

Obesity is associated with a higher risk of breast cancer mortality. The gold standard approach to weight loss is in-person counseling, but telephone counseling may be more feasible. We examined the effect of in-person versus telephone weight loss counseling versus usual care on 6-month changes in body composition, physical activity, diet, and serum biomarkers. MethodsOne hundred breast cancer survivors with a body mass index $ 25 kg/m 2 were randomly assigned to in-person counseling (n = 33), telephone counseling (n = 34), or usual care (UC) (n = 33). In-person and telephone counseling included 11 30-minute counseling sessions over 6 months. These focused on reducing caloric intake, increasing physical activity, and behavioral therapy. Body composition, physical activity, diet, and serum biomarkers were measured at baseline and 6 months. ResultsThe mean age of participants was 59 6 7.5 years old, with a mean BMI of 33.1 6 6.6 kg/m 2 , and the mean time from diagnosis was 2.9 6 2.1 years. Fifty-one percent of the participants had stage I breast cancer. Average 6-month weight loss was 6.4%, 5.4%, and 2.0% for in-person, telephone, and UC groups, respectively (P = .004, P = .009, and P = .46 comparing in-person with UC, telephone with UC, and in-person with telephone, respectively). A significant 30% decrease in C-reactive protein levels was observed among women randomly assigned to the combined weight loss intervention groups compared with a 1% decrease among women randomly assigned to UC (P = .05). ConclusionBoth in-person and telephone counseling were effective weight loss strategies, with favorable effects on C-reactive protein levels. Our findings may help guide the incorporation of weight loss counseling into breast cancer treatment and care.

Mosaic loss of the Y chromosome (mLOY) is the most commonly reported large structural somatic event. Previous studies have indicated age and cigarette smoking increase the risk of mLOY, but the relationship of other exposures with mLOY and mLOY with disease has not been adequately investigated. We characterized mLOY in a large cohort of 223,338 men from the UK Biobank by scanning for deviations in genotyping array median log2 intensity ratios (mLRR) of the Y chromosome using a standard algorithm. A total of 3,789 (1.7%) men showed evidence for mLOY (mLRR < −0.15). In multivariable-adjusted logistic regression models, we found that mLOY increases exponentially with age (overall P-value < 4.9 × 10−324; p-value for the quadratic term = 2.1 × 10−7), and observed a strong association with current smoking (P-value = 7.8 × 10−184). We observed less mLOY in men of African ancestry (0.4%) compared to men of European ancestry (1.8%, P-value = 0.003). Although mLOY was not associated with prevalent cancer (P-value = 0.61), associations were observed for diabetes (P-value = 0.003) and cardiovascular disease (P-value = 0.01). Using Cox proportional hazards regression models, mLOY was associated with all-cause mortality among men with a high proportion of cells affected (mLRR < −0.40; HR = 1.35, 95% CI = 1.08–1.70, P-value = 0.009). In conclusion, mLOY was associated with several health-related factors as well as with all-cause mortality. Further functional studies are warranted to understand how and in what way mLOY could influence adult male health.