Twisted Tensor Products of Kn with Km

We find three families of twisting maps of Km with Kn, where K is a field, and we make a detailed study of its properties. One of them is related to truncated quiver algebras, the second one consists of deformations of the first and the third one requires m = n and yields algebras isomorphic to Mn(K).Fil: Arce, Jack. Pontificia Universidad Católica del Perú. Sección Matemáticas; PerúFil: Guccione, Jorge Alberto. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; ArgentinaFil: Guccione, Juan Jose. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Argentino de Matemática Alberto Calderón; ArgentinaFil: Valqui, Christian. Pontificia Universidad Católica del Perú. Sección Matemáticas; Perú. Instituto de Matemática y Ciencias Afines; Per

Quantitative Proteomics of Intracellular Campylobacter jejuni Reveals Metabolic Reprogramming

Campylobacter jejuni is the major cause of bacterial food-borne illness in the USA and Europe. An important virulence attribute of this bacterial pathogen is its ability to enter and survive within host cells. Here we show through a quantitative proteomic analysis that upon entry into host cells, C. jejuni undergoes a significant metabolic downshift. Furthermore, our results indicate that intracellular C. jejuni reprograms its respiration, favoring the respiration of fumarate. These results explain the poor ability of C. jejuni obtained from infected cells to grow under standard laboratory conditions and provide the bases for the development of novel anti microbial strategies that would target relevant metabolic pathways

Co-morbid depression is associated with poor work outcomes in persons with cardiovascular disease (CVD): A large, nationally representative survey in the Australian population

Background: Co-morbid major depressive disorder (MDD) and cardiovascular disease (CVD) is associated with poor clinical and psychological outcomes. However, the full extent of the burden of, and interaction between, this co-morbidity on important vocational outcomes remains less clear, particularly at the population level. We examine the association of co-morbid MDD with work outcomes in persons with and without CVD.Methods. This study utilised cross-sectional, population-based data from the 2007 Australian National Survey of Mental Health and Wellbeing (n = 8841) to compare work outcomes of individuals with diagnostically-defined MDD and CVD, MDD but not CVD, CVD but not MDD, with a reference group of "healthy" Australians. Workforce participation was defined as being in full- or part-time employment. Work functioning was measured using a WHO Disability Assessment Schedule item. Absenteeism was assessed using the \u27days out of role\u27 item.Results: Of the four groups, those with co-morbid MDD and CVD were least likely to report workforce participation (adj OR:0.4, 95% CI: 0.3-0.6). Those with MDD only (adj OR:0.8, 95% CI:0.7-0.9) and CVD only (adj OR:0.8, 95% CI: 0.6-0.9) also reported significantly reduced odds of participation. Employed individuals with co-morbid MDD and CVD were 8 times as likely to experience impairments in work functioning (adj OR:8.1, 95% CI: 3.8- 17.3) compared with the reference group. MDD was associated with a four-fold increase in impaired functioning. Further, individuals with co-morbid MDD and CVD reported greatest likelihood of workplace absenteeism (adj. OR:3.0, 95% CI: 1.4-6.6). Simultaneous exposure to MDD and CVD conferred an even greater likelihood of poorer work functioning.Conclusions: Co-morbid MDD and CVD is associated with significantly poorer work outcomes. Specifically, the effects of these conditions on work functioning are synergistic. The development of specialised treatment programs for those with co-morbid MDD and CVD is required

c- and N-myc Regulate Neural Precursor Cell Fate, Cell Cycle, and Metabolism to Direct Cerebellar Development

Separate murine knockout (KO) of either c- or N-myc genes in neural stem and precursor cells (NSC) driven by nestin-cre causes microcephaly. The cerebellum is particularly affected in the N-myc KO, leading to a strong reduction in cerebellar granule neural progenitors (CGNP) and mature granule neurons. In humans, mutation of N-myc also causes microcephaly in Feingold Syndrome. We created a double KO (DKO) of c- and N-myc using nestin-cre, which strongly impairs brain growth, particularly that of the cerebellum. Granule neurons were almost absent from the Myc DKO cerebellum, and other cell types were relatively overrepresented, including astroglia, oligodendrocytes, and Purkinje neurons. These findings are indicative of a profound disruption of cell fate of cerebellar stem and precursors. DKO Purkinje neurons were strikingly lacking in normal arborization. Inhibitory neurons were ectopic and exhibited very abnormal GAD67 staining patterns. Also consistent with altered cell fate, the adult DKO cerebellum still retained a residual external germinal layer (EGL). CGNP in the DKO EGL were almost uniformly NeuN and p27KIP1 positive as well as negative for Math1 and BrdU at the peak of normal cerebellar proliferation at P6. The presence of some mitotic CGNP in the absence of S phase cells suggests a possible arrest in M phase. CGNP and NSC metabolism also was affected by loss of Myc as DKO cells exhibited weak nucleolin staining. Together these findings indicate that c- and N-Myc direct cerebellar development by maintaining CGNP and NSC populations through inhibiting differentiation as well as directing rapid cell cycling and active cellular metabolism

Unexpected differential metabolic responses of Campylobacter jejuni to the abundant presence of glutamate and fucose

Introduction: Campylobacter jejuni is the leading cause of foodborne bacterial enteritis in humans, and yet little is known in regard to how genetic diversity and metabolic capabilities among isolates affect their metabolic phenotype and pathogenicity. Objectives: For instance, the C. jejuni 11168 strain can utilize both l-fucose and l-glutamate as a carbon source, which provides the strain with a competitive advantage in some environments and in this study we set out to assess the metabolic response of C. jejuni 11168 to the presence of l-fucose and l-glutamate in the growth medium. Methods: To achieve this, untargeted hydrophilic liquid chromatography coupled to mass spectrometry was used to obtain metabolite profiles of supernatant extracts obtained at three different time points up to 24 h. Results: This study identified both the depletion and the production and subsequent release of a multitude of expected and unexpected metabolites during the growth of C. jejuni 11168 under three different conditions. A large set of standards allowed identification of a number of metabolites. Further mass spectrometry fragmentation analysis allowed the additional annotation of substrate-specific metabolites. The results show that C. jejuni 11168 upon l-fucose addition indeed produces degradation products of the fucose pathway. Furthermore, methionine was faster depleted from the medium, consistent with previously-observed methionine auxotrophy. Conclusions: Moreover, a multitude of not previously annotated metabolites in C. jejuni were found to be increased specifically upon l-fucose addition. These metabolites may well play a role in the pathogenicity of this C. jejuni strain.</p

The use of the Nursing Activities Score in clinical settings: an integrative review

ABSTRACT Objective analyze how studies have approached the results obtained from the application of the Nursing Activities Score (NAS) based on Donabedian’s model of healthcare organization and delivery. Method CINAHL and PubMed databases were searched for papers published between 2003 and March 2015. Results 36 articles that met the inclusion criteria were reviewed and double-coded by three independent coders and analyzed based on the three elements of Donabedian’s health care quality framework: structure, process and outcome. The most frequently addressed, but not always tested, variables were those that fell into the structure category. Conclusion variables that fell into the process category were used less frequently. Beside NAS, the most frequently used variables in the outcome category were mortality and length of stay. However, no study used a quality framework for healthcare or NAS to evaluate costs, and it is recommended that further research should explore this approach

Substitutions in the Amino-Terminal Tail of Neurospora Histone H3 Have Varied Effects on DNA Methylation

Eukaryotic genomes are partitioned into active and inactive domains called euchromatin and heterochromatin, respectively. In Neurospora crassa, heterochromatin formation requires methylation of histone H3 at lysine 9 (H3K9) by the SET domain protein DIM-5. Heterochromatin protein 1 (HP1) reads this mark and directly recruits the DNA methyltransferase, DIM-2. An ectopic H3 gene carrying a substitution at K9 (hH3K9L or hH3K9R) causes global loss of DNA methylation in the presence of wild-type hH3 (hH3WT). We investigated whether other residues in the N-terminal tail of H3 are important for methylation of DNA and of H3K9. Mutations in the N-terminal tail of H3 were generated and tested for effects in vitro and in vivo, in the presence or absence of the wild-type allele. Substitutions at K4, K9, T11, G12, G13, K14, K27, S28, and K36 were lethal in the absence of a wild-type allele. In contrast, mutants bearing substitutions of R2, A7, R8, S10, A15, P16, R17, K18, and K23 were viable. The effect of substitutions on DNA methylation were variable; some were recessive and others caused a semi-dominant loss of DNA methylation. Substitutions of R2, A7, R8, S10, T11, G12, G13, K14, and P16 caused partial or complete loss of DNA methylation in vivo. Only residues R8-G12 were required for DIM-5 activity in vitro. DIM-5 activity was inhibited by dimethylation of H3K4 and by phosphorylation of H3S10, but not by acetylation of H3K14. We conclude that the H3 tail acts as an integrating platform for signals that influence DNA methylation, in part through methylation of H3K9

Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements

Background: Recent assays for individual-specific genome-wide DNA methylation profiles have enabled epigenome-wide association studies to identify specific CpG sites associated with a phenotype. Computational prediction of CpG site-specific methylation levels is important, but current approaches tackle average methylation within a genomic locus and are often limited to specific genomic regions. Results: We characterize genome-wide DNA methylation patterns, and show that correlation among CpG sites decays rapidly, making predictions solely based on neighboring sites challenging. We built a random forest classifier to predict CpG site methylation levels using as features neighboring CpG site methylation levels and genomic distance, and co-localization with coding regions, CGIs, and regulatory elements from the ENCODE project, among others. Our approach achieves 91% -- 94% prediction accuracy of genome-wide methylation levels at single CpG site precision. The accuracy increases to 98% when restricted to CpG sites within CGIs. Our classifier outperforms state-of-the-art methylation classifiers and identifies features that contribute to prediction accuracy: neighboring CpG site methylation status, CpG island status, co-localized DNase I hypersensitive sites, and specific transcription factor binding sites were found to be most predictive of methylation levels. Conclusions: Our observations of DNA methylation patterns led us to develop a classifier to predict site-specific methylation levels that achieves the best DNA methylation predictive accuracy to date. Furthermore, our method identified genomic features that interact with DNA methylation, elucidating mechanisms involved in DNA methylation modification and regulation, and linking different epigenetic processes