A gut feeling of the PXR, PPAR and NF-kappaB connection.

Bowel diseases reveal the complex interplay of sensing and signalling pathways in maintaining healthy homeostasis of the intestine. Recent studies of the xenobiotic nuclear receptor, pregnane X receptor and the inflammatory mediator nuclear transcription factor kappaB (NF-kappaB) reveal a functional link between xenobiotic neutralization and inflammation and explain how certain xenobiotics can affect the immune response. Furthermore, another nuclear receptor, peroxisome proliferator-activated receptor gamma (PPAR gamma) has been shown to produce beneficial effects in experimental inflammatory bowel diseases by repression of NF-kappaB thereby reducing inflammation, whilst its close relative PPAR beta/delta appears at a central position in signalling pathways involved in the progression of colon cancer. Recently accumulated knowledge on the action of these nuclear receptors and NF-kappaB in intestinal homeostasis may provide the rationale for the development of innovative treatment strategies with selective receptor modulators.

Gut microbiota in children with type 1 diabetes differs from that in healthy children: a case-control study.

BACKGROUND A recent study using a rat model found significant differences at the time of diabetes onset in the bacterial communities responsible for type 1 diabetes modulation. We hypothesized that type 1 diabetes in humans could also be linked to a specific gut microbiota. Our aim was to quantify and evaluate the difference in the composition of gut microbiota between children with type 1 diabetes and healthy children and to determine the possible relationship of the gut microbiota of children with type 1 diabetes with the glycemic level. METHODS A case-control study was carried out with 16 children with type 1 diabetes and 16 healthy children. The fecal bacteria composition was investigated by polymerase chain reaction-denaturing gradient gel electrophoresis and real-time quantitative polymerase chain reaction. RESULTS The mean similarity index was 47.39% for the healthy children and 37.56% for the children with diabetes, whereas the intergroup similarity index was 26.69%. In the children with diabetes, the bacterial number of Actinobacteria and Firmicutes, and the Firmicutes to Bacteroidetes ratio were all significantly decreased, with the quantity of Bacteroidetes significantly increased with respect to healthy children. At the genus level, we found a significant increase in the number of Clostridium, Bacteroides and Veillonella and a significant decrease in the number of Lactobacillus, Bifidobacterium, Blautia coccoides/Eubacterium rectale group and Prevotella in the children with diabetes. We also found that the number of Bifidobacterium and Lactobacillus, and the Firmicutes to Bacteroidetes ratio correlated negatively and significantly with the plasma glucose level while the quantity of Clostridium correlated positively and significantly with the plasma glucose level in the diabetes group. CONCLUSIONS This is the first study showing that type 1 diabetes is associated with compositional changes in gut microbiota. The significant differences in the number of Bifidobacterium, Lactobacillus and Clostridium and in the Firmicutes to Bacteroidetes ratio observed between the two groups could be related to the glycemic level in the group with diabetes. Moreover, the quantity of bacteria essential to maintain gut integrity was significantly lower in the children with diabetes than the healthy children. These findings could be useful for developing strategies to control the development of type 1 diabetes by modifying the gut microbiota.

Gut Microbiota Composition in Male Rat Models under Different Nutritional Status and Physical Activity and Its Association with Serum Leptin and Ghrelin Levels.

BACKGROUND Several evidences indicate that gut microbiota is involved in the control of host energy metabolism. OBJECTIVE To evaluate the differences in the composition of gut microbiota in rat models under different nutritional status and physical activity and to identify their associations with serum leptin and ghrelin levels. METHODS IN A CASE CONTROL STUDY, FORTY MALE RATS WERE RANDOMLY ASSIGNED TO ONE OF THESE FOUR EXPERIMENTAL GROUPS: ABA group with food restriction and free access to exercise; control ABA group with food restriction and no access to exercise; exercise group with free access to exercise and feed ad libitum and ad libitum group without access to exercise and feed ad libitum. The fecal bacteria composition was investigated by PCR-denaturing gradient gel electrophoresis and real-time qPCR. RESULTS In restricted eaters, we have found a significant increase in the number of Proteobacteria, Bacteroides, Clostridium, Enterococcus, Prevotella and M. smithii and a significant decrease in the quantities of Actinobacteria, Firmicutes, Bacteroidetes, B. coccoides-E. rectale group, Lactobacillus and Bifidobacterium with respect to unrestricted eaters. Moreover, a significant increase in the number of Lactobacillus, Bifidobacterium and B. coccoides-E. rectale group was observed in exercise group with respect to the rest of groups. We also found a significant positive correlation between the quantity of Bifidobacterium and Lactobacillus and serum leptin levels, and a significant and negative correlation among the number of Clostridium, Bacteroides and Prevotella and serum leptin levels in all experimental groups. Furthermore, serum ghrelin levels were negatively correlated with the quantity of Bifidobacterium, Lactobacillus and B. coccoides-Eubacterium rectale group and positively correlated with the number of Bacteroides and Prevotella. CONCLUSIONS Nutritional status and physical activity alter gut microbiota composition affecting the diversity and similarity. This study highlights the associations between gut microbiota and appetite-regulating hormones that may be important in terms of satiety and host metabolism.

Impact of the gut microbiota on the development of obesity and type 2 diabetes mellitus.

Obesity and its associated disorders are a major public health concern. Although obesity has been mainly related with perturbations of the balance between food intake and energy expenditure, other factors must nevertheless be considered. Recent insight suggests that an altered composition and diversity of gut microbiota could play an important role in the development of metabolic disorders. This review discusses research aimed at understanding the role of gut microbiota in the pathogenesis of obesity and type 2 diabetes mellitus (TDM2). The establishment of gut microbiota is dependent on the type of birth. With effect from this point, gut microbiota remain quite stable, although changes take place between birth and adulthood due to external influences, such as diet, disease and environment. Understand these changes is important to predict diseases and develop therapies. A new theory suggests that gut microbiota contribute to the regulation of energy homeostasis, provoking the development of an impairment in energy homeostasis and causing metabolic diseases, such as insulin resistance or TDM2. The metabolic endotoxemia, modifications in the secretion of incretins and butyrate production might explain the influence of the microbiota in these diseases.

Metabolomic insights into the intricate gut microbial-host interaction in the development of obesity and type 2 diabetes.

Gut microbiota has recently been proposed as a crucial environmental factor in the development of metabolic diseases such as obesity and type 2 diabetes, mainly due to its contribution in the modulation of several processes including host energy metabolism, gut epithelial permeability, gut peptide hormone secretion, and host inflammatory state. Since the symbiotic interaction between the gut microbiota and the host is essentially reflected in specific metabolic signatures, much expectation is placed on the application of metabolomic approaches to unveil the key mechanisms linking the gut microbiota composition and activity with disease development. The present review aims to summarize the gut microbial-host co-metabolites identified so far by targeted and untargeted metabolomic studies in humans, in association with impaired glucose homeostasis and/or obesity. An alteration of the co-metabolism of bile acids, branched fatty acids, choline, vitamins (i.e., niacin), purines, and phenolic compounds has been associated so far with the obese or diabese phenotype, in respect to healthy controls. Furthermore, anti-diabetic treatments such as metformin and sulfonylurea have been observed to modulate the gut microbiota or at least their metabolic profiles, thereby potentially affecting insulin resistance through indirect mechanisms still unknown. Despite the scarcity of the metabolomic studies currently available on the microbial-host crosstalk, the data-driven results largely confirmed findings independently obtained from in vitro and animal model studies, putting forward the mechanisms underlying the implication of a dysfunctional gut microbiota in the development of metabolic disorders.

Recognition of gut microbiota by NOD2 is essential for the homeostasis of intestinal intraepithelial lymphocytes.

NOD2 functions as an intracellular sensor for microbial pathogen and plays an important role in epithelial defense. The loss-of-function mutation of NOD2 is strongly associated with human Crohn's disease (CD). However, the mechanisms of how NOD2 maintains the intestinal homeostasis and regulates the susceptibility of CD are still unclear. Here we found that the numbers of intestinal intraepithelial lymphocytes (IELs) were reduced significantly in Nod2(-/-) mice and the residual IELs displayed reduced proliferation and increased apoptosis. Further study showed that NOD2 signaling maintained IELs via recognition of gut microbiota and IL-15 production. Notably, recovery of IELs by adoptive transfer could reduce the susceptibility of Nod2(-/-) mice to the 2,4,6-trinitrobenzene sulfonic acid (TNBS)-induced colitis. Our results demonstrate that recognition of gut microbiota by NOD2 is important to maintain the homeostasis of IELs and provide a clue that may link NOD2 variation to the impaired innate immunity and higher susceptibility in CD.

Assessment and reuse of contents in the competence-based educational platform InterMediActor

This paper describes a failure alert system and a methodology for content reuse in a new instructional design system called InterMediActor (IMA). IMA provides an environment for instructional content design, production and reuse, and for students’ evaluation based in content specification through a hierarchical structure of competences. The student assessment process and information extraction process for content reuse are explained.

Hierachy-based methodology for producing educational contents with maximal reutilization

Computer based training or distance education are facing dramatic changes withthe advent of standardization efforts, some of them concentrating in maximal reuse.This is of paramount importance for a sustainable -cost affordable- production ofeducational materials. Reuse in itself should not be a goal, though, since manymethodological aspects might be lost. In this paper we propose two contentproduction approaches for the InterMediActor platform under a competence-basedmethodology: either a bottom-up approach where content is designed from scratchor a top-down methodology where existing material can be gradually adapted tofulfil requisites to be used with maximal flexibility into InterMediActor.

Gut symbionts from distinct hosts exhibit genotoxic activity via divergent colibactin biosynthetic pathways.

Secondary metabolites produced by nonribosomal peptide synthetase (NRPS) or polyketide synthase (PKS) pathways are chemical mediators of microbial interactions in diverse environments. However, little is known about their distribution, evolution, and functional roles in bacterial symbionts associated with animals. A prominent example is "colibactin", a largely unknown family of secondary metabolites produced by Escherichia coli via a hybrid NRPS-PKS biosynthetic pathway, inflicting DNA damage upon eukaryotic cells and contributing to colorectal cancer and tumor formation in the mammalian gut. Thus far, homologs of this pathway have only been found in closely related Enterobacteriaceae, while a divergent variant of this gene cluster was recently discovered in a marine alphaproteobacterial Pseudovibrio strain. Herein, we sequenced the genome of Frischella perrara PEB0191, a bacterial gut symbiont of honey bees, and identified a homologous colibactin biosynthetic pathway related to those found in Enterobacteriaceae. We show that the colibactin genomic island (GI) has conserved gene synteny and biosynthetic module architecture across F. perrara, Enterobacteriaceae and the Pseudovibrio strain. Comparative metabolomics analyses of F. perrara and E. coli further reveal that these two bacteria produce related colibactin pathway-dependent metabolites. Finally, we demonstrate that F. perrara, like E. coli, causes DNA damage in eukaryotic cells in vitro in a colibactin pathway-dependent manner. Together, these results support that divergent variants of the colibactin biosynthetic pathway are widely distributed among bacterial symbionts, producing related secondary metabolites and likely endowing its producer with functional capabilities important for diverse symbiotic associations.

The male of Mischocyttarus nomurae Richards, with a re-examination of the limits and contents of the M. cerberus species group (Hymenoptera, Vespidae, Polistinae, Mischocyttarini)

The male of Mischocyttarus nomurae Richards, 1978 is described for the first time, and relationships between this and other similar species are discussed in a context of redefining the limits of the M. cerberus species group.

Making Predictions with Textual Contents

Forecasting real-world quantities with basis on information from textual descriptions has recently attracted significant interest as a research problem, although previous studies have focused on applications involving only the English language. This document presents an experimental study on the subject of making predictions with textual contents written in Portuguese, using documents from three distinct domains. I specifically report on experiments using different types of regression models, using state-of-the-art feature weighting schemes, and using features derived from cluster-based word representations. Through controlled experiments, I have shown that prediction models using the textual information achieve better results than simple baselines such as taking the average value over the training data, and that richer document representations (i.e., using Brown clusters and the Delta- TF-IDF feature weighting scheme) result in slight performance improvements.