Effects of anxiety on visuospatial pattern discrimination and decision-making processes: what can we learn from brain dynamics ?

Detection and discrimination of visuospatial input involve at least extracting, selecting and encoding relevant information and decision-making processes allowing selecting a response. These two operations are altered, respectively, by attentional mechanisms that change discrimination capacities, and by beliefs concerning the likelihood of uncertain events. Information processing is tuned by the attentional level that acts like a filter on perception, while decision-making processes are weighed by subjective probability of risk. In addition, it has been shown that anxiety could affect the detection of unexpected events through the modification of the level of arousal. Consequently, purpose of this study concerns whether and how decision-making and brain dynamics are affected by anxiety. To investigate these questions, the performance of women with either a high (12) or a low (12) STAI-T (State-Trait Anxiety Inventory, Spielberger, 1983) was examined in a decision-making visuospatial task where subjects have to recognize a target visual pattern from non-target patterns. The target pattern was a schematic image of furniture arranged in such a way as to give the impression of a living room. Non-target patterns were created by either the compression or the dilatation of the distances between objects. Target and non-target patterns were always presented in the same configuration. Preliminary behavioral results show no group difference in reaction time. In addition, visuo-spatial abilities were analyzed trough the signal detection theory for quantifying perceptual decisions in the presence of uncertainty (Green and Swets, 1966). This theory treats detection of a stimulus as a decision-making process determined by the nature of the stimulus and cognitive factors. Astonishingly, no difference in d' (corresponding to the distance between means of the distributions) and c (corresponds to the likelihood ratio) indexes was observed. Comparison of Event-related potentials (ERP) reveals that brain dynamics differ according to anxiety. It shows differences in component latencies, particularly a delay in anxious subjects over posterior electrode sites. However, these differences are compensated during later components by shorter latencies in anxious subjects compared to non-anxious one. These inverted effects seem indicate that the absence of difference in reaction time rely on a compensation of attentional level that tunes cortical activation in anxious subjects, but they have to hammer away to maintain performance.

Linkages of dietary patterns, international trade and land use: the case of olive oil in the European Union

Within only two decades olive oil developed from a niche product which could hardly be found in food stores outside the producing regions towards an integrated component in the diets of industrial countries. This paper discusses the impacts of the promotion of the “healthy Mediterranean diet” on land use and agro-ecosystems in the producing countries. It examines the dynamics of olive oil production, trade and consumption in the EU15 in the period 1972 to 2003 and the links between dietary patterns, trade and land use. It analyses the underlying socio-economic driving forces behind the increasing spatial disconnect between production and consumption of olive oil in the EU15 and in particular in Spain, the world largest producer during the last three decades. In the observed period olive oil consumption increased 16 fold in the non-producing EU15 countries. In the geographically limited producing regions like Spain, the 5 fold increase in export production was associated with the rapid industrialization of olive production, the conversion of vast Mediterranean landscapes to olive monocultures and a range of environmental pressures. High amounts of subsidies of the European Common Agricultural Policy and feedback loops within production and consumption systems were driving the transformation of the olive oil system. Our analysis indicates the process of change was not immediately driven by increases in demand for olive oil in non-producing countries, but rather by the institutional setting of the European Union and by concerted political interventions.

Head motion detection using FID navigators.

This work explores a concept for motion detection in brain MR examinations using high channel-count RF coil arrays. It applies ultrashort (<100 μsec) free induction decay signals, making use of the knowledge that motion induces variations in these signals when compared to a reference free induction decay signal. As a proof-of-concept, the method was implemented in a standard structural MRI sequence. The stability of the free induction decay-signal was verified in phantom experiments. Human experiments demonstrated that the observed variations in the navigator data provide a sensitive measure for detection of relevant and common subject motion patterns. The proposed methodology provides a means to monitor subject motion throughout a MRI scan while causing little or no impact on the sequence timing and image contrast. It could hence complement available motion detection and correction methods, thus further reducing motion sensitivity in MR applications.

Conservation of complex knotting and slipknotting patterns in proteins.

While analyzing all available protein structures for the presence of knots and slipknots, we detected a strict conservation of complex knotting patterns within and between several protein families despite their large sequence divergence. Because protein folding pathways leading to knotted native protein structures are slower and less efficient than those leading to unknotted proteins with similar size and sequence, the strict conservation of the knotting patterns indicates an important physiological role of knots and slipknots in these proteins. Although little is known about the functional role of knots, recent studies have demonstrated a protein-stabilizing ability of knots and slipknots. Some of the conserved knotting patterns occur in proteins forming transmembrane channels where the slipknot loop seems to strap together the transmembrane helices forming the channel.

A simplified method for sample collection and DNA isolation for polymerase chain reaction detection of Trypanosoma rangeli and Trypanosoma cruzi in triatomine vectors

Due to the overlapping distribution of Trypanosoma rangeli and T. cruzi in Central and South America, sharing several reservoirs and triatomine vectors, we herein describe a simple method to collect triatomine feces and hemolymph in filter paper for further detection and specific characterization of these two trypanosomes. Experimentally infected triatomines feces and hemolymph were collected in filter paper and specific detection of T. rangeli or T. cruzi DNA by polymerase chain reaction was achieved. This simple DNA collection method allows sample collection in the field and further specific trypanosome detection and characterization in the laboratory.

Meta-analysis based SVM classification enables accurate detection of Alzheimer's disease across different clinical centers using FDG-PET and MRI.

The application of support vector machine classification (SVM) to combined information from magnetic resonance imaging (MRI) and [F18]fluorodeoxyglucose positron emission tomography (FDG-PET) has been shown to improve detection and differentiation of Alzheimer's disease dementia (AD) and frontotemporal lobar degeneration. To validate this approach for the most frequent dementia syndrome AD, and to test its applicability to multicenter data, we randomly extracted FDG-PET and MRI data of 28 AD patients and 28 healthy control subjects from the database provided by the Alzheimer's Disease Neuroimaging Initiative (ADNI) and compared them to data of 21 patients with AD and 13 control subjects from our own Leipzig cohort. SVM classification using combined volume-of-interest information from FDG-PET and MRI based on comprehensive quantitative meta-analyses investigating dementia syndromes revealed a higher discrimination accuracy in comparison to single modality classification. For the ADNI dataset accuracy rates of up to 88% and for the Leipzig cohort of up to 100% were obtained. Classifiers trained on the ADNI data discriminated the Leipzig cohorts with an accuracy of 91%. In conclusion, our results suggest SVM classification based on quantitative meta-analyses of multicenter data as a valid method for individual AD diagnosis. Furthermore, combining imaging information from MRI and FDG-PET might substantially improve the accuracy of AD diagnosis.

Virulence markers and antimicrobial susceptibility of bacteria of the Bacteroides fragilis group isolated from stool of children with diarrhea in São Paulo, Brazil

Bacteroides fragilis has been isolated from several human and non-human monomicrobial and mixed infections. In this study, some virulence markers and the antimicrobial susceptibility of bacteria of the B. fragilis group isolated from children's stools were evaluated. All the 64 isolates showed the following characteristics: capsulated, beta-hemolytic, hydrophilic, and serum-resistant. Only, 24 (37.5%) strains were resistant at 60ºC, for 30 min, and among them, 12 (18.75%) were resistant at 60ºC, for 60 min. Also, none strain was resistant at 100ºC. Four strains were able to hemagglutinate erythrocytes and D-mannose, D-galactose, D-arabinose, and D-xylose inhibited hemagglutination in 2 B. fragilis strains (p76a, p76b). The hemagglutination in the strain B. uniformis p3-2 was inhibited by D-xylose and D-galactose. The bft gene detection and the enterotoxin production were observed only in 13 EF-enterotoxigenic species. Fragilysin activity was confirmed on HT-29 cells. The antimicrobial determination confirmed that both imipenem and metronidazole were efficient against B. fragilis species; all the strains were resistant to lead and nickel. Plasmids of 2.9, 4.4, 4.8, and 8.9 kb were observed in 6 tested strains. These results show the values of the species identification from clinical infections, as well as of the periodic evaluation of the resistance patterns of the B. fragilis group at Brazilian medical institutions.

Detection of human herpesvirus 6 and 7 DNA in saliva from healthy adults from Rio de Janeiro, Brazil

In this study, we aimed to evaluate virus shedding in the saliva of healthy adults from the metropolitan region of the city of Rio de Janeiro, Brazil, in order to verify the prevalence of both human herpesviruses 6 and 7 (HHV-6, HHV-7). The studied group comprised 182 healthy individuals at Pedro Ernesto University Hospital, who were being seen for annual odontologic revisions. Saliva specimens were subjected to a multiplex polymerase chain reaction (PCR) to detect the presence of HHV-6A, HHV-6B and HHV-7. The total Roseolovirus DNA prevalence was 22.4%. The PCR detected a HHV-6 prevalence of 9.8%, with HHV-6A detected in 7.1% of the samples and HHV-6B in 2.7%. HHV-7 DNA was revealed in 12.6% of the studied cases. Multiple infections caused by HHV-6A and 7 were found in 2.1% of the samples. No statistical differences were observed regarding age, but for HHV-7 infection, an upward trend was observed in female patients. Compared to studies from other countries, low prevalence rates of herpesvirus DNA were detected in saliva from the healthy individuals in our sample. PCR methodology thus proved to be a useful tool for Roseolovirus detection and it is important to consider possible geographic and populations differences that could explain the comparatively low prevalence rates described here.

Detection of erythropoiesis-stimulating agents in human anti-doping control: past, present and future.

Stimulation of erythropoiesis is one of the most efficient ways of doping. This type of doping is advantageous for aerobic physical exercise and of particular interest to endurance athletes. Erythropoiesis, which takes place in bone marrow, is under the control of EPO, a hormone secreted primarily by the kidneys when the arterial oxygen tension decreases. In certain pathological disorders, such as chronic renal failure, the production of EPO is insufficient and results in anemia. The pharmaceutical industry has, thus, been very interested in developing drugs that stimulate erythropoiesis. With this aim, various strategies have been, and continue to be, envisaged, giving rise to an expanding range of drugs that are good candidates for doping. Anti-doping control has had to deal with this situation by developing appropriate methods for their detection. This article presents an overview of both the drugs and the corresponding methods of detection, and thus follows a roughly chronological order.

Early pattern recognition in severe perinatal asphyxia: a prospective MRI study.

On the basis of MRI examinations in 88 neonates and infants with perinatal asphyxia, we defined 6 different patterns on T2-weighted images: pattern A--scattered hyperintensity of both hemispheres of the telencephalon with blurred border zones between cortex and white matter, indicating diffuse brain injury; pattern B--parasagittal hyperintensity extending into the corona radiata, corresponding to the watershed zones; pattern C--hyper- and hypointense lesions in thalamus and basal ganglia, which relate to haemorrhagic necrosis or iron deposition in these areas; pattern D--periventricular hyperintensity, mainly along the lateral ventricles, i.e. periventricular leukomalacia (PVL), originating from the matrix zone; pattern E--small multifocal lesions varying from hyper--to hypointense, interpreted as necrosis and haemorrhage; pattern F--periventricular centrifugal hypointense stripes in the centrum semiovale and deep white matter of the frontal and occipital lobes. Contrast was effectively inverted on T1-weighted images. Patterns A, B and C were found in 17%, 25% and 37% of patients, and patterns D, E and F in 19%, 17% and 35%, respectively. In 49 patients a combination of patterns was observed, but 30% of the initial images were normal. At follow-up, persistent abnormalities were seen in all children with patterns A and D, but in only 52% of those with pattern C. Myelination was retarded most often in patients with diffuse brain injury and PVL (patterns A and D).

Frame detection over the semantic web

In the past, research in ontology learning from text has mainly focused on entity recognition, taxonomy induction and relation extraction. In this work we approach a challenging research issue: detecting semantic frames from texts and using them to encode web ontologies. We exploit a new generation Natural Language Processing technology for frame detection, and we enrich the frames acquired so far with argument restrictions provided by a super-sense tagger and domain specializations. The results are encoded according to a Linguistic MetaModel, which allows a complete translation of lexical resources and data acquired from text, enabling custom transformations of the enriched frames into modular ontology components.

Recognition judgments and the performance of the recognition heuristic depend on the size of the reference class

In a series of three experiments, participants made inferences about which one of a pair of two objects scored higher on a criterion. The first experiment was designed to contrast the prediction of Probabilistic Mental Model theory (Gigerenzer, Hoffrage, & Kleinbölting, 1991) concerning sampling procedure with the hard-easy effect. The experiment failed to support the theory's prediction that a particular pair of randomly sampled item sets would differ in percentage correct; but the observation that German participants performed practically as well on comparisons between U.S. cities (many of which they did not even recognize) than on comparisons between German cities (about which they knew much more) ultimately led to the formulation of the recognition heuristic. Experiment 2 was a second, this time successful, attempt to unconfound item difficulty and sampling procedure. In Experiment 3, participants' knowledge and recognition of each city was elicited, and how often this could be used to make an inference was manipulated. Choices were consistent with the recognition heuristic in about 80% of the cases when it discriminated and people had no additional knowledge about the recognized city (and in about 90% when they had such knowledge). The frequency with which the heuristic could be used affected the percentage correct, mean confidence, and overconfidence as predicted. The size of the reference class, which was also manipulated, modified these effects in meaningful and theoretically important ways.

Immunogenetics of invasive aspergillosis.

Invasive aspergillosis is one of the most important infections in hematopoietic stem cell transplant recipients, with an incidence rate of 5-15% and an associated mortality of 30-60%. It remains unclear why certain patients develop invasive aspergillosis while others, undergoing identical transplant regimen and similar post transplant immunosuppression, do not. Over the last decade, pattern recognition receptors such as Toll-like receptors (TLRs) and the C-type lectin receptors (CLRs) have emerged as critical components of the innate immune system. By detecting specific molecular patterns from invading microbes and initiating inflammatory and subsequent adaptive immune responses, pattern recognition receptors are strategically located at the molecular interface of hosts and pathogens. Polymorphisms in pattern recognition receptors and downstream signaling molecules have been associated with increased or decreased susceptibility to infections, suggesting that their detection may have an increasing impact on the treatment and prevention of infectious diseases in the coming years. Infectious risk stratification may be particularly relevant for patients with hematologic malignancies, because of the high prevalence and severity of infections in this population. This review summarizes the innate immune mechanisms involved in Aspergillus fumigatus detection and the role of host genetic polymorphisms in susceptibility to invasive aspergillosis.

Population-based registration of phenotypic anatomic and familial data for melanoma: results from a Swiss multicentric study

CONTEXT AND OBJECTIVES: A multicentric study was set up to assess the feasibility for Swiss cancer registries of actively retrieving 3 additional variables of epidemiological and a etiological relevance for melanoma, and of potential use for the evaluation of prevention campaigns. MATERIAL AND METHODS: The skin type, family history of melanoma and precise anatomical site were retrieved for melanoma cases registered in 5 Swiss cantons (Neuchâtel, St-Gall and Appenzell, Vaud and Wallis) over 3 to 6 consecutive years (1995-2002). Data were obtained via a short questionnaire administered by the physicians - mostly dermatologists - who originally excised the lesions. As the detailed body site was routinely collected in Ticino, data from this Cancer Registry were included in the body site analysis. Relative melanoma density (RMD) was computed by the ratio of observed to expected numbers of melanomas allowing for body site surface areas, and further adjusted for site-specific melanocyte density. RESULTS: Of the 1,645 questionnaires sent, 1,420 (86.3%) were returned. The detailed cutaneous site and skin type were reliably obtained for 84.7% and 78.7% of questionnaires, and family history was known in 76% of instances. Prevalence of sun-sensitive subjects and patients with melanoma affected first-degree relatives, two target groups for early detection and surveillance campaigns were 54.1% and 3.4%, respectively. After translation into the 4th digit of the International Classification of Diseases for Oncology, the anatomical site codes from printed (original information) and pictorial support (body chart from the questionnaire) concurred for 94.6% of lesions. Discrepancies occurred mostly for lesions on the upper, outer part of the shoulder for which the clinician's textual description was "shoulder blade". This differential misclassification suggests under-estimation by about 10% of melanomas of the upper limbs and an over-estimation of 5% for truncal melanomas. Sites of highest melanoma risk were the face, the shoulder and the upper arm for sexes, the back for men and the leg for women. Three major features of this series were: (1) an unexpectedly high RMD for the face in women (6.2 vs 4.2 in men), (2) the absence of a male predominance for melanomas on the ears, and (3) for the upper limbs, a steady gradient of increasing melanoma density with increasing proximity to the trunk, regardless of sex. DISCUSSION AND CONCLUSION: The feasibility of retrieving the skin type, the precise anatomical location and family history of melanoma in a reliable manner was demonstrated thanks to the collaboration of Swiss dermatologists. Use of a schematic body drawing improves the quality of the anatomical site data and facilitate the reporting task of doctors. Age and sex patterns of RMD paralleled general indicators of sun exposure and behaviour, except for the hand (RMD=0.2). These Swiss results support some site or sun exposure specificity in the aetiology of melanoma.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.