Assessment and reuse of contents in the competence-based educational platform InterMediActor

This paper describes a failure alert system and a methodology for content reuse in a new instructional design system called InterMediActor (IMA). IMA provides an environment for instructional content design, production and reuse, and for students’ evaluation based in content specification through a hierarchical structure of competences. The student assessment process and information extraction process for content reuse are explained.

A step-by-step tutorial to use HierFstat to analyse populations hierarchically structured at multiple levels.

The populations of parasites and infectious agents are most of the time structured in complex hierarchy that lies beyond the classical nested design described by Wright's F-statistics (F(IS), F(ST) and F(IT)). In this note we propose a user-friendly step-by-step notice for using recent software (HierFstat) that computes and test fixation indices for any hierarchical structure. We add some tricks and tips for some special data kind (haploid, single locus), some other procedure (bootstrap over loci) and how to handle crossed factors.

GeneID in "Drosophila"

GeneID is a program to predict genes in anonymous genomic sequences designed with a hierarchical structure. In the first step, splice sites, and start and stop codons are predicted and scored along the sequence using position weight matrices (PWMs). In the second step, exons are built from the sites. Exons are scored as the sum of the scores of the defining sites, plus the log-likelihood ratio of a Markov model for coding DNA. In the last step, from the set of predicted exons, the gene structure is assembled, maximizing the sum of the scores of the assembled exons. In this paper we describe the obtention of PWMs for sites, and the Markov model of coding DNA in Drosophila melanogaster. We also compare other models of coding DNA with the Markov model. Finally, we present and discuss the results obtained when GeneID is used to predict genes in the Adh region. These results show that the accuracy of GeneID predictions compares currently with that of other existing tools but that GeneID is likely to be more efficient in terms of speed and memory usage.

Demographic and geographic vascular risk factor differences in European young adults with ischemic stroke: the 15 cities young stroke study.

BACKGROUND AND PURPOSE: We compared among young patients with ischemic stroke the distribution of vascular risk factors among sex, age groups, and 3 distinct geographic regions in Europe. METHODS: We included patients with first-ever ischemic stroke aged 15 to 49 years from existing hospital- or population-based prospective or consecutive young stroke registries involving 15 cities in 12 countries. Geographic regions were defined as northern (Finland, Norway), central (Austria, Belgium, France, Germany, Hungary, The Netherlands, Switzerland), and southern (Greece, Italy, Turkey) Europe. Hierarchical regression models were used for comparisons. RESULTS: In the study cohort (n=3944), the 3 most frequent risk factors were current smoking (48.7%), dyslipidemia (45.8%), and hypertension (35.9%). Compared with central (n=1868; median age, 43 years) and northern (n=1330; median age, 44 years) European patients, southern Europeans (n=746; median age, 41 years) were younger. No sex difference emerged between the regions, male:female ratio being 0.7 in those aged <34 years and reaching 1.7 in those aged 45 to 49 years. After accounting for confounders, no risk-factor differences emerged at the region level. Compared with females, males were older and they more frequently had dyslipidemia or coronary heart disease, or were smokers, irrespective of region. In both sexes, prevalence of family history of stroke, dyslipidemia, smoking, hypertension, diabetes mellitus, coronary heart disease, peripheral arterial disease, and atrial fibrillation positively correlated with age across all regions. CONCLUSIONS: Primary preventive strategies for ischemic stroke in young adults-having high rate of modifiable risk factors-should be targeted according to sex and age at continental level.

Identification of molecular apocrine breast tumours by microarray analysis.

Previous microarray studies on breast cancer identified multiple tumour classes, of which the most prominent, named luminal and basal, differ in expression of the oestrogen receptor alpha gene (ER). We report here the identification of a group of breast tumours with increased androgen signalling and a 'molecular apocrine' gene expression profile. Tumour samples from 49 patients with large operable or locally advanced breast cancers were tested on Affymetrix U133A gene expression microarrays. Principal components analysis and hierarchical clustering split the tumours into three groups: basal, luminal and a group we call molecular apocrine. All of the molecular apocrine tumours have strong apocrine features on histological examination (P=0.0002). The molecular apocrine group is androgen receptor (AR) positive and contains all of the ER-negative tumours outside the basal group. Kolmogorov-Smirnov testing indicates that oestrogen signalling is most active in the luminal group, and androgen signalling is most active in the molecular apocrine group. ERBB2 amplification is commoner in the molecular apocrine than the other groups. Genes that best split the three groups were identified by Wilcoxon test. Correlation of the average expression profile of these genes in our data with the expression profile of individual tumours in four published breast cancer studies suggest that molecular apocrine tumours represent 8-14% of tumours in these studies. Our data show that it is possible with microarray data to divide mammary tumour cells into three groups based on steroid receptor activity: luminal (ER+ AR+), basal (ER- AR-) and molecular apocrine (ER- AR+).

Sequential estimation of multipath MIMO-OFDM channels

Wireless “MIMO” systems, employing multiple transmit and receive antennas, promise a significant increase of channel capacity, while orthogonal frequency-division multiplexing (OFDM) is attracting a good deal of attention due to its robustness to multipath fading. Thus, the combination of both techniques is an attractive proposition for radio transmission. The goal of this paper is the description and analysis of a new and novel pilot-aided estimator of multipath block-fading channels. Typical models leading to estimation algorithms assume the number of multipath components and delays to be constant (and often known), while their amplitudes are allowed to vary with time. Our estimator is focused instead on the more realistic assumption that the number of channel taps is also unknown and varies with time following a known probabilistic model. The estimation problem arising from these assumptions is solved using Random-Set Theory (RST), whereby one regards the multipath-channel response as a single set-valued random entity.Within this framework, Bayesian recursive equations determine the evolution with time of the channel estimator. Due to the lack of a closed form for the solution of Bayesian equations, a (Rao–Blackwellized) particle filter (RBPF) implementation ofthe channel estimator is advocated. Since the resulting estimator exhibits a complexity which grows exponentially with the number of multipath components, a simplified version is also introduced. Simulation results describing the performance of our channel estimator demonstrate its effectiveness.

Incorporating features of distribution and progression for automatic Makam classification

Automatic classification of makams from symbolic data is a rarely studied topic. In this paper, first a review of an n-gram based approach is presented using various representations of the symbolic data. While a high degree of precision can be obtained, confusion happens mainly for makams using (almost) the same scale and pitch hierarchy but differ in overall melodic progression, seyir. To further improve the system, first n-gram based classification is tested for various sections of the piece to take into account a feature of the seyir that melodic progression starts in a certain region of the scale. In a second test, a hierarchical classification structure is designed which uses n-grams and seyir features in different levels to further improve the system.

Multiple target tracking using random sets

This paper presents several algorithms for joint estimation of the target number and state in a time-varying scenario. Building on the results presented in [1], which considers estimation of the target number only, we assume that not only the target number, but also their state evolution must be estimated. In this context, we extend to this new scenario the Rao-Blackwellization procedure of [1] to compute Bayes recursions, thus defining reduced-complexity solutions for the multi-target set estimator. A performance assessmentis finally given both in terms of Circular Position Error Probability - aimed at evaluating the accuracy of the estimated track - and in terms of Cardinality Error Probability, aimed at evaluating the reliability of the target number estimates.

Restricted gene flow and subpopulation differentiation in Silene dioica

The size of breeding units and the hierarchical population structure of the dioecious perennial herb Silene dioica were investigated on four closely situated island populations in the Skeppsvik Archipelago in northern Sweden. F-statistics analyses of nine polymorphic allozyme loci revealed that plants on single islands are divided into many small breeding units, between 0.2 m2 and 6 m2. Hierarchical analyses showed that levels of differentiation among subpopulations within islands (FPL=0.080) were about twice as high as among islands (FLT=0.048). These results are discussed in the light of what is known about pollen and seed movement in the archipelago.

Identification of cancer stem cells in Ewing's sarcoma.

Cancer stem cells that display tumor-initiating properties have recently been identified in several distinct types of malignancies, holding promise for more effective therapeutic strategies. However, evidence of such cells in sarcomas, which include some of the most aggressive and therapy-resistant tumors, has not been shown to date. Here, we identify and characterize cancer stem cells in Ewing's sarcoma family tumors (ESFT), a highly aggressive pediatric malignancy believed to be of mesenchymal stem cell (MSC) origin. Using magnetic bead cell separation of primary ESFT, we have isolated a subpopulation of CD133+ tumor cells that display the capacity to initiate and sustain tumor growth through serial transplantation in nonobese diabetic/severe combined immunodeficiency mice, re-establishing at each in vivo passage the parental tumor phenotype and hierarchical cell organization. Consistent with the plasticity of MSCs, in vitro differentiation assays showed that the CD133+ cell population retained the ability to differentiate along adipogenic, osteogenic, and chondrogenic lineages. Quantitative real-time PCR analysis of genes implicated in stem cell maintenance revealed that CD133+ ESFT cells express significantly higher levels of OCT4 and NANOG than their CD133- counterparts. Taken together, our observations provide the first identification of ESFT cancer stem cells and demonstration of their MSC properties, a critical step towards a better biological understanding and rational therapeutic targeting of these tumors.

Alliance patterns over the course of short-term dynamic psychotherapy: The shape of productive relationships.

The shape of alliance processes over the course of psychotherapy has already been studied in several process-outcome studies on very brief psychotherapy. The present study applies the shape-of-change methodology to short-term dynamic psychotherapies and complements this method with hierarchical linear modeling. A total of 50 psychotherapies of up to 40 sessions were included. Alliance was measured at the end of each session. The results indicate that a linear progression model is most adequate. Three main patterns were found: stable, linear, and quadratic growth. The linear growth pattern, along with the slope parameter, was related to treatment outcome. This study sheds additional light on alliance process research, underscores the importance of linear alliance progression for outcome, and also fosters a better understanding of its limitations.

An evaluation of new parsimony-based versus parametric inference methods in biogeography: a case study using the globally distributed plant family Sapindaceae

Aim  Recently developed parametric methods in historical biogeography allow researchers to integrate temporal and palaeogeographical information into the reconstruction of biogeographical scenarios, thus overcoming a known bias of parsimony-based approaches. Here, we compare a parametric method, dispersal-extinction-cladogenesis (DEC), against a parsimony-based method, dispersal-vicariance analysis (DIVA), which does not incorporate branch lengths but accounts for phylogenetic uncertainty through a Bayesian empirical approach (Bayes-DIVA). We analyse the benefits and limitations of each method using the cosmopolitan plant family Sapindaceae as a case study.Location  World-wide.Methods  Phylogenetic relationships were estimated by Bayesian inference on a large dataset representing generic diversity within Sapindaceae. Lineage divergence times were estimated by penalized likelihood over a sample of trees from the posterior distribution of the phylogeny to account for dating uncertainty in biogeographical reconstructions. We compared biogeographical scenarios between Bayes-DIVA and two different DEC models: one with no geological constraints and another that employed a stratified palaeogeographical model in which dispersal rates were scaled according to area connectivity across four time slices, reflecting the changing continental configuration over the last 110 million years.Results  Despite differences in the underlying biogeographical model, Bayes-DIVA and DEC inferred similar biogeographical scenarios. The main differences were: (1) in the timing of dispersal events - which in Bayes-DIVA sometimes conflicts with palaeogeographical information, and (2) in the lower frequency of terminal dispersal events inferred by DEC. Uncertainty in divergence time estimations influenced both the inference of ancestral ranges and the decisiveness with which an area can be assigned to a node.Main conclusions  By considering lineage divergence times, the DEC method gives more accurate reconstructions that are in agreement with palaeogeographical evidence. In contrast, Bayes-DIVA showed the highest decisiveness in unequivocally reconstructing ancestral ranges, probably reflecting its ability to integrate phylogenetic uncertainty. Care should be taken in defining the palaeogeographical model in DEC because of the possibility of overestimating the frequency of extinction events, or of inferring ancestral ranges that are outside the extant species ranges, owing to dispersal constraints enforced by the model. The wide-spanning spatial and temporal model proposed here could prove useful for testing large-scale biogeographical patterns in plants.

La quête du consentement éclairé en médecine comme construction sociale [The application of informed consent in medicine as social construction].

The aim of this article is to propose an anthropological point of view about informed consent in medicine. This quest for legitimacy should be read as a relational and social construction. In the heart of clinical complexity we find on one side various techniques employed by the medical community to validate research and to obtain the consent of patients. On the other side patients offer plural and subjective answers due to the doctor patient hierarchical and long relationship. Between constraints and freedoms, informed consent brings to light social relation.

Evaluation of adding a second marker to overcome Staphylococcus aureus spa typing homoplasies.

The utility of sequencing a second highly variable locus in addition to the spa gene (e.g., double-locus sequence typing [DLST]) was investigated to overcome limitations of a Staphylococcus aureus single-locus typing method. Although adding a second locus seemed to increase discriminatory power, it was not sufficient to definitively infer evolutionary relationships within a single multilocus sequence type (ST-5).

Substantial advantage of a combined Bayesian and genotyping approach in testosterone doping tests.

Testosterone abuse is conventionally assessed by the urinary testosterone/epitestosterone (T/E) ratio, levels above 4.0 being considered suspicious. A deletion polymorphism in the gene coding for UGT2B17 is strongly associated with reduced testosterone glucuronide (TG) levels in urine. Many of the individuals devoid of the gene would not reach a T/E ratio of 4.0 after testosterone intake. Future test programs will most likely shift from population based- to individual-based T/E cut-off ratios using Bayesian inference. A longitudinal analysis is dependent on an individual's true negative baseline T/E ratio. The aim was to investigate whether it is possible to increase the sensitivity and specificity of the T/E test by addition of UGT2B17 genotype information in a Bayesian framework. A single intramuscular dose of 500mg testosterone enanthate was given to 55 healthy male volunteers with either two, one or no allele (ins/ins, ins/del or del/del) of the UGT2B17 gene. Urinary excretion of TG and the T/E ratio was measured during 15 days. The Bayesian analysis was conducted to calculate the individual T/E cut-off ratio. When adding the genotype information, the program returned lower individual cut-off ratios in all del/del subjects increasing the sensitivity of the test considerably. It will be difficult, if not impossible, to discriminate between a true negative baseline T/E value and a false negative one without knowledge of the UGT2B17 genotype. UGT2B17 genotype information is crucial, both to decide which initial cut-off ratio to use for an individual, and for increasing the sensitivity of the Bayesian analysis.