Dark Sector from Interacting Canonical and Non-Canonical Scalar Fields

In this work it is investigated general models with interactions between two canonical scalar fields and between one non-canonical (tachyon-type) and one canonical scalar field. The potentials and couplings to the gravity are selected through the Noether symmetry approach. These general models are employed to describe interactions between dark energy and dark matter, with the fields being constrained by the astronomical data. The cosmological solutions of some cases are compared with the observed evolution of the late Universe.Comment: 20 pages, 13 figures, correction of misprints in eqs. (4), (5), (43), (44

Hierarchical structures in the Large and Small Magellanic Clouds

We investigate the degree of spatial correlation among extended structures in the LMC and SMC. To this purpose we work with sub-samples characterised by different properties such as age and size, taken from the updated catalogue of Bica et al. or gathered in the present work. The structures are classified as star clusters or non-clusters (basically, nebular complexes and their stellar associations). The radius distribution functions follow power-laws ($dN/dR\propto R^{-\alpha}$) with slopes and maximum radius ($R_{max}$) that depend on object class (and age). Non-clusters are characterised by $\alpha\approx1.9$ and R_{max}\la472 pc, while young clusters (age \la10 Myr) have $\alpha\approx3.6$ and R_{max}\la15 pc, and old ones (age \ga600 Myr) have $\alpha\approx2.5$ and R_{max}\la40 pc. Young clusters present a high degree of spatial self-correlation and, especially, correlate with star-forming structures, which does not occur with the old ones. This is consistent with the old clusters having been heavily mixed up, since their ages correspond to several LMC and SMC crossing times. On the other hand, with ages corresponding to fractions of the respective crossing times, the young clusters still trace most of their birthplace structural pattern. Also, small clusters ($R<10$ pc), as well as small non-clusters ($R<100$ pc), are spatially self-correlated, while their large counterparts of both classes are not. The above results are consistent with a hierarchical star-formation scenario for the LMC and SMC.Comment: Accepted by MNRA

Growth characteristics in individuals with osteogenesis imperfecta in North America: results from a multicenter study.

PurposeOsteogenesis imperfecta (OI) predisposes people to recurrent fractures, bone deformities, and short stature. There is a lack of large-scale systematic studies that have investigated growth parameters in OI.MethodsUsing data from the Linked Clinical Research Centers, we compared height, growth velocity, weight, and body mass index (BMI) in 552 individuals with OI. Height, weight, and BMI were plotted on Centers for Disease Control and Prevention normative curves.ResultsIn children, the median z-scores for height in OI types I, III, and IV were -0.66, -6.91, and -2.79, respectively. Growth velocity was diminished in OI types III and IV. The median z-score for weight in children with OI type III was -4.55. The median z-scores for BMI in children with OI types I, III, and IV were 0.10, 0.91, and 0.67, respectively. Generalized linear model analyses demonstrated that the height z-score was positively correlated with the severity of the OI subtype (P &lt; 0.001), age, bisphosphonate use, and rodding (P &lt; 0.05).ConclusionFrom the largest cohort of individuals with OI, we provide median values for height, weight, and BMI z-scores that can aid the evaluation of overall growth in the clinic setting. This study is an important first step in the generation of OI-specific growth curves

Health service utilization in IBD: comparison of self-report and administrative data

<p>Abstract</p> <p>Background</p> <p>The reliability of self-report regarding health care utilization in inflammatory bowel disease (IBD) is unknown. If proven reliable, it could help justify self-report as a means of determining health care utilization and associated costs.</p> <p>Methods</p> <p>The Manitoba IBD Cohort Study is a population-based longitudinal study of participants diagnosed within 7 years of enrollment. Health care utilization was assessed through standardized interview. Participants (n = 352) reported the total number of nights hospitalized, frequency of physician contacts in the prior 12 months and whether the medical contacts were for IBD-related reasons or not. Reports of recent antibiotic use were also recorded. Actual utilization was drawn from the administrative database of Manitoba Health, the single comprehensive provincial health insurer.</p> <p>Results</p> <p>According to the administrative data, 15% of respondents had an overnight hospitalization, while 10% had an IBD-related hospitalization. Self-report concordance was highly sensitive (92%; 82%) and specific (96%; 97%, respectively). 97% of participants had contact with a physician in the previous year, and 69% had IBD-related visits. Physician visits were significantly under-reported and there was a trend to over-report the number of nights in hospital.</p> <p>Conclusions</p> <p>Self-report data can be helpful in evaluating health service utilization, provided that the researcher is aware of the systematic sources of bias. Outpatient visits are well identified by self-report. The discordance for the type of outpatient visit may be either a weakness of self-report or a flaw in diagnosis coding of the administrative data. If administrative data are not available, self-report information may be a cost-effective alternative, particularly for hospitalizations.</p

Charged-Particle Thermonuclear Reaction Rates: III. Nuclear Physics Input

The nuclear physics input used to compute the Monte Carlo reaction rates and probability density functions that are tabulated in the second paper of this series (Paper II) is presented. Specifically, we publish the input files to the Monte Carlo reaction rate code RatesMC, which is based on the formalism presented in the first paper of this series (Paper I). This data base contains overwhelmingly experimental nuclear physics information. The survey of literature for this review was concluded in November 2009.Comment: 132 page

Nasal Acai Polysaccharides Potentiate Innate Immunity to Protect against Pulmonary Francisella tularensis and Burkholderia pseudomallei Infections

Pulmonary Francisella tularensis and Burkholderia pseudomallei infections are highly lethal in untreated patients, and current antibiotic regimens are not always effective. Activating the innate immune system provides an alternative means of treating infection and can also complement antibiotic therapies. Several natural agonists were screened for their ability to enhance host resistance to infection, and polysaccharides derived from the Acai berry (Acai PS) were found to have potent abilities as an immunotherapeutic to treat F. tularensis and B. pseudomallei infections. In vitro, Acai PS impaired replication of Francisella in primary human macrophages co-cultured with autologous NK cells via augmentation of NK cell IFN-γ. Furthermore, Acai PS administered nasally before or after infection protected mice against type A F. tularensis aerosol challenge with survival rates up to 80%, and protection was still observed, albeit reduced, when mice were treated two days post-infection. Nasal Acai PS administration augmented intracellular expression of IFN-γ by NK cells in the lungs of F. tularensis-infected mice, and neutralization of IFN-γ ablated the protective effect of Acai PS. Likewise, nasal Acai PS treatment conferred protection against pulmonary infection with B. pseudomallei strain 1026b. Acai PS dramatically reduced the replication of B. pseudomallei in the lung and blocked bacterial dissemination to the spleen and liver. Nasal administration of Acai PS enhanced IFN-γ responses by NK and γδ T cells in the lungs, while neutralization of IFN-γ totally abrogated the protective effect of Acai PS against pulmonary B. pseudomallei infection. Collectively, these results demonstrate Acai PS is a potent innate immune agonist that can resolve F. tularensis and B. pseudomallei infections, suggesting this innate immune agonist has broad-spectrum activity against virulent intracellular pathogens

Co-designing inflammatory bowel disease (Ibd) services in Scotland : findings from a nationwide survey

Background: The Scottish Government’s ambition is to ensure that health services are co-designed with the communities they serve. Crohn’s and Colitis UK and the Scottish Government acknowledged the need to review and update the current IBD care model. An online survey was conducted asking IBD patients about their experiences of the NHS care they receive. This survey was the first step of co-designing and developing a national strategy for IBD service improvement in Scotland. Aim: To explore IBD patients’ experiences of current services and make recommendations for future service development. Methods: This study was part of a wider cross-sectional on-line survey. Participants were patients with IBD across Scotland. 777 people with IBD took part in the survey. Thematic analysis of all data was conducted independently by two researchers. Results: Three key themes emerged: Quality of life: Participants highlighted the impact the disease has on quality of life and the desperate need for IBD services to address this more holistically. IBD clinicians and access: Participants recognised the need for more IBD nurses and gastroenterologists along with better access to them. Those with a named IBD nurse reported to be more satisfied with their care. An explicit IBD care pathway: Patients with IBD identified the need of making the IBD care pathway more explicit to service users. Conclusions: Participants expressed the need for a more holistic approach to their IBD care. This includes integrating psychological, counselling and dietetic services into IBD care with better access to IBD clinicians and a more explicit IBD care pathway. Keywords: Inflammatory bowel disease, Co-designing, Qualitative study, Patient survey, Crohn’s disease, Ulcerative coliti

Can we accurately classify schizophrenia patients from healthy controls using magnetic resonance imaging and machine learning?:A multi-method and multi-dataset study

Machine learning is a powerful tool that has previously been used to classify schizophrenia (SZ) patients from healthy controls (HC) using magnetic resonance images. Each study, however, uses different datasets, classification algorithms, and validation techniques. Here, we perform a critical appraisal of the accuracy of machine learning methodologies used in SZ/HC classifications studies by comparing three machine learning algorithms (logistic regression [LR], support vector machines [SVMs], and linear discriminant analysis [LDA]) on three independent datasets (435 subjects total) using two tissue density estimates and cortical thickness (CT). Performance is assessed using 10-fold cross-validation, as well as a held-out validation set. Classification using CT outperformed tissue densities, but there was no clear effect of dataset. LR, SVMs, and LDA each yielded the highest accuracies for a different feature set and validation paradigm, but most accuracies were between 55 and 70%, well below previously reported values. The highest accuracy achieved was 73.5% using CT data and an SVM. Taken together, these results illustrate some of the obstacles to constructing effective disease classifiers, and suggest that tissue densities and CT may not be sufficiently sensitive for SZ/HC classification given current available methodologies and sample sizes