Intravenous sodium nitrite in acute ST-elevation myocardial infarction: a randomized controlled trial (NIAMI).

AIM: Despite prompt revascularization of acute myocardial infarction (AMI), substantial myocardial injury may occur, in part a consequence of ischaemia reperfusion injury (IRI). There has been considerable interest in therapies that may reduce IRI. In experimental models of AMI, sodium nitrite substantially reduces IRI. In this double-blind randomized placebo controlled parallel-group trial, we investigated the effects of sodium nitrite administered immediately prior to reperfusion in patients with acute ST-elevation myocardial infarction (STEMI). METHODS AND RESULTS: A total of 229 patients presenting with acute STEMI were randomized to receive either an i.v. infusion of 70 μmol sodium nitrite (n = 118) or matching placebo (n = 111) over 5 min immediately before primary percutaneous intervention (PPCI). Patients underwent cardiac magnetic resonance imaging (CMR) at 6-8 days and at 6 months and serial blood sampling was performed over 72 h for the measurement of plasma creatine kinase (CK) and Troponin I. Myocardial infarct size (extent of late gadolinium enhancement at 6-8 days by CMR-the primary endpoint) did not differ between nitrite and placebo groups after adjustment for area at risk, diabetes status, and centre (effect size -0.7% 95% CI: -2.2%, +0.7%; P = 0.34). There were no significant differences in any of the secondary endpoints, including plasma troponin I and CK area under the curve, left ventricular volumes (LV), and ejection fraction (EF) measured at 6-8 days and at 6 months and final infarct size (FIS) measured at 6 months. CONCLUSIONS: Sodium nitrite administered intravenously immediately prior to reperfusion in patients with acute STEMI does not reduce infarct size

Innate Recognition of Fungal Cell Walls

The emergence of fungal infections as major causes of morbidity and mortality in immunosuppressed individuals has prompted studies into how the host recognizes fungal pathogens. Fungi are eukaryotes and as such share many similarities with mammalian cells. The most striking difference, though, is the presence of a cell wall that serves to protect the fungus from environmental stresses, particularly osmotic changes [1]. This task is made challenging because the fungus must remodel itself to allow for cell growth and division, including the conversion to different morphotypes, such as occurs during germination of spherical spores into filamentous hyphae. The cell wall also connects the fungus with its environment by triggering intracellular signaling pathways and mediating adhesion to other cells and extracellular matrices. Here, important facts and concepts critical for understanding innate sensing of the fungal cell wall by mammalian pathogens are reviewed

Innate Immune Sensing of DNA

Discusses efforts to understand how DNA triggers immune responses

Omnichannel Value Chain: Mapping Digital Technologies for Channel Integration Activities

In order to provide a seamless customer experience, researchers and practitioners have proposed creation of an omnichannel retailing environment by integrating online and offline channels. Channel integration necessitates use of digital technologies and there are myriads of technological solutions available. However, retailers are struggling with selection and implementation of suitable technologies to add value through channel integration. Despite the strong practical need, this issue has not been effectively addressed in the academic literature. This paper presents an omnichannel value chain underpinned by Porter’s value chain model. We identify ten channel integration activities for value creation by carrying out a synthesis of current research on omnichannel retailing. Enabling digital technologies are then mapped to these activities using technology implementation examples and provide a guideline for retailers to select appropriate technologies for the identified value creation activities

Constructing Biological Pathways by a Two-Step Counting Approach

Networks are widely used in biology to represent the relationships between genes and gene functions. In Boolean biological models, it is mainly assumed that there are two states to represent a gene: on-state and off-state. It is typically assumed that the relationship between two genes can be characterized by two kinds of pairwise relationships: similarity and prerequisite. Many approaches have been proposed in the literature to reconstruct biological relationships. In this article, we propose a two-step method to reconstruct the biological pathway when the binary array data have measurement error. For a pair of genes in a sample, the first step of this approach is to assign counting numbers for every relationship and select the relationship with counting number greater than a threshold. The second step is to calculate the asymptotic p-values for hypotheses of possible relationships and select relationships with a large p-value. This new method has the advantages of easy calculation for the counting numbers and simple closed forms for the p-value. The simulation study and real data example show that the two-step counting method can accurately reconstruct the biological pathway and outperform the existing methods. Compared with the other existing methods, this two-step method can provide a more accurate and efficient alternative approach for reconstructing the biological network