Influence of biocontrol strain Pseudomonas fluorescens CHA0 and its antibiotic overproducing derivative on the diversity of root colonizing pseudomonads

Non-target effects of biocontrol strains of Pseudomonas on the population of resident pseudomonads should be assessed prior to their large scale application in the environment. The rifampicin resistant bacterium P. fluorescens CHA0-Rif and its antibiotic overproducing derivative CHA0-Rif/pME3424 were introduced into soil microcosms and the population of resident pseudomonads colonizing cucumber roots was investigated after 10 and 52 days. Both CHA0-Rif and CHA0-Rif/pME3424 displaced a part of the resident pseudomonad population after 10 days. To investigate the population structure, utilization of 10 carbon sources and production of two exoenzymes was assessed for 5600 individual pseudomonad isolates and 1700 isolates were subjected to amplified ribosomal DNA restriction analysis of the spacer region (spacer-ARDRA). After 10 days, only the proportion of pseudomonads able to degrade -tryptophan was reduced in treatments inoculated with either biocontrol strain. In parallel the phenotypic diversity was reduced. These effects were only observed 10 days after inoculation, and they were similar for inoculation with CHA0-Rif and CHA0-Rif/pME3424. Changes in the population structure of resident pseudomonads on cucumber roots during plant growth were more pronounced than changes due to the inoculants. The inoculants did not affect the genotypic diversity detected with spacer-ARDRA, but the genotypic fingerprints corresponded only partially to the phenotypic profiles. Overall CHA0-Rif had a small and transient impact on the population of resident pseudomonads and the effect was essentially the same for the genetically engineered derivative CHA0-

Focal degeneration of astrocytes in amyotrophic lateral sclerosis

Astrocytes emerge as key players in motor neuron degeneration in Amyotrophic Lateral Sclerosis (ALS). Whether astrocytes cause direct damage by releasing toxic factors or contribute indirectly through the loss of physiological functions is unclear. Here we identify in the hSOD1(G93A) transgenic mouse model of ALS a degenerative process of the astrocytes, restricted to those directly surrounding spinal motor neurons. This phenomenon manifests with an early onset and becomes significant concomitant with the loss of motor cells and the appearance of clinical symptoms. Contrary to wild-type astrocytes, mutant hSOD1-expressing astrocytes are highly vulnerable to glutamate and undergo cell death mediated by the metabotropic type-5 receptor (mGluR5). Blocking mGluR5 in vivo slows down astrocytic degeneration, delays the onset of the disease and slightly extends survival in hSOD1(G93A) transgenic mice. We propose that excitotoxicity in ALS affects both motor neurons and astrocytes, favouring their local interactive degeneration. This new mechanistic hypothesis has implications for therapeutic interventions.Cell Death and Differentiation advance online publication, 11 July 2008; doi:10.1038/cdd.2008.99.

Accurate and early diagnosis of orthopedic device-related infection by microbial heat production and sonication.

Proper and rapid diagnosis of orthopedic device-related infection is important for successful treatment. Sonication has been shown to improve the diagnostic performance. We hypothesized that the combination of sonication with a novel method called microcalorimetry will further improve and accelerate the diagnosis of implant infection. We prospectively included 39 consecutive patients (mean age 59 years, 62% males) at our institution from whom 29 orthopedic prostheses and 10 osteosynthesis material were explanted. The explanted device was sonicated. The resulting sonication fluid was analyzed using microcalorimetry. Using standardized criteria to define orthopedic device-related infection, 12 cases (31%) were defined as infected. In all, positive periprosthetic tissue cultures were found. The sensitivity and specificity of microcalorimetry of sonication fluid were 100% and 97%, respectively. Mean time to detection, defined as time to reach a rising heat flow signal of 20 µW measured after equilibiration needed to get accurate measurement, was 10.9 h. In summary, microcalorimetry of sonication fluid is a reliable and a fast method in detecting the presence of microorganisms in orthopedic device-related infection. © 2013 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 31:1700-1703, 2013.

Prediction of hip fracture risk by quantitative ultrasound in more than 7000 Swiss women > or =70 years of age: comparison of three technologically different bone ultrasound devices in the SEMOF study.

To compare the prediction of hip fracture risk of several bone ultrasounds (QUS), 7062 Swiss women > or =70 years of age were measured with three QUSs (two of the heel, one of the phalanges). Heel QUSs were both predictive of hip fracture risk, whereas the phalanges QUS was not. INTRODUCTION: As the number of hip fracture is expected to increase during these next decades, it is important to develop strategies to detect subjects at risk. Quantitative bone ultrasound (QUS), an ionizing radiation-free method, which is transportable, could be interesting for this purpose. MATERIALS AND METHODS: The Swiss Evaluation of the Methods of Measurement of Osteoporotic Fracture Risk (SEMOF) study is a multicenter cohort study, which compared three QUSs for the assessment of hip fracture risk in a sample of 7609 elderly ambulatory women > or =70 years of age. Two QUSs measured the heel (Achilles+; GE-Lunar and Sahara; Hologic), and one measured the heel (DBM Sonic 1200; IGEA). The Cox proportional hazards regression was used to estimate the hazard of the first hip fracture, adjusted for age, BMI, and center, and the area under the ROC curves were calculated to compare the devices and their parameters. RESULTS: From the 7609 women who were included in the study, 7062 women 75.2 +/- 3.1 (SD) years of age were prospectively followed for 2.9 +/- 0.8 years. Eighty women reported a hip fracture. A decrease by 1 SD of the QUS variables corresponded to an increase of the hip fracture risk from 2.3 (95% CI, 1.7, 3.1) to 2.6 (95% CI, 1.9, 3.4) for the three variables of Achilles+ and from 2.2 (95% CI, 1.7, 3.0) to 2.4 (95% CI, 1.8, 3.2) for the three variables of Sahara. Risk gradients did not differ significantly among the variables of the two heel QUS devices. On the other hand, the phalanges QUS (DBM Sonic 1200) was not predictive of hip fracture risk, with an adjusted hazard risk of 1.2 (95% CI, 0.9, 1.5), even after reanalysis of the digitalized data and using different cut-off levels (1700 or 1570 m/s). CONCLUSIONS: In this elderly women population, heel QUS devices were both predictive of hip fracture risk, whereas the phalanges QUS device was not.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PURPOSE: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. METHOD: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). RESULTS: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. CONCLUSION: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.