Concentric characterization and classification of complex network nodes: Application to an institutional collaboration network

Differently from theoretical scale-free networks, most real networks present multi-scale behavior, with nodes structured in different types of functional groups and communities. While the majority of approaches for classification of nodes in a complex network has relied on local measurements of the topology/connectivity around each node, valuable information about node functionality can be obtained by concentric (or hierarchical) measurements. This paper extends previous methodologies based on concentric measurements, by studying the possibility of using agglomerative clustering methods, in order to obtain a set of functional groups of nodes, considering particular institutional collaboration network nodes, including various known communities (departments of the University of Sao Paulo). Among the interesting obtained findings, we emphasize the scale-free nature of the network obtained, as well as identification of different patterns of authorship emerging from different areas (e.g. human and exact sciences). Another interesting result concerns the relatively uniform distribution of hubs along concentric levels, contrariwise to the non-uniform pattern found in theoretical scale-free networks such as the BA model. (C) 2008 Elsevier B.V. All rights reserved.

CLASSIFICATION OF SUBALGEBRAS OF THE CAYLEY ALGEBRA OVER A FINITE FIELD

We classify all unital subalgebras of the Cayley algebra O(q) over the finite field F(q), q = p(n). We obtain the number of subalgebras of each type and prove that all isomorphic subalgebras are conjugate with respect to the automorphism group of O(q). We also determine the structure of the Moufang loops associated with each subalgebra of O(q).

Classification of Boal, Malvazia, Sercial and Verdelho wines based on terpenoid patterns

Thirty-six Madeira wine samples from Boal, Malvazia, Sercial and Verdelho white grape varieties were analyzed in order to estimate the free fraction of monoterpenols and C13 norisoprenoids (terpenoid compounds) using dynamic headspace solid phase micro-extraction (HS-SPME) technique coupled with gas chromatography–mass spectrometry (GC–MS). The average values from three vintages (1998–2000) show that these wines have characteristic profiles of terpenoid compounds. Malvazia wines exhibits the highest values of total free monoterpenols, contrary to Verdelho wines which had the lowest levels of terpenoids but produced the highest concentration of farnesol. The use of multivariate analysis techniques allows establishing relations between the compounds and the varieties under investigation. Principal component analysis (PCA) and linear discriminant analysis (LDA) were applied to the obtained matrix data. A good separation and classification power between the four groups as a function of their varietal origin was observed.

Environmental Fate of Neonicotinoids and Classification of Their Potential Risks to Hypogean, Epygean, and Surface Water Ecosystems in Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Self-Organizing Maps as a New Tool for Classification of Plants at Lower Hierarchical Levels

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Critical analysis of the international classification of headache disorders diagnostic criteria (ICHD I-1988) and (ICHD II-2004), for migraine in children and adolescents

The present study analyzed the (ICHD I-1988) and ( ICHD II-2004) diagnostic criteria in children and adolescents. Our population consisted of 496 patients of the Headache Outpatient Ward for Children and Adolescents retrospectively studied from 1992 to 2002. Individuals were classified according to three diagnostic groups: Intuitive Clinical Diagnosis ( Gold Standard), ICHD I-1988 and ICHD II-2004. They were statistically compared using the variables: Sensitivity ( S), Specificity (Sp), Positive Predictive Value (PPV), Negative Predictive Value (NPV). When ICHD I-1988 was used, the sensitivity of migraine without and with aura was 21% and 27%, respectively, whereas in ICHD II-2004 it changed to 53% and 71% without affecting specificity. As a conclusion, the current classification criteria ( ICHD II-2004) showed greater sensitivity and high specificity for migraine than ICHD I-1988, although it improved migraine diagnosis in children and adolescents, the sensitivity remains poor.

Classification of Aristolochia species based on GC-MS and chemometric analyses of essential oils

Essential oils were obtained from roots of 10 Aristolochia species by hydrodistillation and analysed by GC MS. A total of 75 compounds were identified in the analysed oils. Multivariate analyses of the chemical constituents of the roots enabled classification of the species into four morphological groups. These forms of analysis represent an aid in identification of further specimens belonging to these species. (C) 2007 Elsevier Ltd. All rights reserved.

Automatic classification of prostate stromal tissue in histological images using Haralick descriptors and Local Binary Patterns

In this paper we presente a classification system that uses a combination of texture features from stromal regions: Haralick features and Local Binary Patterns (LBP) in wavelet domain. The system has five steps for classification of the tissues. First, the stromal regions were detected and extracted using segmentation techniques based on thresholding and RGB colour space. Second, the Wavelet decomposition was applied in the extracted regions to obtain the Wavelet coefficients. Third, the Haralick and LBP features were extracted from the coefficients. Fourth, relevant features were selected using the ANOVA statistical method. The classication (fifth step) was performed with Radial Basis Function (RBF) networks. The system was tested in 105 prostate images, which were divided into three groups of 35 images: normal, hyperplastic and cancerous. The system performance was evaluated using the area under the ROC curve and resulted in 0.98 for normal versus cancer, 0.95 for hyperplasia versus cancer and 0.96 for normal versus hyperplasia. Our results suggest that texture features can be used as discriminators for stromal tissues prostate images. Furthermore, the system was effective to classify prostate images, specially the hyperplastic class which is the most difficult type in diagnosis and prognosis.

Influence of genotype-environment interaction on the classification of Nellore bulls in Southern Brazil

The aim of this study was to assess the occurrence of genotype-environment interaction, as well as its effects on the magnitude of genetic parameters and the classification of Nellore breeding bulls for the trait adjusted weight at 205 days (W205) on Southern Brazil. The components of (co)variance were estimated by Bayesian inference, using a linear-linear animal model in a bi-trait analysis. The proposed model for the analyses considers as random the direct additive genetic and maternal effects and residual effects, and as fixed effects the contemporary groups, sex, season of birth and weighing, and calving age as covariable (linear and quadratic effects). The a posteriori mean estimates of the direct heritabilities for W205 in the three States varied from 0.24 in Paraná (PR) to 0.34 in Santa Catarina (SC). The estimates of maternal heritability varied from 0.23 in SC and Rio Grande do Sul (RS) to 0.28 in PR. The a posteriori mean distributions of the genetic correlation varied from 0.52 between SC and RS, to 0.84 between PR and RS, suggesting that the best breeding bulls in SC are not the same as in RS.

Frequent ATRX, CIC, FUBP1 and IDH1 mutations refine the classification of malignant gliomas

Mutations in the critical chromatin modifier ATRX and mutations in CIC and FUBP1, which are potent regulators of cell growth, have been discovered in specific subtypes of gliomas, the most common type of primary malignant brain tumors. However, the frequency of these mutations in many subtypes of gliomas, and their association with clinical features of the patients, is poorly understood. Here we analyzed these loci in 363 brain tumors. ATRX is frequently mutated in grade II-III astrocytomas (71%), oligoastrocytomas (68%), and secondary glioblastomas (57%), and ATRX mutations are associated with IDH1 mutations and with an alternative lengthening of telomeres phenotype. CIC and FUBP1 mutations occurred frequently in oligodendrogliomas (46% and 24%, respectively) but rarely in astrocytomas or oligoastrocytomas (<10%). This analysis allowed us to define two highly recurrent genetic signatures in gliomas: IDH1/ATRX (I-A) and IDH1/CIC/FUBP1 (I-CF). Patients with I-CF gliomas had a significantly longer median overall survival (96 months) than patients with I-A gliomas (51 months) and patients with gliomas that did not harbor either signature (13 months). The genetic signatures distinguished clinically distinct groups of oligoastrocytoma patients, which usually present a diagnostic challenge, and were associated with differences in clinical outcome even among individual tumor types. In addition to providing new clues about the genetic alterations underlying gliomas, the results have immediate clinical implications, providing a tripartite genetic signature that can serve as a useful adjunct to conventional glioma classification that may aid in prognosis, treatment selection, and therapeutic trial design.

Classification of thoracolumbar fractures and dislocations

A classification of injuries is necessary in order to develop a common language for treatment indications and outcomes. Several classification systems have been proposed, the most frequently used is the Denis classification. The problem of this classification system is that it is based on an assumption, which is anatomically unidentifiable: the so-called middle column. For this reason, few years ago, a group of spine surgeons has developed a new classification system, which is based on the severity of the injury. The severity is defined by the pathomorphological findings, the prognosis in terms of healing and potential of neurological damage. This classification is based on three major groups: A = isolated anterior column injuries by axial compression, B = disruption of the posterior ligament complex by distraction posteriorly, and group C = corresponding to group B but with rotation. There is an increasing severity from A to C, and within each group, the severity usually increases within the subgroups from .1, .2, .3. All these pathomorphologies are supported by a mechanism of injury, which is responsible for the extent of the injury. The type of injury with its groups and subgroups is able to suggest the treatment modality.

Problems in functioning from the patient perspective using the International Classification of Functioning, Disability and Health (ICF) as a reference

We conducted a qualitative, multicenter study using a focus group design to explore the lived experiences of persons with any kind of primary sleep disorder with regard to functioning and contextual factors using six open-ended questions related to the International Classification of Functioning, Disability and Health (ICF) components. We classified the results using the ICF as a frame of reference. We identified the meaningful concepts within the transcribed data and then linked them to ICF categories according to established linking rules. The six focus groups with 27 participants yielded a total of 6986 relevant concepts, which were linked to a total of 168 different second-level ICF categories. From the patient perspective, the ICF components: (1) Body Functions; (2) Activities & Participation; and (3) Environmental Factors were equally represented; while (4) Body Structures appeared poignantly less frequently. Out of the total number of concepts, 1843 concepts (26%) were assigned to the ICF component Personal Factors, which is not yet classified but could indicate important aspects of resource management and strategy development of those who have a sleep disorder. Therefore, treatment of patients with sleep disorders must not be limited to anatomical and (patho-)physiological changes, but should also consider a more comprehensive view that includes patient's demands, strategies and resources in daily life and the contextual circumstances surrounding the individual.

Time-lapse microscopy and classification of 2D human mesenchymal stem cells based on cell shape picks up myogenic from osteogenic and adipogenic differentiation

Current methods to characterize mesenchymal stem cells (MSCs) are limited to CD marker expression, plastic adherence and their ability to differentiate into adipogenic, osteogenic and chondrogenic precursors. It seems evident that stem cells undergoing differentiation should differ in many aspects, such as morphology and possibly also behaviour; however, such a correlation has not yet been exploited for fate prediction of MSCs. Primary human MSCs from bone marrow were expanded and pelleted to form high-density cultures and were then randomly divided into four groups to differentiate into adipogenic, osteogenic chondrogenic and myogenic progenitor cells. The cells were expanded as heterogeneous and tracked with time-lapse microscopy to record cell shape, using phase-contrast microscopy. The cells were segmented using a custom-made image-processing pipeline. Seven morphological features were extracted for each of the segmented cells. Statistical analysis was performed on the seven-dimensional feature vectors, using a tree-like classification method. Differentiation of cells was monitored with key marker genes and histology. Cells in differentiation media were expressing the key genes for each of the three pathways after 21 days, i.e. adipogenic, osteogenic and chondrogenic, which was also confirmed by histological staining. Time-lapse microscopy data were obtained and contained new evidence that two cell shape features, eccentricity and filopodia (= 'fingers') are highly informative to classify myogenic differentiation from all others. However, no robust classifiers could be identified for the other cell differentiation paths. The results suggest that non-invasive automated time-lapse microscopy could potentially be used to predict the stem cell fate of hMSCs for clinical application, based on morphology for earlier time-points. The classification is challenged by cell density, proliferation and possible unknown donor-specific factors, which affect the performance of morphology-based approaches. Copyright © 2012 John Wiley & Sons, Ltd.

Developing ICF Core Sets for persons with sleep disorders based on the International Classification of Functioning, Disability and Health

BACKGROUND: With the International Classification of Functioning, Disability and Health (ICF), we can now rely on a globally agreed-upon framework and system for classifying the typical spectrum of problems in the functioning of persons given the environmental context in which they live. ICF Core Sets are subgroups of ICF items selected to capture those aspects of functioning that are most likely to be affected by sleep disorders. OBJECTIVE: The objective of this paper is to outline the developmental process for the ICF Core Sets for Sleep. METHODS: The ICF Core Sets for Sleep will be defined at an ICF Core Sets Consensus Conference, which will integrate evidence from preliminary studies, namely (a) a systematic literature review regarding the outcomes used in clinical trials and observational studies, (b) focus groups with people in different regions of the world who have sleep disorders, (c) an expert survey with the involvement of international clinical experts, and (d) a cross-sectional study of people with sleep disorders in different regions of the world. CONCLUSION: The ICF Core Sets for Sleep are being designed with the goal of providing useful standards for research, clinical practice and teaching. It is hypothesized that the ICF Core Sets for Sleep will stimulate research that leads to an improved understanding of functioning, disability, and health in sleep medicine. It is of further hope that such research will lead to interventions and accommodations that improve the restoration and maintenance of functioning and minimize disability among people with sleep disorders throughout the world.

Multi-parametric classification of Alzheimer's disease and mild cognitive impairment: the impact of quantitative magnetization transfer MR imaging

Multi-parametric and quantitative magnetic resonance imaging (MRI) techniques have come into the focus of interest, both as a research and diagnostic modality for the evaluation of patients suffering from mild cognitive decline and overt dementia. In this study we address the question, if disease related quantitative magnetization transfer effects (qMT) within the intra- and extracellular matrices of the hippocampus may aid in the differentiation between clinically diagnosed patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI) and healthy controls. We evaluated 22 patients with AD (n=12) and MCI (n=10) and 22 healthy elderly (n=12) and younger (n=10) controls with multi-parametric MRI. Neuropsychological testing was performed in patients and elderly controls (n=34). In order to quantify the qMT effects, the absorption spectrum was sampled at relevant off-resonance frequencies. The qMT-parameters were calculated according to a two-pool spin-bath model including the T1- and T2 relaxation parameters of the free pool, determined in separate experiments. Histograms (fixed bin-size) of the normalized qMT-parameter values (z-scores) within the anterior and posterior hippocampus (hippocampal head and body) were subjected to a fuzzy-c-means classification algorithm with downstreamed PCA projection. The within-cluster sums of point-to-centroid distances were used to examine the effects of qMT- and diffusion anisotropy parameters on the discrimination of healthy volunteers, patients with Alzheimer and MCIs. The qMT-parameters T2(r) (T2 of the restricted pool) and F (fractional pool size) differentiated between the three groups (control, MCI and AD) in the anterior hippocampus. In our cohort, the MT ratio, as proposed in previous reports, did not differentiate between MCI and AD or healthy controls and MCI, but between healthy controls and AD.