Classification of organisms previously reported as the SP and Stewart-Letscher groups, with descriptions of Necropsobacter gen. nov. and of Necropsobacter rosorum sp. nov. for organisms of the SP group

To allow classification of bacteria previously reported as the SP group and the Stewart-Letscher group, 35 isolates from rodents (21), rabbits (eight), a dog and humans (five) were phenotypically and genotypically characterized. Comparison of partial rpoB sequences showed that 34 of the isolates were closely related, demonstrating at least 97.4 % similarity. 16S rRNA gene sequence comparison of 20 selected isolates confirmed the monophyly of the SP group and revealed 98.5 %-100 % similarity between isolates. A blast search using the 16S rRNA gene sequences showed that the highest similarity outside the SP group was 95.5 % to an unclassified rat isolate. The single strain, P625, representing the Stewart-Letscher group showed the highest 16S rRNA gene similarity (94.9-95.5 %) to members of the SP group. recN gene sequence analysis of 11 representative strains resulted in similarities of 97-100 % among the SP group strains, which showed 80 % sequence similarity to the Stewart-Letscher group strain. Sequence similarity values based on the recN gene, indicative for whole genome similarity, showed the SP group being clearly separated from established genera, whereas the Stewart-Letscher group strain was associated with the SP group. A new genus, Necropsobacter gen. nov., with only one species, Necropsobacter rosorum sp. nov., is proposed to include all members of the SP group. The new genus can be separated from existing genera of the family Pasteurellaceae by at least three phenotypic characters. The most characteristic properties of the new genus are that haemolysis is not observed on bovine blood agar, positive reactions are observed in the porphyrin test, acid is produced from (+)-L-arabinose, (+)-D-xylose, dulcitol, (+)-D-galactose, (+)-D-mannose, maltose and melibiose, and negative reactions are observed for symbiotic growth, urease, ornithine decarboxylase and indole. Previous publications have documented that both ubiquinones and demethylmenaquinone were produced by the proposed type strain of the new genus, Michel A/76(T), and that the major polyamine of representative strains (type strain not included) of the genus is 1,3-diaminopropane, spermidine is present in moderate amounts and putrescine and spermine are detectable only in minor amounts. The major fatty acids of strain Michel A/76(T) are C(14 : 0), C(16 : 0), C(16:1)omega7c and summed feature C(14 : 0) 3-OH/iso-C(16 : 1) I. This fatty acid profile is typical for members of the family Pasteurellaceae. The G+C content of DNA of strain Michel A/76(T) was estimated to be 52.5 mol% in a previous investigation. The type strain is P709(T) ( = Michel A/76(T) = CCUG 28028(T) = CIP 110147(T) = CCM 7802(T)).

Stratification and Prognostic Relevance of Jass's Molecular Classification of Colorectal Cancer

Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP), microsatellite instability (MSI), KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT) and classifies tumors into five subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: Three hundred two patients were included in this study. Molecular analysis was performed for five CIMP-related promoters (CRABP1, MLH1, p16INK4a, CACNA1G, NEUROG1), MGMT, MSI, KRAS, and BRAF. Methylation in at least 4 promoters or in one to three promoters was considered CIMP-high and CIMP-low (CIMP-H/L), respectively. Results: CIMP-H, CIMP-L, and CIMP-negative were found in 7.1, 43, and 49.9% cases, respectively. One hundred twenty-three tumors (41%) could not be classified into any one of the proposed molecular subgroups, including 107 CIMP-L, 14 CIMP-H, and two CIMP-negative cases. The 10 year survival rate for CIMP-high patients [22.6% (95%CI: 7-43)] was significantly lower than for CIMP-L or CIMP-negative (p = 0.0295). Only the combined analysis of BRAF and CIMP (negative versus L/H) led to distinct prognostic subgroups. Conclusion: Although CIMP status has an effect on outcome, our results underline the need for standardized definitions of low- and high-level CIMP, which clearly hinders an effective prognostic and molecular classification of colorectal cancer.

Contemporary consensus proposal on criteria and classification of eosinophilic disorders and related syndromes

Eosinophilia is an important indicator of various neoplastic and nonneoplastic conditions. Depending on the underlying disease and mechanisms, eosinophil infiltration can lead to organ dysfunction, clinical symptoms, or both. During the past 2 decades, several different classifications of eosinophilic disorders and related syndromes have been proposed in various fields of medicine. Although criteria and definitions are, in part, overlapping, no global consensus has been presented to date. The Year 2011 Working Conference on Eosinophil Disorders and Syndromes was organized to update and refine the criteria and definitions for eosinophilic disorders and to merge prior classifications in a contemporary multidisciplinary schema. A panel of experts from the fields of immunology, allergy, hematology, and pathology contributed to this project. The expert group agreed on unifying terminologies and criteria and a classification that delineates various forms of hypereosinophilia, including primary and secondary variants based on specific hematologic and immunologic conditions, and various forms of the hypereosinophilic syndrome. For patients in whom no underlying disease or hypereosinophilic syndrome is found, the term hypereosinophilia of undetermined significance is introduced. The proposed novel criteria, definitions, and terminologies should assist in daily practice, as well as in the preparation and conduct of clinical trials.

Time course based artifact identification for independent components of resting-state FMRI

In functional magnetic resonance imaging (fMRI) coherent oscillations of the blood oxygen level-dependent (BOLD) signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting-state networks (RSN). Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA) and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting-state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82, and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting-state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting-state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

A mass spectrometric multicenter study supports classification of preeclampsia as heterogeneous disorder

The diagnostic value of affinity-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis to distinguish preeclampsia (PE) from matched controls was tested in a multicenter setting.

The influence of intention on masked priming: A study with semantic classification of words

Unconscious perception is commonly described as a phenomenon that is not under intentional control and relies on automatic processes. We challenge this view by arguing that some automatic processes may indeed be under intentional control, which is implemented in task-sets that define how the task is to be performed. In consequence, those prime attributes that are relevant to the task will be most effective. To investigate this hypothesis, we used a paradigm which has been shown to yield reliable short-lived priming in tasks based on semantic classification of words. This type of study uses fast, well practised classification responses, whereby responses to targets are much less accurate if prime and target belong to a different category than if they belong to the same category. In three experiments, we investigated whether the intention to classify the same words with respect to different semantic categories had a differential effect on priming. The results suggest that this was indeed the case: Priming varied with the task in all experiments. However, although participants reported not seeing the primes, they were able to classify the primes better than chance using the classification task they had used before with the targets. When a lexical task was used for discrimination in experiment 4, masked primes could however not be discriminated. Also, priming was as pronounced when the primes were visible as when they were invisible. The pattern of results suggests that participants had intentional control on prime processing, even if they reported not seeing the primes.

Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG)

The early detection of subjects with probable Alzheimer's disease (AD) is crucial for effective appliance of treatment strategies. Here we explored the ability of a multitude of linear and non-linear classification algorithms to discriminate between the electroencephalograms (EEGs) of patients with varying degree of AD and their age-matched control subjects. Absolute and relative spectral power, distribution of spectral power, and measures of spatial synchronization were calculated from recordings of resting eyes-closed continuous EEGs of 45 healthy controls, 116 patients with mild AD and 81 patients with moderate AD, recruited in two different centers (Stockholm, New York). The applied classification algorithms were: principal component linear discriminant analysis (PC LDA), partial least squares LDA (PLS LDA), principal component logistic regression (PC LR), partial least squares logistic regression (PLS LR), bagging, random forest, support vector machines (SVM) and feed-forward neural network. Based on 10-fold cross-validation runs it could be demonstrated that even tough modern computer-intensive classification algorithms such as random forests, SVM and neural networks show a slight superiority, more classical classification algorithms performed nearly equally well. Using random forests classification a considerable sensitivity of up to 85% and a specificity of 78%, respectively for the test of even only mild AD patients has been reached, whereas for the comparison of moderate AD vs. controls, using SVM and neural networks, values of 89% and 88% for sensitivity and specificity were achieved. Such a remarkable performance proves the value of these classification algorithms for clinical diagnostics.

Clinical forensic radiology in strangulation victims: forensic expertise based on magnetic resonance imaging (MRI) findings

Based on only one objective and several subjective signs, the forensic classification of strangulation incidents concerning their life-threatening quality can be problematic. Reflecting that it is almost impossible to detect internal injuries of the neck with the standard forensic external examination, we examined 14 persons who have survived manual and ligature strangulation or forearm choke holds using MRI technique (1.5-T scanner). Two clinical radiologists evaluated the neck findings independently. The danger to life was evaluated based on the "classical" external findings alone and in addition to the radiological data. We observed hemorrhaging in the subcutaneous fatty tissue of the neck in ten cases. Other frequent findings were hemorrhages of the neck and larynx muscles, the lymph nodes, the pharynx, and larynx soft tissues. Based on the classical forensic strangulation findings with MRI, eight of the cases were declared as life-endangering incidents, four of them without the presence of petechial hemorrhage but with further signs of impaired brain function due to hypoxia. The accuracy of future forensic classification of the danger to life will probably be increased when it is based not only on one objective and several subjective signs but also on the evidence of inner neck injuries. However, further prospective studies including larger cohorts are necessary to clarify the value of the inner neck injuries in the forensic classification of surviving strangulation victims.

A novel 2D-based approach to the discovery of candidate substrates for the metalloendopeptidase meprin

In the past, protease-substrate finding proved to be rather haphazard and was executed by in vitro cleavage assays using singly selected targets. In the present study, we report the first protease proteomic approach applied to meprin, an astacin-like metalloendopeptidase, to determine physiological substrates in a cell-based system of Madin-Darby canine kidney epithelial cells. A simple 2D IEF/SDS/PAGE-based image analysis procedure was designed to find candidate substrates in conditioned media of Madin-Darby canine kidney cells expressing meprin in zymogen or in active form. The method enabled the discovery of hitherto unknown meprin substrates with shortened (non-trypsin-generated) N- and C-terminally truncated cleavage products in peptide fragments upon LC-MS/MS analysis. Of 22 (17 nonredundant) candidate substrates identified, the proteolytic processing of vinculin, lysyl oxidase, collagen type V and annexin A1 was analysed by means of immunoblotting validation experiments. The classification of substrates into functional groups may propose new functions for meprins in the regulation of cell homeostasis and the extracellular environment, and in innate immunity, respectively.

Salivary stones and stenosis. A comprehensive classification

INTRODUCTION: Sialendoscopy and sialoMRI enables diagnosis of salivary gland obstructive pathologies, such as lithiasis, stenosis, and dilatations. Therefore, a classification of these pathologies is needed, allowing large series comparisons, for better diagnosis and treatment of salivary pathologies. MATERIAL AND METHODS: With help from people from the European Sialendoscopy Training Center (ESTC), the results of sialographies, sialoMRI and sialendoscopies, a comprehensive classification of obstructive salivary pathologies is described, based on the absence or presence of lithiasis (L), stenosis (S), and dilatation (D) ("LSD" classification). DISCUSSION: It appears that a classification of salivary gland obstructive pathologies should be described. We hope it will be widely used and of course criticized to be improved and to compare the results of salivary gland diagnostic methods, such as sialography and sialendoscopy, and also the results and indications for salivary gland therapeutic methods, such as lithotripsy, sialendoscopy, and/or open surgery.

A disease model for wheezing disorders in preschool children based on clinicians' perceptions

BACKGROUND: Wheezing disorders in childhood vary widely in clinical presentation and disease course. During the last years, several ways to classify wheezing children into different disease phenotypes have been proposed and are increasingly used for clinical guidance, but validation of these hypothetical entities is difficult. METHODOLOGY/PRINCIPAL FINDINGS: The aim of this study was to develop a testable disease model which reflects the full spectrum of wheezing illness in preschool children. We performed a qualitative study among a panel of 7 experienced clinicians from 4 European countries working in primary, secondary and tertiary paediatric care. In a series of questionnaire surveys and structured discussions, we found a general consensus that preschool wheezing disorders consist of several phenotypes, with a great heterogeneity of specific disease concepts between clinicians. Initially, 24 disease entities were described among the 7 physicians. In structured discussions, these could be narrowed down to three entities which were linked to proposed mechanisms: a) allergic wheeze, b) non-allergic wheeze due to structural airway narrowing and c) non-allergic wheeze due to increased immune response to viral infections. This disease model will serve to create an artificial dataset that allows the validation of data-driven multidimensional methods, such as cluster analysis, which have been proposed for identification of wheezing phenotypes in children. CONCLUSIONS/SIGNIFICANCE: While there appears to be wide agreement among clinicians that wheezing disorders consist of several diseases, there is less agreement regarding their number and nature. A great diversity of disease concepts exist but a unified phenotype classification reflecting underlying disease mechanisms is lacking. We propose a disease model which may help guide future research so that proposed mechanisms are measured at the right time and their role in disease heterogeneity can be studied.

Computer-aided diagnosis of carotid atherosclerosis based on ultrasound image statistics, laws' texture and neural networks

Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws' texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke.

Classification of the taxon 2 and taxon 3 complex of Bisgaard within Gallibacterium and description of Gallibacterium melopsittaci sp. nov., Gallibacterium trehalosifermentans sp. nov. and Gallibacterium salpingitidis sp. nov

This investigation was based on 23 isolates from several European countries collected over the past 30 years, and included characterization of all isolates. Published data on amplified fragment length polymorphism typing of isolates representing all biovars as well as protein profiles were used to select strains that were then further characterized by polyamine profiling and sequencing of 16S rRNA, infB, rpoB and recN genes. Comparison of 16S rRNA gene sequences revealed a monophyletic group within the avian 16S rRNA group of the Pasteurellaceae, which currently includes the genera Avibacterium, Gallibacterium and Volucribacter. Five monophyletic subgroups related to Gallibacterium anatis were recognized by 16S rRNA, rpoB, infB and recN gene sequence comparisons. Whole-genome similarity between strains of the five subgroups and the type strain of G. anatis calculated from recN sequences allowed us to classify them within the genus Gallibacterium. In addition, phenotypic data including biochemical traits, protein profiling and polyamine patterns clearly indicated that these taxa are related. Major phenotypic diversity was observed for 16S rRNA gene sequence groups. Furthermore, comparison of whole-genome similarities, phenotypic data and published data on amplified fragment length polymorphism and protein profiling revealed that each of the five groups present unique properties that allow the proposal of three novel species of Gallibacterium, for which we propose the names Gallibacterium melopsittaci sp. nov. (type strain F450(T) =CCUG 36331(T) =CCM 7538(T)), Gallibacterium trehalosifermentans sp. nov. (type strain 52/S3/90(T) =CCUG 55631(T) =CCM 7539(T)) and Gallibacterium salpingitidis sp. nov. (type strain F150(T) =CCUG 15564(T) =CCUG 36325(T) =NCTC 11414(T)), a novel genomospecies 3 of Gallibacterium and an unnamed taxon (group V). An emended description of the genus Gallibacterium is also presented.

IDH/MGMT-driven molecular classification of low-grade glioma is a strong predictor for long-term survival

BACKGROUND Low-grade gliomas (LGGs) are rare brain neoplasms, with survival spanning up to a few decades. Thus, accurate evaluations on how biomarkers impact survival among patients with LGG require long-term studies on samples prospectively collected over a long period. METHODS The 210 adult LGGs collected in our databank were screened for IDH1 and IDH2 mutations (IDHmut), MGMT gene promoter methylation (MGMTmet), 1p/19q loss of heterozygosity (1p19qloh), and nuclear TP53 immunopositivity (TP53pos). Multivariate survival analyses with multiple imputation of missing data were performed using either histopathology or molecular markers. Both models were compared using Akaike's information criterion (AIC). The molecular model was reduced by stepwise model selection to filter out the most critical predictors. A third model was generated to assess for various marker combinations. RESULTS Molecular parameters were better survival predictors than histology (ΔAIC = 12.5, P< .001). Forty-five percent of studied patients died. MGMTmet was positively associated with IDHmut (P< .001). In the molecular model with marker combinations, IDHmut/MGMTmet combined status had a favorable impact on overall survival, compared with IDHwt (hazard ratio [HR] = 0.33, P< .01), and even more so the triple combination, IDHmut/MGMTmet/1p19qloh (HR = 0.18, P< .001). Furthermore, IDHmut/MGMTmet/TP53pos triple combination was a significant risk factor for malignant transformation (HR = 2.75, P< .05). CONCLUSION By integrating networks of activated molecular glioma pathways, the model based on genotype better predicts prognosis than histology and, therefore, provides a more reliable tool for standardizing future treatment strategies.