Surfactant status and respiratory outcome in premature infants receiving late surfactant treatment.

BACKGROUND:Many premature infants with respiratory failure are deficient in surfactant, but the relationship to occurrence of bronchopulmonary dysplasia (BPD) is uncertain. METHODS:Tracheal aspirates were collected from 209 treated and control infants enrolled at 7-14 days in the Trial of Late Surfactant. The content of phospholipid, surfactant protein B, and total protein were determined in large aggregate (active) surfactant. RESULTS:At 24 h, surfactant treatment transiently increased surfactant protein B content (70%, p < 0.01), but did not affect recovered airway surfactant or total protein/phospholipid. The level of recovered surfactant during dosing was directly associated with content of surfactant protein B (r = 0.50, p < 0.00001) and inversely related to total protein (r = 0.39, p < 0.0001). For all infants, occurrence of BPD was associated with lower levels of recovered large aggregate surfactant, higher protein content, and lower SP-B levels. Tracheal aspirates with lower amounts of recovered surfactant had an increased proportion of small vesicle (inactive) surfactant. CONCLUSIONS:We conclude that many intubated premature infants are deficient in active surfactant, in part due to increased intra-alveolar metabolism, low SP-B content, and protein inhibition, and that the severity of this deficit is predictive of BPD. Late surfactant treatment at the frequency used did not provide a sustained increase in airway surfactant

Chapter 3: Choosing the Important Outcomes for a Systematic Review of a Medical Test

In this chapter of the Evidence-based Practice Centers Methods Guide for Medical Tests, we describe how the decision to use a medical test generates a broad range of outcomes and that each of these outcomes should be considered for inclusion in a systematic review. Awareness of these varied outcomes affects how a decision maker balances the benefits and risks of the test; therefore, a systematic review should present the evidence on these diverse outcomes. The key outcome categories include clinical management outcomes and direct health effects; emotional, social, cognitive, and behavioral responses to testing; legal and ethical outcomes, and costs. We describe the challenges of incorporating these outcomes in a systematic review, suggest a framework for generating potential outcomes for inclusion, and describe the role of stakeholders in choosing the outcomes for study. Finally, we give examples of systematic reviews that either included a range of outcomes or that might have done so. The following are the key messages in this chapter: Consider both the outcomes that are relevant to the process of testing and those that are relevant to the results of the test.Consider inclusion of outcomes in all five domains: clinical management effects, direct test effects; emotional, social, cognitive and behavioral effects; legal and ethical effects, and costs.Consider to which group the outcomes of testing are most relevant.Given resource limitations, prioritize which outcomes to include. This decision depends on the needs of the stakeholder(s), who should be assisted in prioritizing the outcomes for inclusion

Photon CT Scanning of Advanced Ceramic Materials

Advanced ceramic materials (e. g. Si3N4, ZrO2, SiC, A12O3) are being developed for high temperature applications in advanced heat engines and high temperature heat recovery systems [1]. Although fracture toughness has been a constant problem, advanced ceramics are now being developed with fracture toughnesses close to those of metals [2]. Small size flaws (10–200 μm), small non-uniformities in density distributions (0.1–2%) present as long-range density gradients, and porous regions which can be seen as localized areas of slightly lower density, are critical in most ceramics. The need to detect these small flaws is causing a significant effort to be devoted towards nondestructive evaluation. Detection of “defects” such as those noted in engineering ceramics has presented problems for conventional non-destructive evaluation methods [3]

Chronic Granulomatous Disease; fundamental stages in our understanding of CGD

It has been 50 years since chronic granulomatous disease was first reported as a disease which fatally affected the ability of children to survive infections. Various milestone discoveries from the insufficient ability of patients' leucocytes to destroy microbial particles to the underlying genetic predispositions through which the disease is inherited have had important consequences. Longterm antibiotic prophylaxis has helped to fight infections associated with chronic granulomatous disease while the steady progress in bone marrow transplantation and the prospect of gene therapy are hailed as long awaited permanent treatment options. This review unearths the important findings by scientists that have led to our current understanding of the disease

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

Identification of a cytokine network sustaining neutrophil and Th17 activation in untreated early rheumatoid arthritis

© 2010 Cascão et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Introduction: Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease characterized by sustained synovitis. Recently, several studies have proposed neutrophils and Th17 cells as key players in the onset and perpetuation of this disease. The main goal of this work was to determine whether cytokines driving neutrophil and Th17 activation are dysregulated in very early rheumatoid arthritis patients with less than 6 weeks of disease duration and before treatment (VERA). Methods: Cytokines related to neutrophil and Th17 activation were quantified in the serum of VERA and established RA patients and compared with other very early arthritis (VEA) and healthy controls. Synovial fluid (SF) from RA and osteoarthritis (OA) patients was also analyzed. Results: VERA patients had increased serum levels of cytokines promoting Th17 polarization (IL-1b and IL-6), as well as IL-8 and Th17-derived cytokines (IL-17A and IL-22) known to induce neutrophil-mediated inflammation. In established RA this pattern is more evident within the SF. Early treatment with methotrexate or corticosteroids led to clinical improvement but without an impact on the cytokine pattern. Conclusions: VERA patients already display increased levels of cytokines related with Th17 polarization and neutrophil recruitment and activation, a dysregulation also found in SF of established RA. 0 Thus, our data suggest that a cytokine-milieu favoring Th17 and neutrophil activity is an early event in RA pathogenesis.This work was supported by a grant from Sociedade Portuguesa de Reumatologia/Schering-Plough 2005. RAM and RC were funded by Fundação para a Ciência e a Tecnologia (FCT) SFRH/BD/30247/2006 and SFRH/BD/40513/2007, respectively. MMS-C was funded by Marie Curie Intra-European Fellowship PERG-2008-239422 and a EULAR Young Investigator Award

Effects of a brief mindfulness-based intervention on emotional regulation and levels of mindfulness in senior students

Mindfulness-based interventions have been applied in diverse populations and achieved mental health benefits. This study examined the effects of a brief mindfulness program for emotional regulation and levels of mindfulness on senior students in Brazil. The intervention consisted of six weekly meetings attended by 30 participants. It is a pre-experimental research, with pre- and post-test comparative and correlation measurements. The preliminary results, which relied on parametrical and non-parametrical tests, revealed a reduction in total emotional regulation difficulties (p = 0.0001; r = − 0.55). Also, there was an increase in the levels of mindfulness in the subtests for both dimensions under evaluation: “Awareness” (p = 0.0001; d = 0.77) and “Acceptance” (p = 0.048; d = 0.37). By associating the amount of meditative practices performed by students with the variables, a significant positive correlation was found with the mindfulness dimension “Awareness” (rP = 0.422; p = 0.020), and there was a significant negative correlation with Difficulties in emotion regulation (rS = − 0.478; p = 0.008) and with its respective subscales “Non-acceptance” (rS = − 0.654; p = 0.0001) and “Clarity” (rS = − 0.463; p = 0.010). In conclusion, the application of a brief mindfulness-based intervention is promising in Brazilian university contexts; moreover, it can bring benefits to students, e.g., an increase in emotion regulation as well as in levels of mindfulness. We suggest that further research should use an experimental design and follow-up.info:eu-repo/semantics/publishedVersio

Discovering study-specific gene regulatory networks

This article has been made available through the Brunel Open Access Publishing Fund.Microarrays are commonly used in biology because of their ability to simultaneously measure thousands of genes under different conditions. Due to their structure, typically containing a high amount of variables but far fewer samples, scalable network analysis techniques are often employed. In particular, consensus approaches have been recently used that combine multiple microarray studies in order to find networks that are more robust. The purpose of this paper, however, is to combine multiple microarray studies to automatically identify subnetworks that are distinctive to specific experimental conditions rather than common to them all. To better understand key regulatory mechanisms and how they change under different conditions, we derive unique networks from multiple independent networks built using glasso which goes beyond standard correlations. This involves calculating cluster prediction accuracies to detect the most predictive genes for a specific set of conditions. We differentiate between accuracies calculated using cross-validation within a selected cluster of studies (the intra prediction accuracy) and those calculated on a set of independent studies belonging to different study clusters (inter prediction accuracy). Finally, we compare our method's results to related state-of-the art techniques. We explore how the proposed pipeline performs on both synthetic data and real data (wheat and Fusarium). Our results show that subnetworks can be identified reliably that are specific to subsets of studies and that these networks reflect key mechanisms that are fundamental to the experimental conditions in each of those subsets

The grinch who stole wisdom

Dr. Seuss is wise. How the Grinch Stole Christmas (Seuss, 1957) could serve as a parable for our time. It can also be seen as a roadmap for the development of contemplative wisdom. The abiding popularity of How the Grinch Stole Christmas additionally suggests that contemplative wisdom is more readily available to ordinary people, even children, than is normally thought. This matters because from the point of view of contemplatives in any of the world's philosophies or religions, people are confused about wisdom. The content of the nascent field of wisdom studies, they might say, is largely not wisdom at all but rather what it's like to live in a particular kind of prison cell, a well appointed cell perhaps, but not a place that makes possible either personal satisfaction or deep problem solving. I believe that what the contemplative traditions have to say is important; they offer a different orientation to what personal wisdom is, how to develop it, and how to use it in the world than is presently contained in either our popular culture or our sciences. In order to illustrate this I will examine, in some detail, one contemplative path within Buddhism. Buddhism is particularly useful in this respect because its practices are nontheistic and thus avoid many of the cultural landmines associated with the contemplative aspects of Western religions