Identification of Francisella tularensis cluster in central and western Europe

We conducted a molecular analysis of Francisella tularensis strains isolated in Switzerland and identified a specific subpopulation belonging to a cluster of F. tularensis subsp. holarctica that is widely dispersed in central and western continental Europe. This subpopulation was present before the tularemia epidemics on the Iberian Peninsula.

Long-term patterns of subjective wellbeing in schizophrenia: cluster, predictors of cluster affiliation, and their relation to recovery criteria in 2842 patients followed over 3 years

To study the longitudinal patterns of subjective wellbeing in schizophrenia using cluster analysis and their relation to recovery criteria, further to examine predictors for cluster affiliation, and to evaluate the sensitivity and specificity of baseline subjective wellbeing cut-offs for cluster affiliation.

Cluster randomized clinical trials in orthodontics: design, analysis and reporting issues

Cluster randomized trials (CRTs) use as the unit of randomization clusters, which are usually defined as a collection of individuals sharing some common characteristics. Common examples of clusters include entire dental practices, hospitals, schools, school classes, villages, and towns. Additionally, several measurements (repeated measurements) taken on the same individual at different time points are also considered to be clusters. In dentistry, CRTs are applicable as patients may be treated as clusters containing several individual teeth. CRTs require certain methodological procedures during sample calculation, randomization, data analysis, and reporting, which are often ignored in dental research publications. In general, due to similarity of the observations within clusters, each individual within a cluster provides less information compared with an individual in a non-clustered trial. Therefore, clustered designs require larger sample sizes compared with non-clustered randomized designs, and special statistical analyses that account for the fact that observations within clusters are correlated. It is the purpose of this article to highlight with relevant examples the important methodological characteristics of cluster randomized designs as they may be applied in orthodontics and to explain the problems that may arise if clustered observations are erroneously treated and analysed as independent (non-clustered).

A 350 ka record of climate change from Lake El'gygytgyn, Far East Russian Arctic: refining the pattern of climate modes by means of cluster analysis

Abstract. Rock magnetic, biochemical and inorganic records of the sediment cores PG1351 and Lz1024 from Lake El’gygytgyn, Chukotka peninsula, Far East Russian Arctic, were subject to a hierarchical agglomerative cluster analysis in order to refine and extend the pattern of climate modes as defined by Melles et al. (2007). Cluster analysis of the data obtained from both cores yielded similar results, differentiating clearly between the four climate modes warm, peak warm, cold and dry, and cold and moist. In addition, two transitional phases were identified, representing the early stages of a cold phase and slightly colder conditions during a warm phase. The statistical approach can thus be used to resolve gradual changes in the sedimentary units as an indicator of available oxygen in the hypolimnion in greater detail. Based upon cluster analyses on core Lz1024, the published succession of climate modes in core PG1351, covering the last 250 ka, was modified and extended back to 350 ka. Comparison to the marine oxygen isotope (�18O) stack LR04 (Lisiecki and Raymo, 2005) and the summer insolation at 67.5� N, with the extended Lake El’gygytgyn parameter records of magnetic susceptibility (�LF), total organic carbon content (TOC) and the chemical index of alteration (CIA; Minyuk et al., 2007), revealed that all stages back to marine isotope stage (MIS) 10 and most of the substages are clearly reflected in the pattern derived from the cluster analysis.

Cooperative Effects of Electron Donors and Acceptors for the Stabilization of Elusive Metal Cluster Frameworks: Synthesis and Solid-State Structures of Pt-19(CO)(24)(mu(4)-AuPPh3)(3)](-) and Pt-19(CO)(24){mu(4)-Au-2(PPh3)(2)}(2)]

The anionic cluster Pt-19(CO)(22)](4-) (1), of pentagonal symmetry, reacts with CO and AuPPh3+ fragments. Upon increasing the Au:Pt-19, molar ratio, different species are sequentially formed, but only the last two members of the series could be characterized by X-ray diffraction, namely, Pt-19(CO)(24)(mu(4)-AuPPh3)(3)](-) (2) and Pt-19(CO)(24){mu(4)-Au-2(PPh3)(2)}(2)] (3).The metallic framework of the starting cluster is completely modified after the addition of CO and AuL+, and both products display the same platinum core of trigonal symmetry, with closely packed metal atoms. The three AuL+ units cap three different square faces in 2, whereas four AuL+ fragments are grouped in two independent bimetallic units in the neutral cluster 3. Electrochemical and spectroelectrochemical studies on 2 showed that its redox ability is comparable with that of the homometallic 1.

The origin of the 'Mycoplasma mycoides cluster' coincides with domestication of ruminants.

The 'Mycoplasma mycoides cluster' comprises the ruminant pathogens Mycoplasma mycoides subsp. mycoides the causative agent of contagious bovine pleuropneumonia (CBPP), Mycoplasma capricolum subsp. capripneumoniae the agent of contagious caprine pleuropneumonia (CCPP), Mycoplasma capricolum subsp. capricolum, Mycoplasma leachii and Mycoplasma mycoides subsp. capri. CBPP and CCPP are major livestock diseases and impact the agricultural sector especially in developing countries through reduced food-supply and international trade restrictions. In addition, these diseases are a threat to disease-free countries. We used a multilocus sequence typing (MLST) approach to gain insights into the demographic history of and phylogenetic relationships among the members of the 'M. mycoides cluster'. We collected partial sequences from seven housekeeping genes representing a total of 3,816 base pairs from 118 strains within this cluster, and five strains isolated from wild Caprinae. Strikingly, the origin of the 'M. mycoides cluster' dates to about 10,000 years ago, suggesting that the establishment and spread of the cluster coincided with livestock domestication. In addition, we show that hybridization and recombination may be important factors in the evolutionary history of the cluster.

Improvement of antibiotic prescription in outpatient care: a cluster-randomized intervention study using a sentinel surveillance network of physicians.

OBJECTIVES To assess the effectiveness of implementing guidelines, coupled with individual feedback, on antibiotic prescribing behaviour of primary care physicians in Switzerland. METHODS One hundred and forty general practices from a representative Swiss sentinel network of primary care physicians participated in this cluster-randomized prospective intervention study. The intervention consisted of providing guidelines on treatment of respiratory tract infections (RTIs) and uncomplicated lower urinary tract infections (UTIs), coupled with sustained, regular feedback on individual antibiotic prescription behaviour during 2 years. The main aims were: (i) to increase the percentage of prescriptions of penicillins for all RTIs treated with antibiotics; (ii) to increase the percentage of trimethoprim/sulfamethoxazole prescriptions for all uncomplicated lower UTIs treated with antibiotics; (iii) to decrease the percentage of quinolone prescriptions for all cases of exacerbated COPD (eCOPD) treated with antibiotics; and (iv) to decrease the proportion of sinusitis and other upper RTIs treated with antibiotics. The study was registered at ClinicalTrials.gov (NCT01358916). RESULTS While the percentage of antibiotics prescribed for sinusitis or other upper RTIs and the percentage of quinolones prescribed for eCOPD did not differ between the intervention group and the control group, there was a significant increase in the percentage of prescriptions of penicillins for all RTIs treated with antibiotics [57% versus 49%, OR = 1.42 (95% CI 1.08-1.89), P = 0.01] and in the percentage of trimethoprim/sulfamethoxazole prescriptions for all uncomplicated lower UTIs treated with antibiotics [35% versus 19%, OR = 2.16 (95% CI 1.19-3.91), P = 0.01] in the intervention group. CONCLUSIONS In our setting, implementing guidelines, coupled with sustained individual feedback, was not able to reduce the proportion of sinusitis and other upper RTIs treated with antibiotics, but increased the use of recommended antibiotics for RTIs and UTIs, as defined by the guidelines.

Cluster of Bacteria Associated with Peri-Implantitis.

BACKGROUND Information on the microbiota in peri-implantitis is limited. We hypothesized that neither gender nor a history of periodontitis/smoking or the microbiota at implants differ by implant status. MATERIALS AND METHODS Baseline microbiological samples collected at one implant in each of 166 participants with peri-implantitis and from 47 individuals with a healthy implant were collected and analyzed by DNA-DNA checkerboard hybridization (78 species). Clinical and radiographic data defined implant status. RESULTS Nineteen bacterial species were found at higher counts from implants with peri-implantitis including Aggregatibacter actinomycetemcomitans, Campylobacter gracilis, Campylobacter rectus, Campylobacter showae, Helicobacter pylori, Haemophilus influenzae, Porphyromonas gingivalis, Staphylococcus aureus, Staphylococcus anaerobius, Streptococcus intermedius, Streptococcus mitis, Tannerella forsythia, Treponema denticola, and Treponema socranskii (p < .001). Receiver operating characteristic curve analysis identified T. forsythia, P. gingivalis, T. socranskii, Staph. aureus, Staph. anaerobius, Strep. intermedius, and Strep. mitis in peri-implantitis comprising 30% of the total microbiota. When adjusted for gender (not significant [NS]), smoking status (NS), older age (p = .003), periodontitis history (p < .01), and T. forsythia (likelihood ratio 3.6, 95% confidence interval 1.4, 9.1, p = .007) were associated with peri-implantitis. CONCLUSION A cluster of bacteria including T. forsythia and Staph. aureus are associated with peri-implantitis.