Phylogenetic analysis of "Candidatus Mycoplasma turicensis" isolates from pet cats in the United Kingdom, Australia, and South Africa, with analysis of risk factors for infection

Two hemotropic mycoplasmas have been recognized in cats, Mycoplasma haemofelis and "Candidatus Mycoplasma haemominutum." We recently described a third feline hemoplasma species, designated "Candidatus Mycoplasma turicensis," in a Swiss cat with hemolytic anemia. This isolate induced anemia after experimental transmission to two specific-pathogen-free cats and analysis of the 16S rRNA gene revealed its close relationship to rodent hemotropic mycoplasmas. The agent was recently shown to be prevalent in Swiss pet cats. We sought to investigate the presence and clinical importance of "Candidatus Mycoplasma turicensis" infection in pet cats outside of Switzerland and to perform the molecular characterization of isolates from different countries. A "Candidatus Mycoplasma turicensis"-specific real-time PCR assay was applied to blood samples from 426 United Kingdom (UK), 147 Australian, and 69 South African pet cats. The 16S rRNA genes of isolates from different countries were sequenced and signalment and laboratory data for the cats were evaluated for associations with "Candidatus Mycoplasma turicensis" infection. Infections were detected in samples from UK, Australian, and South African pet cats. Infection was associated with the male gender, and "Candidatus Mycoplasma haemominutum" and M. haemofelis coinfection. Coinfected cats exhibited significantly lower packed cell volume (PCV) values than uninfected cats. Phylogenetic analyses revealed that some Australian and South African "Candidatus Mycoplasma turicensis" isolates branched away from the remaining isolates. In summary, "Candidatus Mycoplasma turicensis" infection in pet cats exists over a wide geographical area and significantly decreased PCV values are observed in cats coinfected with other feline hemoplasmas.

Brain areas involved in medial temporal lobe seizures: a principal component analysis of ictal SPECT data

The study describes brain areas involved in medial temporal lobe (mTL) seizures of 12 patients. All patients showed so-called oro-alimentary behavior within the first 20 s of clinical seizure manifestation characteristic of mTL seizures. Single photon emission computed tomography (SPECT) images of regional cerebral blood flow (rCBF) were acquired from the patients in ictal and interictal phases and from normal volunteers. Image analysis employed categorical comparisons with statistical parametric mapping and principal component analysis (PCA) to assess functional connectivity. PCA supplemented the findings of the categorical analysis by decomposing the covariance matrix containing images of patients and healthy subjects into distinct component images of independent variance, including areas not identified by the categorical analysis. Two principal components (PCs) discriminated the subject groups: patients with right or left mTL seizures and normal volunteers, indicating distinct neuronal networks implicated by the seizure. Both PCs were correlated with seizure duration, one positively and the other negatively, confirming their physiological significance. The independence of the two PCs yielded a clear clustering of subject groups. The local pattern within the temporal lobe describes critical relay nodes which are the counterpart of oro-alimentary behavior: (1) right mesial temporal zone and ipsilateral anterior insula in right mTL seizures, and (2) temporal poles on both sides that are densely interconnected by the anterior commissure. Regions remote from the temporal lobe may be related to seizure propagation and include positively and negatively loaded areas. These patterns, the covarying areas of the temporal pole and occipito-basal visual association cortices, for example, are related to known anatomic paths.

Analysis of patient flows for orthopedic procedures using small area analysis in Switzerland

BACKGROUND: In general cantons regulate and control the Swiss health service system; patient flows within and between cantons are thereby partially disregarded. This paper develops an alternative spatial model, based upon the construction of orthopedic hospital service areas (HSAOs), and introduces indices for the analysis of patient streams in order to identify areas, irrespective of canton, with diverse characteristics, importance, needs, or demands. METHODS: HSAOs were constructed using orthopedic discharge data. Patient streams between the HSAOs were analysed by calculating three indices: the localization index (% local residents discharged locally), the netindex (the ratio of discharges of nonlocal incoming residents to outgoing local residents), and the market share index (% of local resident discharges of all discharges in local hospitals). RESULTS: The 85 orthopedic HSAOs show a median localization index of 60.8%, a market share index of 75.1%, and 30% of HSAOs have a positive netindex. Insurance class of bed, admission type, and patient age are partially but significantly associated with those indicators. A trend to more centrally provided health services can be observed not only in large urban HSAOs such as Geneva, Bern, Basel, and Zurich, but also in HSAOs in mountain sport areas such as Sion, Davos, or St.Moritz. Furthermore, elderly and emergency patients are more frequently treated locally than younger people or those having elective procedures. CONCLUSION: The division of Switzerland into HSAOs provides an alternative spatial model for analysing and describing patient streams for health service utilization. Because this small area model allows more in-depth analysis of patient streams both within and between cantons, it may improve support and planning of resource allocation of in-patient care in the Swiss healthcare system.

How does spatial extent of fMRI datasets affect independent component analysis decomposition?

Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.

Analysis of gene order data supports vertical inheritance of the leukotoxin operon and genome rearrangements in the 5' flanking region in genus Mannheimia

BACKGROUND: The Mannheimia subclades belong to the same bacterial genus, but have taken divergent paths toward their distinct lifestyles. For example, M. haemolytica + M. glucosida are potential pathogens of the respiratory tract in the mammalian suborder Ruminantia, whereas M. ruminalis, the supposed sister group, lives as a commensal in the ovine rumen. We have tested the hypothesis that vertical inheritance of the leukotoxin (lktCABD) operon has occurred from the last common ancestor of genus Mannheimia to any ancestor of the diverging subclades by exploring gene order data. RESULTS: We examined the gene order in the 5' flanking region of the leukotoxin operon and found that the 5' flanking gene strings, hslVU-lapB-artJ-lktC and xylAB-lktC, are peculiar to M. haemolytica + M. glucosida and M. granulomatis, respectively, whereas the gene string hslVU-lapB-lktC is present in M. ruminalis, the supposed sister group of M. haemolytica + M. glucosida, and in the most ancient subclade M. varigena. In M. granulomatis, we found remnants of the gene string hslVU-lapB-lktC in the xylB-lktC intergenic region. CONCLUSION: These observations indicate that the gene string hslVU-lapB-lktC is more ancient than the hslVU-lapB-artJ-lktC and xylAB-lktC gene strings. The presence of (remnants of) the ancient gene string hslVU-lapB-lktC among any subclades within genus Mannheimia supports that it has been vertically inherited from the last common ancestor of genus Mannheimia to any ancestor of the diverging subclades, thus reaffirming the hypothesis of vertical inheritance of the leukotoxin operon. The presence of individual 5' flanking regions in M. haemolytica + M. glucosida and M. granulomatis reflects later genome rearrangements within each subclade. The evolution of the novel 5' flanking region in M. haemolytica + M. glucosida resulted in transcriptional coupling between the divergently arranged artJ and lkt promoters. We propose that the chimeric promoter have led to high level expression of the leukotoxin operon which could explain the increased potential of certain M. haemolytica + M. glucosida strains to cause a particular type of infection.

Determination of histopathological tumor grade in neuroepithelial brain tumors by using spectral pattern analysis of in vivo spectroscopic data

OBJECT: In this study, 1H magnetic resonance (MR) spectroscopy was prospectively tested as a reliable method for presurgical grading of neuroepithelial brain tumors. METHODS: Using a database of tumor spectra obtained in patients with histologically confirmed diagnoses, 94 consecutive untreated patients were studied using single-voxel 1H spectroscopy (point-resolved spectroscopy; TE 135 msec, TE 135 msec, TR 1500 msec). A total of 90 tumor spectra obtained in patients with diagnostic 1H MR spectroscopy examinations were analyzed using commercially available software (MRUI/VARPRO) and classified using linear discriminant analysis as World Health Organization (WHO) Grade I/II, WHO Grade III, or WHO Grade IV lesions. In all cases, the classification results were matched with histopathological diagnoses that were made according to the WHO classification criteria after serial stereotactic biopsy procedures or open surgery. Histopathological studies revealed 30 Grade I/II tumors, 29 Grade III tumors, and 31 Grade IV tumors. The reliability of the histological diagnoses was validated considering a minimum postsurgical follow-up period of 12 months (range 12-37 months). Classifications based on spectroscopic data yielded 31 tumors in Grade I/II, 32 in Grade III, and 27 in Grade IV. Incorrect classifications included two Grade II tumors, one of which was identified as Grade III and one as Grade IV; two Grade III tumors identified as Grade II; two Grade III lesions identified as Grade IV; and six Grade IV tumors identified as Grade III. Furthermore, one glioblastoma (WHO Grade IV) was classified as WHO Grade I/II. This represents an overall success rate of 86%, and a 95% success rate in differentiating low-grade from high-grade tumors. CONCLUSIONS: The authors conclude that in vivo 1H MR spectroscopy is a reliable technique for grading neuroepithelial brain tumors.

Learning styles vary among general surgery residents: analysis of 12 years of data

PURPOSE: Understanding the learning styles of individuals may assist in the tailoring of an educational program to optimize learning. General surgery faculty and residents have been characterized previously as having a tendency toward particular learning styles. We seek to understand better the learning styles of general surgery residents and differences that may exist within the population. METHODS: The Kolb Learning Style Inventory was administered yearly to general surgery residents at the University of Cincinnati from 1994 to 2006. This tool allows characterization of learning styles into 4 groups: converging, accommodating, assimilating, and diverging. The converging learning style involves education by actively solving problems. The accommodating learning style uses emotion and interpersonal relationships. The assimilating learning style learns by abstract logic. The diverging learning style learns best by observation. Chi-square analysis and analysis of variance were performed to determine significance. RESULTS: Surveys from 1994 to 2006 (91 residents, 325 responses) were analyzed. The prevalent learning style was converging (185, 57%), followed by assimilating (58, 18%), accommodating (44, 14%), and diverging (38, 12%). At the PGY 1 and 2 levels, male and female residents differed in learning style, with the accommodating learning style being relatively more frequent in women and assimilating learning style more frequent in men (Table 1, p < or = 0.001, chi-square test). Interestingly, learning style did not seem to change with advancing PGY level within the program, which suggests that individual learning styles may be constant throughout residency training. If a resident's learning style changed, it tended to be to converging. In addition, no relation exists between learning style and participation in dedicated basic science training or performance on the ABSIT/SBSE. CONCLUSIONS: Our data suggests that learning style differs between male and female general surgery residents but not with PGY level or ABSIT/SBSE performance. A greater understanding of individual learning styles may allow more refinement and tailoring of surgical programs.

From Statistical Data to Spatial Knowledge - informing decision making in Vietnam

Vietnam has developed rapidly over the past 15 years. However, progress was not uniformly distributed across the country. Availability, adequate visualization and analysis of spatially explicit data on socio-economic and environmental aspects can support both research and policy towards sustainable development. Applying appropriate mapping techniques allows gleaning important information from tabular socio-economic data. Spatial analysis of socio-economic phenomena can yield insights into locally-specifi c patterns and processes that cannot be generated by non-spatial applications. This paper presents techniques and applications that develop and analyze spatially highly disaggregated socioeconomic datasets. A number of examples show how such information can support informed decisionmaking and research in Vietnam.

Spatial Assessment of Erosion and its Impact on Soil Fertility in the Tajik Foothills

Efficient planning of soil conservation measures requires, first, to understand the impact of soil erosion on soil fertility with regard to local land cover classes; and second, to identify hot spots of soil erosion and bright spots of soil conservation in a spatially explicit manner. Soil organic carbon (SOC) is an important indicator of soil fertility. The aim of this study was to conduct a spatial assessment of erosion and its impact on SOC for specific land cover classes. Input data consisted of extensive ground truth, a digital elevation model and Landsat 7 imagery from two different seasons. Soil spectral reflectance readings were taken from soil samples in the laboratory and calibrated with results of SOC chemical analysis using regression tree modelling. The resulting model statistics for soil degradation assessments are promising (R2=0.71, RMSEV=0.32). Since the area includes rugged terrain and small agricultural plots, the decision tree models allowed mapping of land cover classes, soil erosion incidence and SOC content classes at an acceptable level of accuracy for preliminary studies. The various datasets were linked in the hot-bright spot matrix, which was developed to combine soil erosion incidence information and SOC content levels (for uniform land cover classes) in a scatter plot. The quarters of the plot show different stages of degradation, from well conserved land to hot spots of soil degradation. The approach helps to gain a better understanding of the impact of soil erosion on soil fertility and to identify hot and bright spots in a spatially explicit manner. The results show distinctly lower SOC content levels on large parts of the test areas, where annual crop cultivation was dominant in the 1990s and where cultivation has now been abandoned. On the other hand, there are strong indications that afforestations and fruit orchards established in the 1980s have been successful in conserving soil resources.

Individual patient data meta-analysis of diagnostic and prognostic studies in obstetrics, gynaecology and reproductive medicine

BACKGROUND: In clinical practice a diagnosis is based on a combination of clinical history, physical examination and additional diagnostic tests. At present, studies on diagnostic research often report the accuracy of tests without taking into account the information already known from history and examination. Due to this lack of information, together with variations in design and quality of studies, conventional meta-analyses based on these studies will not show the accuracy of the tests in real practice. By using individual patient data (IPD) to perform meta-analyses, the accuracy of tests can be assessed in relation to other patient characteristics and allows the development or evaluation of diagnostic algorithms for individual patients. In this study we will examine these potential benefits in four clinical diagnostic problems in the field of gynaecology, obstetrics and reproductive medicine. METHODS/DESIGN: Based on earlier systematic reviews for each of the four clinical problems, studies are considered for inclusion. The first authors of the included studies will be invited to participate and share their original data. After assessment of validity and completeness the acquired datasets are merged. Based on these data, a series of analyses will be performed, including a systematic comparison of the results of the IPD meta-analysis with those of a conventional meta-analysis, development of multivariable models for clinical history alone and for the combination of history, physical examination and relevant diagnostic tests and development of clinical prediction rules for the individual patients. These will be made accessible for clinicians. DISCUSSION: The use of IPD meta-analysis will allow evaluating accuracy of diagnostic tests in relation to other relevant information. Ultimately, this could increase the efficiency of the diagnostic work-up, e.g. by reducing the need for invasive tests and/or improving the accuracy of the diagnostic workup. This study will assess whether these benefits of IPD meta-analysis over conventional meta-analysis can be exploited and will provide a framework for future IPD meta-analyses in diagnostic and prognostic research.

Calibration and analysis of the 2007 data

he physics program of the NA61/SHINE (SHINE = SPS Heavy Ion and Neutrino Experiment) experiment at the CERN SPS consists of three subjects. In the first stage of data taking (2007-2009) measurements of hadron production in hadron-nucleus interactions needed for neutrino (T2K) and cosmic-ray (Pierre Auger and KASCADE) experiments will be performed. In the second stage (2009-2010) hadron production in proton-proton and proton-nucleus interactions needed as reference data for a better understanding of nucleus-nucleus reactions will be studied. In the third stage (2009-2013) energy dependence of hadron production properties will be measured in p+p, p+Pb interactions and nucleus-nucleus collisions, with the aim to identify the properties of the onset of deconfinement and find evidence for the critical point of strongly interacting matter. The NA61 experiment was approved at CERN in June 2007. The first pilot run was performed during October 2007. Calibrations of all detector components have been performed successfully and preliminary uncorrected spectra have been obtained. High quality of track reconstruction and particle identification similar to NA49 has been achieved. The data and new detailed simulations confirm that the NA61 detector acceptance and particle identification capabilities cover the phase space required by the T2K experiment. This document reports on the progress made in the calibration and analysis of the 2007 data.

An analysis of the Galveston Hurricane using the 20CR data set

The Twentieth Century Reanalysis (20CR) is an atmospheric dataset consisting of 56 ensemble members, which covers the entire globe and reaches back to 1871. To assess the suitability of this dataset for studying past extremes, we analysed a prominent extreme event, namely the Galveston Hurricane, which made landfall in September 1900 in Texas, USA. The ensemble mean of 20CR shows a track of the pressure minimum with a small standard deviation among the 56 ensemble members in the area of the Gulf of Mexico. However, there are systematic differences between the assimilated “Best Track” from the International Best Track Archive for Climate Stewardship (IBTrACS) and the ensemble mean track in 20CR. East of the Strait of Florida, the tracks derived from 20CR are located systematically northeast of the assimilated track while in the Gulf of Mexico, the 20CR tracks are systematically shifted to the southwest compared to the IBTrACS position. The hurricane can also be observed in the wind field, which shows a cyclonic rotation and a relatively calm zone in the centre of the hurricane. The 20CR data reproduce the pressure gradient and cyclonic wind field. Regarding the amplitude of the wind speeds, the ensemble mean values from 20CR are significantly lower than the wind speeds known from measurements.