Short-term associations between extreme heat events and adverse health outcomes are well-established in epidemiologic studies. However, the use of different exposure definitions across studies has limited our understanding of extreme heat characteristics that are most important for specific health outcomes or subpopulations. Logic regression is a statistical learning method for constructing decision trees based on Boolean combinations of binary predictors. We describe how logic regression can be utilized as a data-driven approach to identify extreme heat exposure definitions using health outcome data. We evaluated the performance of the proposed algorithm in a simulation study, as well as in a 20-year time-series analysis of extreme heat and emergency department visits for 12 outcomes in the Atlanta metropolitan area. For the Atlanta case study, our novel application of logic regression identified extreme heat exposure definitions that were associated with several heat-sensitive disease outcomes (e.g., fluid and electrolyte imbalance, renal diseases, ischemic stroke, and hypertension). Exposures were often characterized by extreme apparent minimum temperature or maximum temperature over multiple days. The simulation study also demonstrated that logic regression can successfully identify exposures of different lags and duration structures when statistical power is sufficient. Logic regression is a useful tool for identifying important characteristics of extreme heat exposures for adverse health outcomes, which may help improve future heat warning systems and response plans. Logic regression is a useful tool for identifying important characteristics of extreme heat exposures for adverse health outcomes, which may help improve future heat warning systems and response plans. Direct-Acting agents (DAAs) target and inhibit essential viral replication proteins. They have revolutionized the treatment of Hepatitis C virus (HCV) infection reaching high levels of sustained virologic response. However, the detection of basal resistance-associated substitutions (RASs) to DAAs in naïve patients could be important in predicting the treatment outcome in some patients exhibiting failures to DAA-based therapies. Therefore, the aim of this work was to evaluate the presence of RASs as minority variants within intra-host viral populations, and assess their relationship to response to therapy on a multiple times relapser patient infected chronically with HCV. https://www.selleckchem.com/products/pf-477736.html infected-patient with a genotype 1a strain was evaluated. He had previously not responded to dual therapy (pegylated interferon-α plus ribavirin) and was going to start a direct-acting agent-based therapy (DAAs). He showed no significant liver fibrosis (F0). Viral RNA was extracted from serum samples taken prior and after thera RASs (pre- and post-treatment) are detected in very low frequencies (< 1%) within intra-host viral populations. Increased awareness of this association may improve detection and guide towards a personalized HCV treatment, directly improving the outcome in hard-to-treatpatients. This report shows that some patients might relapse after a DAA-based therapy even when RASs (pre- and post-treatment) are detected in very low frequencies ( less then  1%) within intra-host viral populations. Increased awareness of this association may improve detection and guide towards a personalized HCV treatment, directly improving the outcome in hard-to-treat patients. Immune responses need to be initiated rapidly, and maintained as needed, to prevent establishment and growth of infections. #link# At the same time, resources need to be balanced with other physiological processes. On the level of transcription, studies have shown that this balancing act is reflected in tight control of the initiation kinetics and shutdown dynamics of specific immune genes. To investigate genome-wide expression dynamics and trade-offs after infection at a high temporal resolution, we performed an RNA-seq time course on D. melanogaster with 20 time points post Imd stimulation. A combination of methods, including spline fitting, cluster analysis, and Granger causality inference, allowed detailed dissection of expression profiles, lead-lag interactions, and functional annotation of genes through guilt-by-association. We identified Imd-responsive genes and co-expressed, less well characterized genes, with an immediate-early response and sustained up-regulation up to 5 days after stimulation. In contfor the development of methods for analysis of a post-stress transcriptional response time-series at whole-genome scale. Carrot is a crop with a wide range of phenotypic and molecular diversity. Within cultivated carrots, the western gene pool comprises types characterized by different storage root morphology. First western carrot cultivars originated from broad-based populations. It was followed by intercrosses among plants representing early open-pollinated cultivars, combined with mass phenotypic selection for traits of interest. Selective breeding improved root uniformity and led to the development of a range of cultivars differing in root shape and size. Based on the root shape and the market use of cultivars, a dozen of market types have been distinguished. Despite their apparent phenotypic variability, several studies have suggested that western cultivated carrot germplasm was genetically non-structured. Ninety-three DcS-ILP markers and 2354 SNP markers were used to evaluate the structure of genetic diversity in the collection of 78 western type open-pollinated carrot cultivars, each represented by five plants. The mial variation among carrot plants of different market types, therefore can be used in germplasm characterization and analysis of genome relationships. The presented results likely reveal the actual genetic diversity structure within the western carrot gene pool and point at possible discrepancies within the cultivars' passport data. Both marker systems used in the study enabled detection of substantial variation among carrot plants of different market types, therefore can be used in germplasm characterization and analysis of genome relationships. The presented results likely reveal the actual genetic diversity structure within the western carrot gene pool and point at possible discrepancies within the cultivars' passport data.