Admissible monetary aggregates for the Euro area

We use the Fleissig and Whitney (2003) weak separability test to determine admissible levels of monetary aggregation for the Euro area. We find that the Euro area monetary assets in M2 and M3 are weakly separable and construct admissible Divisia monetary aggregates for these assets. We evaluate the Divisia aggregates as indicator variables, building on Nelson (2002), Reimers (2002), and Stracca (2004). Specifically, we show that real growth of the admissible Divisia aggregates enter the Euro area IS curve positively and significantly for the period from 1980 to 2005. Out of sample, we show that Divisia M2 and M3 appear to contain useful information for forecasting Euro area inflation.

Antidiabetic properties of zinc-alpha2-glycoprotein in ob/ob mice

Zinc-alpha(2)-glycoprotein (ZAG) is an adipokine associated with fat loss in cancer cachexia. The purpose of this study was to evaluate the ability of recombinant human ZAG to attenuate type 2 diabetes in the ob/ob mouse model. ZAG (50 microg daily, iv) induced a progressive loss of body weight (3.5 g in 5 d), without an effect on food or water intake but with a 0.4 C rise in body temperature, suggesting an increased energy expenditure. Despite an increased plasma glycerol, indicative of increased lipolysis, levels of glucose, triglycerides, and nonesterified fatty acids were decreased by 17, 25, and 62%, respectively, due to an increased use of both glucose and lipids by muscle and brown adipose tissue. The weight of the latter increased 2-fold, and there was increased expression of uncoupling proteins-1 and -3. Plasma insulin levels were reduced by 36%, whereas pancreatic insulin was increased 4-fold, and there was a 53% decrease in the total area under the glucose curve in the glucose tolerance test and reduced insulin requirement. There was an increase in skeletal muscle mass due to an increase in protein synthesis and a decrease in protein degradation. These results suggest that ZAG may potentially be effective in the treatment of type 2 diabetes.

Development of a near activity visual questionnaire to assess accommodating intraocular lenses

Purpose: To develop a questionnaire that subjectively assesses near visual function in patients with 'accommodating' intraocular lenses (IOLs). Methods: A literature search of existing vision-related quality-of-life instruments identified all questions relating to near visual tasks. Questions were combined if repeated in multiple instruments. Further relevant questions were added and item interpretation confirmed through multidisciplinary consultation and focus groups. A preliminary 19-item questionnaire was presented to 22 subjects at their 4-week visit post first eye phacoemulsification with 'accommodative' IOL implantation, and again 6 and 12 weeks post-operatively. Rasch Analysis, Frequency of Endorsement, and tests of normality (skew and kurtosis) were used to reduce the instrument. Cronbach's alpha and test-retest reliability (intraclass correlation coefficient, ICC) were determined for the final questionnaire. Construct validity was obtained by Pearson's product moment correlation (PPMC) of questionnaire scores to reading acuity (RA) and to Critical Print Size (CPS) reading speed. Criterion validity was obtained by receiver operating characteristic (ROC) curve analysis and dimensionality of the questionnaire was assessed by factor analysis. Results: Rasch Analysis eliminated nine items due to poor fit statistics. The final items have good separation (2.55), internal consistency (Cronbach's α = 0.97) and test-retest reliability (ICC = 0.66). PPMC of questionnaire scores with RA was 0.33, and with CPS reading speed was 0.08. Area under the ROC curve was 0.88 and Factor Analysis revealed one principal factor. Conclusion: The pilot data indicates the questionnaire to be internally consistent, reliable and a valid instrument that could be useful for assessing near visual function in patients with 'accommodating' IOLS. The questionnaire will now be expanded to include other types of presbyopic correction. © 2007 British Contact Lens Association.

A tree-based decision model to support prediction of the severity of asthma exacerbations in children

This paper describes the development of a tree-based decision model to predict the severity of pediatric asthma exacerbations in the emergency department (ED) at 2 h following triage. The model was constructed from retrospective patient data abstracted from the ED charts. The original data was preprocessed to eliminate questionable patient records and to normalize values of age-dependent clinical attributes. The model uses attributes routinely collected in the ED and provides predictions even for incomplete observations. Its performance was verified on independent validating data (split-sample validation) where it demonstrated AUC (area under ROC curve) of 0.83, sensitivity of 84%, specificity of 71% and the Brier score of 0.18. The model is intended to supplement an asthma clinical practice guideline, however, it can be also used as a stand-alone decision tool.

Role of β-adrenergic receptors in the oral activity of zinc-α2-glycoprotein (ZAG)

Zinc-a2-glycoprotein (ZAG) is an adipokine with the potential as a therapeutic agent in the treatment of obesity and type 2 diabetes. In this study we show that human ZAG, which is a 41-kDa protein, when administered to ob/ob mice at 50 µg/d-1 orally in the drinking water produced a progressive loss of body weight (5 g after 8 d treatment), together with a 0.5 C increase in rectal temperature and a 40% reduction in urinary excretion of glucose. There was also a 33% reduction in the area under the curve during an oral glucose tolerance test and an increased sensitivity to insulin. These results were similar to those after iv administration of ZAG. However, tryptic digestion was shown to inactivate ZAG. There was no evidence of human ZAG in the serum but a 2-fold elevation of murine ZAG, which was also observed in target tissues such as white adipose tissue. To determine whether the effect was due to interaction of the human ZAG with the ß-adrenergic (ß-AR) in the gastrointestinal tract before digestion, ZAG was coadministered to ob/ob mice together with propanolol (40 mg/kg-1), a nonspecific ß-AR antagonist. The effect of ZAG on body weight, rectal temperature, urinary glucose excretion, improvement in glucose disposal, and increased insulin sensitivity were attenuated by propanolol, as was the increase in murine ZAG in the serum. These results suggest that oral administration of ZAG increases serum levels through interaction with a ß-AR in the upper gastrointestinal tract, and gene expression studies showed this to be in the esophagus.

Admissible monetary aggregates for the euro area

We use the Fleissig and Whitney [Fleissig, A.R., Whitney, G.A., 2003. A new PC-based test for Varian's weak separability conditions. Journal of Business and Economics Statistics 21 (1), 133–144] weak separability test to determine admissible levels of monetary aggregation for the Euro area. We find that the Euro area monetary assets in M2 and M3 are weakly separable and construct admissible Divisia monetary aggregates for these assets. We show that real growth of the admissible Divisia aggregates enters the Euro area IS curve positively and significantly for the period from 1980 to 2005. Out of sample, we show that Divisia M2 and M3 appear to contain useful information for forecasting Euro area inflation.

The relationship between alexithymia and salivary cortisol levels in somatoform disorders

The purpose of this study was to investigate cortisol levels as a function of the hypothalamic-pituitary-adrenal axis (HPA) in relation to alexithymia in patients with somatoform disorders (SFD). Diurnal salivary cortisol was sampled in 32 patients with SFD who also underwent a psychiatric examination and filled in questionnaires (Toronto Alexithymia Scale, TAS scale; Screening for Somatoform Symptoms, SOMS scale; Hamilton Depression Scale, HAMD). The mean TAS total score in the sample was 55.69.6, 32% of patients being classified as alexithymic on the basis of their TAS scores. Depression scores were moderate (HAMD=13.2, Beck Depression Inventory, BDI=16.5). The patients' alexithymia scores (TAS scale Difficulty identifying feelings) correlated significantly positively with their somatization scale scores (Symptom Checklist-90 Revised, SCL-90-R); r=0.3438 (P0.05) and their scores on the Global Severity Index (GSI) on the SCL-90-R; r=0.781 (P0.01). Regression analysis was performed with cortisol variables as the dependent variables. Cortisol levels [measured by the area under the curve-ground (AUC-G), area under the curve-increase (AUC-I) and morning cortisol (MCS)] were best predicted in a multiple linear regression model by lower depressive scores (HAMD) and more psychopathological symptoms (SCL-90-R). No significant correlations were found between the patients' alexithymia scores (TAS) and cortisol levels. The healthy control group (n=25) demonstrated significantly higher cortisol levels than did the patients with SFD; in both tests P0.001 for AUC-G and AUC-I. However, the two groups did not differ in terms of their mean morning cortisol levels (P0.05). The results suggest that pre-existing hypocortisolism might possibly be associated with SFD.

Reduced postprandial proinsulinaemia and 32-33 split proinsulinaemia after a mixed meal in type 2 diabetic patients following sensitization to insulin with pioglitazone

Objective: Reduced insulin sensitivity associated with fasting hyperproinsulinaemia is common in type 2 diabetes. Proinsulinaemia is an established independent cardiovascular risk factor. The objective was to investigate fasting and postprandial release of insulin, proinsulin (PI) and 32-33 split proinsulin (SPI) before and after sensitization to insulin with pioglitazone compared to a group treated with glibenclamide. Design and patients: A randomized double-blind placebo-controlled trial. Twenty-two type 2 diabetic patients were recruited along with 10 normal subjects. After 4 weeks washout, patients received a mixed meal and were assigned to receive pioglitazone or glibenclamide for 20 weeks, after which patients received another identical test meal. The treatment regimes were designed to maintain glycaemic control (HbA1c) at pretreatment levels so that ß-cells received an equivalent glycaemic stimulus for both test meals. Measurements: Plasma insulin, PI, SPI and glucose concentrations were measured over an 8-h postprandial period. The output of PI and SPI was measured as the integrated postprandial response (area under the curve, AUC). Results: Pioglitazone treatment resulted in a significant reduction in fasting levels of PI and SPI compared to those of the controls. Postprandially, pioglitazone treatment had no effect on the insulin AUC response to the meal but significantly reduced the PI and SPI AUCs. Glibenclamide increased fasting insulin and the postprandial insulin AUC but had no effect on the PI and SPI AUCs. Conclusions: Sensitization to insulin with pioglitazone reduces the amount of insulin precursor species present in fasting and postprandially and may reduce cardiovascular risk. © 2007 The Authors.

Regularity analysis of nocturnal oximetry recordings to assist in the diagnosis of sleep apnoea syndrome

The relationship between sleep apnoea–hypopnoea syndrome (SAHS) severity and the regularity of nocturnal oxygen saturation (SaO2) recordings was analysed. Three different methods were proposed to quantify regularity: approximate entropy (AEn), sample entropy (SEn) and kernel entropy (KEn). A total of 240 subjects suspected of suffering from SAHS took part in the study. They were randomly divided into a training set (96 subjects) and a test set (144 subjects) for the adjustment and assessment of the proposed methods, respectively. According to the measurements provided by AEn, SEn and KEn, higher irregularity of oximetry signals is associated with SAHS-positive patients. Receiver operating characteristic (ROC) and Pearson correlation analyses showed that KEn was the most reliable predictor of SAHS. It provided an area under the ROC curve of 0.91 in two-class classification of subjects as SAHS-negative or SAHS-positive. Moreover, KEn measurements from oximetry data exhibited a linear dependence on the apnoea–hypopnoea index, as shown by a correlation coefficient of 0.87. Therefore, these measurements could be used for the development of simplified diagnostic techniques in order to reduce the demand for polysomnographies. Furthermore, KEn represents a convincing alternative to AEn and SEn for the diagnostic analysis of noisy biomedical signals.

Optimising the diagnostic performance of the Geriatric Depression Scale

The aim of this work is to empirically generate a shortened version of the Geriatric Depression Scale (GDS), with the intention of maximising the diagnostic performance in the detection of depression compared with previously GDS validated versions, while optimizing the size of the instrument. A total of 233 individuals (128 from a Day Hospital, 105 randomly selected from the community) aged 60 or over completed the GDS and other measures. The 30 GDS items were entered in the Day Hospital sample as independent variables in a stepwise logistic regression analysis predicting diagnosis of Major Depression. A final solution of 10 items was retained, which correctly classified 97.4% of cases. The diagnostic performance of these 10 GDS items was analysed in the random sample with a receiver operating characteristic (ROC) curve. Sensitivity (100%), specificity (97.2%), positive (81.8%) and negative (100%) predictive power, and the area under the curve (0.994) were comparable with values for GDS-30 and higher compared with GDS-15, GDS-10 and GDS-5. In addition, the new scale proposed had excellent fit when testing its unidimensionality with CFA for categorical outcomes (e.g., CFI=0.99). The 10-item version of the GDS proposed here, the GDS-R, seems to retain the diagnostic performance for detecting depression in older adults of the GDS-30 items, while increasing the sensitivity and predictive values relative to other shortened versions.

Application of support vector machines on the basis of the first Hungarian bankruptcy model

In our study we rely on a data mining procedure known as support vector machine (SVM) on the database of the first Hungarian bankruptcy model. The models constructed are then contrasted with the results of earlier bankruptcy models with the use of classification accuracy and the area under the ROC curve. In using the SVM technique, in addition to conventional kernel functions, we also examine the possibilities of applying the ANOVA kernel function and take a detailed look at data preparation tasks recommended in using the SVM method (handling of outliers). The results of the models assembled suggest that a significant improvement of classification accuracy can be achieved on the database of the first Hungarian bankruptcy model when using the SVM method as opposed to neural networks.

Off-line and on-line affective recognition of a computer user through a biosignal processing approach

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. ^ In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment ("relaxation" vs. "stress") are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. ^ For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). ^ In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the "relaxation" vs. "stress" states.^

Use of Hemoglobin A1C to Detect Haitian-Americans with Undiagnosed Type 2 Diabetes

OBJECTIVE: To evaluate the validity of hemoglobin A1C (A1C) as a diagnostic tool for type 2 diabetes and to determine the most appropriate A1C cutoff point for diagnosis in a sample of Haitian-Americans. SUBJECTS AND METHODS: Subjects (n = 128) were recruited from Miami-Dade and Broward counties, FL. Receiver operating characteristics (ROC) analysis was run in order to measure sensitivity and specificity of A1C for detecting diabetes at different cutoff points. RESULTS: The area under the ROC curve was 0.86 using fasting plasma glucose ≥ 7.0 mmol/L as the gold standard. An A1C cutoff point of 6.26% had sensitivity of 80% and specificity of 74%, whereas an A1C cutoff point of 6.50% (recommended by the American Diabetes Association – ADA) had sensitivity of 73% and specificity of 89%. CONCLUSIONS: A1C is a reliable alternative to fasting plasma glucose in detecting diabetes in this sample of Haitian-Americans. A cutoff point of 6.26% was the optimum value to detect type 2 diabetes.

Reação de genótipos de cafeeiro à Hemileia vastatrix e à Cercospora coffeicola

Coffee plants were introduced in Brazil in the Northern State of Para around 1727. Two major diseases have affected coffee trees in the country. One is rust, caused by fungus Hemileia vastatrix and accountable for production losses up to 50%. The other one is Cercospora leaf spot, caused by fungus Cercospora coffeicola endemic to all Brazilian coffee farms and, therefore, economically critical due to production losses both in the plant nursery and in the field. Availability of resistant varieties has been a constant challenge for breeders. Research programs play an important role in the search for new resistant and/or tolerant genotypes, since over time plants can become susceptible to new, genetically variable races of pathogens. This study aimed to evaluate the incidence and severity of such diseases, the resistance of different coffee genotypes to H. vastatrix and C. coffeicola pathogens, as well as the productivity of said genotypes in dense planting system. The experimental design consisted of randomized blocks, with twelve genotypes (treatments) and two replications (blocks). SISVAR® program was used to analyze data and compare them building on Scott-Knott test and Tukey’s test with a probability of 5%. Disease incidence and severity percentage were assessed for both Cercospora leaf spot and rust. Means were used to calculate the area under the disease progress curve (AUDPC) of both diseases. As to rust, the most resistant genotypes were H586-6, IBC 12, and H556-7 H567-6. As to Cercospora leaf spot and productivity, no statistical differences were found across genotypes. The dense planting system did not impair plant development, but favored disease evolution given the microclimate it produces.

Classificação de nódulos pulmonares em imagens tomográficas utilizando redes neurais artificiais em cascata

Lung cancer is the most common of malignant tumors, with 1.59 million new cases worldwide in 2012. Early detection is the main factor to determine the survival of patients affected by this disease. Furthermore, the correct classification is important to define the most appropriate therapeutic approach as well as suggest the prognosis and the clinical disease evolution. Among the exams used to detect lung cancer, computed tomography have been the most indicated. However, CT images are naturally complex and even experts medical are subject to fault detection or classification. In order to assist the detection of malignant tumors, computer-aided diagnosis systems have been developed to aid reduce the amount of false positives biopsies. In this work it was developed an automatic classification system of pulmonary nodules on CT images by using Artificial Neural Networks. Morphological, texture and intensity attributes were extracted from lung nodules cut tomographic images using elliptical regions of interest that they were subsequently segmented by Otsu method. These features were selected through statistical tests that compare populations (T test of Student and U test of Mann-Whitney); from which it originated a ranking. The features after selected, were inserted in Artificial Neural Networks (backpropagation) to compose two types of classification; one to classify nodules in malignant and benign (network 1); and another to classify two types of malignancies (network 2); featuring a cascade classifier. The best networks were associated and its performance was measured by the area under the ROC curve, where the network 1 and network 2 achieved performance equal to 0.901 and 0.892 respectively.