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The present study investigates whether or not Japanese college students whose English vocabularies differ in size construct structurally distinct L2 English mental lexicons (ML) of nouns, and whether the way that the lexical items in their ML are connected with others retains any characteristic features. The study aims at confirming the findings of Orita, Kobayashi, Murasato, Kamimoto, Yoshii, and Lavin (2013), which revealed structurally marked distinctions in the L2 English ML of verbs between two participant groups (Japanese college students) having different vocabulary sizes are reflected in their L2 English ML of nouns. A free word sorting task using 24 English nouns were given t0 30 college students with a small vocabulary size (4426.7, SD = 755.3) and 30 college students with a large vocabulary size (5778.3, SD = 690.8), whose vocabulary sizes were significantly different from each other (t (58)=7.233, P < 0.05, two-tailed).Permutation tests (number of generated random permutations = 5,000) indicated that noun structures in the ML were statistically significantly different from each other between the two participant groups. The sorting task results also showed that participants searched for and retrieved lexical links by activating semantic networks in their MLs, and this finding applied particularly to the large vocabulary size group. Some pedagogical implications for teaching vocabulary are proposed.

Despite the importance of microbial dysbiosis in human disease, the phenomenon remains poorly understood. We provide the first comprehensive and predictive model of dysbiosis at ecosystem-scale, leveraging our new machine learning method for efficiently inferring compact and interpretable dynamical systems models. Coupling this approach with the most densely temporally sampled interventional study of the microbiome to date, using microbiota from healthy and dysbiotic human donors that we transplanted into mice subjected to antibiotic and dietary interventions, we demonstrate superior predictive performance of our method over state-of-the-art techniques. Moreover, we demonstrate that our approach uncovers intrinsic dynamical properties of dysbiosis driven by destabilizing competitive cycles, in contrast to stabilizing interaction chains in the healthy microbiome, which have implications for restoration of the microbiome to treat disease.

International audience; Leveraging systems biology approaches, we illustrate how metabolically distinct species of Clostridia protect against or worsen Clostridioides difficile infection in mice by modulating the pathogen's colonization, growth, and virulence to impact host survival. Gnotobiotic mice colonized with the amino acid fermenter Paraclostridium bifermentans survive infection with reduced disease severity, while mice colonized with the butyrate-producer, Clostridium sardiniense, succumb more rapidly. Systematic in vivo analyses revealed how each commensal alters the gut-nutrient environment to modulate the pathogen's metabolism, gene regulatory networks, and toxin production. Oral administration of P. bifermentans rescues conventional, clindamycin-treated mice from lethal C. difficile infection in a manner similar to that of monocolonized animals, thereby supporting the therapeutic potential of this commensal species. Our findings lay the foundation for mechanistically informed therapies to counter C. difficile disease using systems biology approaches to define host-commensal-pathogen interactions in vivo.

Animal models are essential to dissect host-microbiota interactions that impact health and the development of disease. In addition to providing pre-clinical models for the development of novel therapeutics and diagnostic biomarkers, mouse systems actively support microbiome studies by defining microbial contributions to normal development and homeostasis, and as well as their role in promoting diseases such as inflammatory auto-immune diseases, diabetes, metabolic syndromes, and susceptibilities to infectious agents. Mice provide a genetically tenable host that can be reared under gnotobiotic (germfree) conditions, allowing colonization studies with human or mouse-origin defined or complex microbial communities to define specific in vivo effects. The protocols and background information detail key aspects to consider in designing host-microbiome experiments with mouse models, and to develop robust systems that leverage gnotobiotic mice, microbial consortia, and specific environmental perturbations to identify causal effects in vivo.

Genome-wide association studies have identified risk loci associated with the development of inflammatory bowel disease, while epidemiological studies have emphasized that pathogenesis likely involves host interactions with environmental elements whose source and structure need to be defined. Here, we identify a class of compounds derived from dietary, microbial, and industrial sources that are characterized by the presence of a five-membered oxazole ring and induce CD1d-dependent intestinal inflammation. We observe that minimal oxazole structures modulate natural killer T cell-dependent inflammation by regulating lipid antigen presentation by CD1d on intestinal epithelial cells (IECs). CD1d-restricted production of interleukin 10 by IECs is limited through activity of the aryl hydrocarbon receptor (AhR) pathway in response to oxazole induction of tryptophan metabolites. As such, the depletion of the AhR in the intestinal epithelium abrogates oxazole-induced inflammation. In summary, we identify environmentally derived oxazoles as triggers of CD1d-dependent intestinal inflammatory responses that occur via activation of the AhR in the intestinal epithelium.