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Systemic multicompartmental effects of the gut microbiome on mouse metabolic phenotypes
To characterize the impact of gut microbiota on host metabolism, we investigated the multicompartmental metabolic profiles of a conventional mouse strain (C3H/HeJ) (n=5) and its germ-free (GF) equivalent (n=5). We confirm that the microbiome strongly impacts on the metabolism of bile acids through the enterohepatic cycle and gut metabolism (higher levels of phosphocholine and glycine in GF liver and marked higher levels of bile acids in three gut compartments). Furthermore we demonstrate that (1) well-defined metabolic differences exist in all examined compartments between the metabotypes of GF and conventional mice: bacterial co-metabolic products such as hippurate (urine) and 5-aminovalerate (colon epithelium) were found at reduced concentrations, whereas raffinose was only detected in GF colonic profiles. (2) The microbiome also influences kidney homeostasis with elevated levels of key cell volume regulators (betaine, choline, myo-inositol and so on) observed in GF kidneys. (3) Gut microbiota modulate metabotype expression at both local (gut) and global (biofluids, kidney, liver) system levels and hence influence the responses to a variety of dietary modulation and drug exposures relevant to personalized health-care investigations
Role of Biotransformation Studies in Minimizing Metabolism-Related Liabilities in Drug Discovery
Metabolism-related liabilities continue to be a major cause of attrition for drug candidates in clinical development. Such problems may arise from the bioactivation of the parent compound to a reactive metabolite capable of modifying biological materials covalently or engaging in redox-cycling reactions leading to the formation of other toxicants. Alternatively, they may result from the formation of a major metabolite with systemic exposure and adverse pharmacological activity. To avert such problems, biotransformation studies are becoming increasingly important in guiding the refinement of a lead series during drug discovery and in characterizing lead candidates prior to clinical evaluation. This article provides an overview of the methods that are used to uncover metabolism-related liabilities in a pre-clinical setting and offers suggestions for reducing such liabilities via the modification of structural features that are used commonly in drug-like molecules
Cross-linguistic patterns in the acquisition of quantifiers
Learners of most languages are faced with the task of acquiring words to talk about number and quantity. Much is known about the order of acquisition of number words as well as the cognitive and perceptual systems and cultural practices that shape it. Substantially less is known about the acquisition of quantifiers. Here, we consider the extent to which systems and practices that support number word acquisition can be applied to quantifier acquisition and conclude that the two domains are largely distinct in this respect. Consequently, we hypothesize that the acquisition of quantifiers is constrained by a set of factors related to each quantifier's specific meaning. We investigate competence with the expressions for "all," "none," "some," "some not," and "most" in 31 languages, representing 11 language types, by testing 768 5-y-old children and 536 adults. We found a cross-linguistically similar order of acquisition of quantifiers, explicable in terms of four factors relating to their meaning and use. In addition, exploratory analyses reveal that languageand learner-specific factors, such as negative concord and gender, are significant predictors of variation
Nature of learning environment in concurrent enrollment mathematics classrooms: a cluster analysis
Concurrent enrollment programs, which allow college credit-bearing classes to be offered in the high school taught by qualified high-school teachers, are a potential solution to the student debt issues impacting the United States and other countries. However, the learning environments of these rapidly-growing programs have never been studied. Because concurrent enrollment classes are taught in high schools with college-level rigour, they present a learning environment that is distinct from both high-school and college classrooms. This study had two broad goals of (1) determining if the What Is Happening In this Class? (WIHIC) questionnaire is a valid and reliable instrument for the concurrent enrollment environment and, if so, (2) investigating the learning environments of 68 concurrent enrollment teachersâ classrooms using the WIHIC. The WIHIC was found to be valid and reliable, and cluster analysis of the concurrent enrollment classes revealed three distinct types of learning environments which we labeled âmost conduciveâ for learning, âconduciveâ and âleast conduciveâ. A follow-up discriminant function analysis revealed that the WIHIC scales of teacher support, involvement and student cohesion were most influential in determining cluster membership