Local host response following an intramammary challenge with Staphylococcus fleurettii and different strains of Staphylococcus chromogenes in dairy heifers

Coagulase-negative staphylococci (CNS) are a common cause of subclinical mastitis in dairy cattle. The CNS inhabit various ecological habitats, ranging between the environment and the host. In order to obtain a better insight into the host response, an experimental infection was carried out in eight healthy heifers in mid-lactation with three different CNS strains: a Staphylococcus fleurettii strain originating from sawdust bedding, an intramammary Staphylococcus chromogenes strain originating from a persistent intramammary infection (S. chromogenes IM) and a S. chromogenes strain isolated from a heifer's teat apex (S. chromogenes TA). Each heifer was inoculated in the mammary gland with 1.0 x 10(6) colony forming units of each bacterial strain (one strain per udder quarter), whereas the remaining quarter was infused with phosphate-buffered saline. Overall, the CNS evoked a mild local host response. The somatic cell count increased in all S. fleurettii-inoculated quarters, although the strain was eliminated within 12 h. The two S. chromogenes strains were shed in larger numbers for a longer period. Bacterial and somatic cell counts, as well as neutrophil responses, were higher after inoculation with S. chromogenes IM than with S. chromogenes TA. In conclusion, these results suggest that S. chromogenes might be better adapted to the mammary gland than S. fleurettii. Furthermore, not all S. chromogenes strains induce the same local host response

Agents intervening against delirium in the intensive care unit trial-Protocol for a secondary Bayesian analysis

Background Delirium is highly prevalent in the intensive care unit (ICU) and is associated with high morbidity and mortality. The antipsychotic haloperidol is the most frequently used agent to treat delirium although this is not supported by solid evidence. The agents intervening against delirium in the intensive care unit (AID-ICU) trial investigates the effects of haloperidol versus placebo for the treatment of delirium in adult ICU patients. Methods This protocol describes the secondary, pre-planned Bayesian analyses of the primary and secondary outcomes up to day 90 of the AID-ICU trial. We will use Bayesian linear regression models for all count outcomes and Bayesian logistic regression models for all dichotomous outcomes. We will adjust for stratification variables (site and delirium subtype) and use weakly informative priors supplemented with sensitivity analyses using sceptical priors. We will present results as absolute differences (mean differences and risk differences) and relative differences (ratios of means and relative risks). Posteriors will be summarised using median values as point estimates and percentile-based 95% credibility intervals. Probabilities of any benefit/harm, clinically important benefit/harm and clinically unimportant differences will be presented for all outcomes. Discussion The results of this secondary, pre-planned Bayesian analysis will complement the primary frequentist analysis of the AID-ICU trial and facilitate a nuanced and probabilistic interpretation of the trial results.Peer reviewe

A pig model of acute Staphylococcus aureus induced pyemia

<p>Abstract</p> <p>Background</p> <p>Sepsis caused by <it>Staphylococcus aureus </it>constitutes an important cause of morbidity and mortality in humans, and the incidence of this disease-entity is increasing. In this paper we describe the initial microbial dynamics and lesions in pigs experimentally infected with <it>S. aureus</it>, with the aim of mimicking human sepsis and pyemia.</p> <p>Methods</p> <p>The study was conducted in anaesthetized and intravenously inoculated pigs, and was based on bacteriological examination of blood and testing of blood for IL-6 and C-reactive protein. Following killing of the animals and necropsy bacteriological and histological examinations of different organs were performed 4, 5 or 6 h after inoculation.</p> <p>Results</p> <p>Clearance of bacteria from the blood was completed within the first 2 h in some of the pigs and the highest bacterial load was recorded in the lungs as compared to the spleen, liver and bones. This probably was a consequence of both the intravenous route of inoculation and the presence of pulmonary intravascular macrophages. Inoculation of bacteria induced formation of acute microabscesses in the lungs, spleen and liver, but not in the kidneys or bones. No generalized inflammatory response was recorded, i.e. IL-6 was not detected in the blood and C-reactive protein did not increase, probably because of the short time course of the study.</p> <p>Conclusion</p> <p>This study demonstrates the successful induction of acute pyemia (microabscesses), and forms a basis for future experiments that should include inoculation with strains of <it>S. aureus </it>isolated from man and an extension of the timeframe aiming at inducing sepsis, severe sepsis and septic shock.</p

ZAK beta is activated by cellular compression and mediates contraction-induced MAP kinase signaling in skeletal muscle

Mechanical inputs give rise to p38 and JNK activation, which mediate adaptive physiological responses in various tissues. In skeletal muscle, contraction-induced p38 and JNK signaling ensure adaptation to exercise, muscle repair, and hypertrophy. However, the mechanisms by which muscle fibers sense mechanical load to activate this signaling have remained elusive. Here, we show that the upstream MAP3K ZAK beta is activated by cellular compression induced by osmotic shock and cyclic compression in vitro, and muscle contraction in vivo. This function relies on ZAKO's ability to recognize stress fibers in cells and Z-discs in muscle fibers when mechanically perturbed. Consequently, ZAK-deficient mice present with skeletal muscle defects characterized by fibers with centralized nuclei and progressive adaptation towards a slower myosin profile. Our results highlight how cells in general respond to mechanical compressive load and how mechanical forces generated during muscle contraction are translated into MAP kinase signaling.Peer reviewe

The Index-Based Subgraph Matching Algorithm (ISMA): Fast Subgraph Enumeration in Large Networks Using Optimized Search Trees

Subgraph matching algorithms are designed to find all instances of predefined subgraphs in a large graph or network and play an important role in the discovery and analysis of so-called network motifs, subgraph patterns which occur more often than expected by chance. We present the index-based subgraph matching algorithm (ISMA), a novel tree-based algorithm. ISMA realizes a speedup compared to existing algorithms by carefully selecting the order in which the nodes of a query subgraph are investigated. In order to achieve this, we developed a number of data structures and maximally exploited symmetry characteristics of the subgraph. We compared ISMA to a naive recursive tree-based algorithm and to a number of well-known subgraph matching algorithms. Our algorithm outperforms the other algorithms, especially on large networks and with large query subgraphs. An implementation of ISMA in Java is freely available at http://sourceforge.net/projects/isma

The Index-Based Subgraph Matching Algorithm with General Symmetries (ISMAGS):Exploiting Symmetry for Faster Subgraph Enumeration

Subgraph matching algorithms are used to find and enumerate specific interconnection structures in networks. By enumerating these specific structures/subgraphs, the fundamental properties of the network can be derived. More specifically in biological networks, subgraph matching algorithms are used to discover network motifs, specific patterns occurring more often than expected by chance. Finding these network motifs yields information on the underlying biological relations modelled by the network. In this work, we present the Index-based Subgraph Matching Algorithm with General Symmetries (ISMAGS), an improved version of the Index-based Subgraph Matching Algorithm (ISMA). ISMA quickly finds all instances of a predefined motif in a network by intelligently exploring the search space and taking into account easily identifiable symmetric structures. However, more complex symmetries (possibly involving switching multiple nodes) are not taken into account, resulting in superfluous output. ISMAGS overcomes this problem by using a customised symmetry analysis phase to detect all symmetric structures in the network motif subgraphs. These structures are then converted to symmetry-breaking constraints used to prune the search space and speed up calculations. The performance of the algorithm was tested on several types of networks (biological, social and computer networks) for various subgraphs with a varying degree of symmetry. For subgraphs with complex (multi-node) symmetric structures, high speed-up factors are obtained as the search space is pruned by the symmetry-breaking constraints. For subgraphs with no or simple symmetric structures, ISMAGS still reduces computation times by optimising set operations. Moreover, the calculated list of subgraph instances is minimal as it contains no instances that differ by only a subgraph symmetry. An implementation of the algorithm is freely available at https://github.com/mhoubraken/ISMAGS