Relationship Between Cortisol Levels and Memory Performance may be Modulated by the Presence or Absence of Cognitive Impairment: Evidence from Healthy Elderly, Mild Cognitive Impairment and Alzheimer`s Disease Subjects

An inverted U-shape function between cortisol levels and memory performance has been reported in studies on both young animals and humans. Yet little is known about this relationship in normal aging or in older subjects with cognitive impairment. This issue is particularly significant since increased levels of cortisol have been reported in Alzheimer`s disease (AD). The present study examined the association between cortisol levels and visual memory performance in healthy subjects as well as in individuals presenting mild cognitive impairment (MCI) or AD. Salivary cortisol was measured in 40 healthy elderly subjects, 31 individuals with amnestic MCI, and 40 subjects with mild probable AD. Memory performance was evaluated using the Brief Cognitive Screening Battery. Higher cortisol levels were associated with better memory performance in healthy elderly (p = 0.005), while higher cortisol levels were correlated with poorer memory performance in MCI subjects (p = 0.011). No correlation between cortisol and memory was found in the AD group (p > 0.05). These results suggest that the relationship between cortisol levels and memory performance in the aging process could vary according to the presence or absence of cognitive impairment.

Impact of cancer-related symptom synergisms on health-related quality of life and performance status

To identify the impact of multiple symptoms and their co-occurrence on health-related quality of life (HRQOL) dimensions and performance status (PS), 115 outpatients with cancer, who were not receiving active cancer treatment and were recruited from, a university hospital in Sao Paulo, Brazil completed the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-C30, the Beck Depression Inventory, and the Brief Pain Inventory. Karnofsky Performance Status scores also were completed. Application of TwoStep Cluster analysis resulted in two distinct patient subgroups based on 113 patient experiences with pain, depression, fatigue, insomnia, constipation, lack of appetite, dyspnea, nausea, vomiting, and diarrhea. One group had multiple and severe symptom subgroup and another had Less symptoms and with lower severity. Multiple and severe symptoms had worse PS, role functioning, and physical, emotional, cognitive, social, and overall HRQOL. Multiple and severe symptom subgroup was also six times as likely as lower severity to have poor role functioning;five times more likely to have poor emotional;four times more likely to have poor PS, physical, and overall HRQOL, and three times as likely to have poor cognitive and social HRQOL, independent of gender, age, level of education, and economic condition. Classification and Regression Tree analyses were undertaken to identify which co-occurring symptoms would best determine reduction in HRQOL and PS. Pain and fatigue were identified as indicators of reduction on physical HRQOL and PS. Fatigue and insomnia were associated with reduction in cognitive; depression and pain in social; and fatigue and constipation in role functioning. Only depression was associated with reduction in overall HRQOL. These data demonstrate that there is a synergic effect among distinct cancer symptoms that result in reduction in HRQOL dimensions and PS.

Support vector machines for detecting age-related changes in running kinematics

Age-related changes in running kinematics have been reported in the literature using classical inferential statistics. However, this approach has been hampered by the increased number of biomechanical gait variables reported and subsequently the lack of differences presented in these studies. Data mining techniques have been applied in recent biomedical studies to solve this problem using a more general approach. In the present work, we re-analyzed lower extremity running kinematic data of 17 young and 17 elderly male runners using the Support Vector Machine (SVM) classification approach. In total, 31 kinematic variables were extracted to train the classification algorithm and test the generalized performance. The results revealed different accuracy rates across three different kernel methods adopted in the classifier, with the linear kernel performing the best. A subsequent forward feature selection algorithm demonstrated that with only six features, the linear kernel SVM achieved 100% classification performance rate, showing that these features provided powerful combined information to distinguish age groups. The results of the present work demonstrate potential in applying this approach to improve knowledge about the age-related differences in running gait biomechanics and encourages the use of the SVM in other clinical contexts. (C) 2010 Elsevier Ltd. All rights reserved.

Post-concurrent exercise hemodynamics and cardiac autonomic modulation

Concurrent training is recommended for health improvement, but its acute effects on cardiovascular function are not well established. This study analyzed hemodynamics and autonomic modulation after a single session of aerobic (A), resistance (R), and concurrent (A + R) exercises. Twenty healthy subjects randomly underwent four sessions: control (C:30 min of rest), aerobic (A:30 min, cycle ergometer, 75% of VO(2) peak), resistance (R:6 exercises, 3 sets, 20 repetitions, 50% of 1 RM), and concurrent (AR: A + R). Before and after the interventions, blood pressure (BP), heart rate (HR), cardiac output (CO), and HR variability were measured. Systolic BP decreased after all the exercises, and the greatest decreases were observed after the A and AR sessions (-13 +/- 1 and -11 +/- 1 mmHg, respectively, P < 0.05). Diastolic BP decreased similarly after all the exercises, and this decrease lasted longer after the A session. CO also decreased similarly after the exercises, while systemic vascular resistance increased after the R and AR sessions in the recovery period (+4.0 +/- 1.7 and +6.3 +/- 1.9 U, respectively, P < 0.05). Stroke volume decreased, while HR increased after the exercises, and the greatest responses were observed after the AR session (SV, A = -14.6 +/- 3.6, R = -22.4 +/- 3.5 and AR = -23.4 +/- 2.4 ml; HR, A = +13 +/- 2, R = +15 +/- 2 vs. AR = +20 +/- 2 bpm, P < 0.05). Cardiac sympathovagal balance increased after the exercises, and the greatest increase was observed after the AR session (A = +0.7 +/- 0.8, R = +1.0 +/- 0.8 vs. AR = +1.2 +/- 0.8, P < 0.05). In conclusion, the association of aerobic and resistance exercises in the same training session did not potentiate postexercise hypotension, and increased cardiac sympathetic activation during the recovery period.

A low carbohydrate diet affects autonomic modulation during heavy but not moderate exercise

The aim of this study was to examine the effects of low carbohydrate (CHO) availability on heart rate variability (HRV) responses during moderate and severe exercise intensities until exhaustion. Six healthy males (age, 26.5 +/- 6.7 years; body mass, 78.4 +/- 7.7 kg; body fat %, 11.3 +/- 4.5%; (V) over dotO(2max), 39.5 +/- 6.6 mL kg(-1) min(-1)) volunteered for this study. All tests were performed in the morning, after 8-12 h overnight fasting, at a moderate intensity corresponding to 50% of the difference between the first (LT(1)) and second (LT(2)) lactate breakpoints and at a severe intensity corresponding to 25% of the difference between the maximal power output and LT(2). Forty-eight hours before each experimental session, the subjects performed a 90-min cycling exercise followed by 5-min rest periods and subsequent 1-min cycling bouts at 125% (V) over dotO(2max) (with 1-min rest periods) until exhaustion, in order to deplete muscle glycogen. A diet providing 10% (CHO(low)) or 65% (CHO(control)) of energy as carbohydrates was consumed for the following 2 days until the experimental test. The Poicare plots (standard deviations 1 and 2: SD1 and SD2, respectively) and spectral autoregressive model (low frequency LF, and high frequency HF) were applied to obtain HRV parameters. The CHO availability had no effect on the HRV parameters or ventilation during moderate-intensity exercise. However, the SD1 and SD2 parameters were significantly higher in CHO(low) than in CHO(control), as taken at exhaustion during the severe-intensity exercise (P < 0.05). The HF and LF frequencies (ms(2)) were also significantly higher in CHO(low) than in CHO(control) (P < 0.05). In addition, ventilation measured at the 5 and 10-min was higher in CHO(low) (62.5 +/- 4.4 and 74.8 +/- 6.5 L min(-1), respectively, P < 0.05) than in CHO(control) (70.0 +/- 3.6 and 79.6 +/- 5.1 L min(-1), respectively; P < 0.05) during the severe-intensity exercise. These results suggest that the CHO availability alters the HRV parameters during severe-, but not moderate-, intensity exercise, and this was associated with an increase in ventilation volume.

Endothelial nitric oxide synthase polymorphisms and adaptation of parasympathetic modulation to exercise training

SILVA, B. M., F. J. NEVES, M. V. NEGRÃO, C. R. ALVES, R. G. DIAS, G. B. ALVES, A. C. PEREIRA, M. Urbana A. RONDON, J. E. KRIEGER, C. E. NEGRÃO, and A. C. DA NOBREGA. Endothelial Nitric Oxide Synthase Polymorphisms and Adaptation of Parasympathetic Modulation to Exercise Training. Med. Sci. Sports Exerc., Vol. 43, No. 9, pp. 1611-1618, 2011. Purpose: There is a large interindividual variation in the parasympathetic adaptation induced by aerobic exercise training, which may be partially attributed to genetic polymorphisms. Therefore, we investigated the association among three polymorphisms in the endothelial nitric oxide gene (-786T>C, 4b4a, and 894G>T), analyzed individually and as haplotypes, and the parasympathetic adaptation induced by exercise training. Methods: Eighty healthy males, age 20-35 yr, were genotyped by polymerase chain reaction-restriction fragment length polymorphism analysis, and haplotypes were inferred using the software PHASE 2.1. Autonomic modulation (i.e., HR variability and spontaneous baroreflex sensitivity) and peak oxygen consumption ((V) over dotO(2peak)) were measured before and after training (running, moderate to severe intensity, three times per week, 60 min.day(-1), during 18 wk). Results: Training increased (V) over dotO(2peak) (P < 0.05) and decreased mean arterial pressure (P < 0.05) in the whole sample. Subjects with the -786C polymorphic allele had a significant reduction in baroreflex sensitivity after training (change: wild type (-786TT) = 2% +/- 89% vs polymorphic (-786TC/CC) = -28% +/- 60%, median +/- quartile range, P = 0.03), and parasympathetic modulation was marginally reduced in subjects with the 894T polymorphic allele (change: wild type (894GG) = 8% +/- 67% vs polymorphic (894GT/TT) = -18% +/- 59%, median +/- quartile range, P = 0.06). Furthermore, parasympathetic modulation percent change was different between the haplotypes containing wild-type alleles(-786T/4b/894G) and polymorphic alleles at positions -786 and 894 (-786C/4b/894T) (-6% +/- 56% vs -41% +/- 50%, median T quartile range, P = 0.04). Conclusions: The polymorphic allele at position -786 and the haplotype containing polymorphic alleles at positions -786 and 894 in the endothelial nitric oxide gene were associated with decreased parasympathetic modulation after exercise training.

SAB(IO): A BIOLOGICALLY PLAUSIBLE CONNECTIONIST APPROACH TO AUTOMATIC TEXT SUMMARIZATION

An implementation of a computational tool to generate new summaries from new source texts is presented, by means of the connectionist approach (artificial neural networks). Among other contributions that this work intends to bring to natural language processing research, the use of a more biologically plausible connectionist architecture and training for automatic summarization is emphasized. The choice relies on the expectation that it may bring an increase in computational efficiency when compared to the sa-called biologically implausible algorithms.

Assessment of Depressive Symptoms and Cognitive Impairment in Elders From Rural Areas of the Brazilian State of Rio Grande do Sul

The main objective of this study was to examine the relationships among demographic characteristics, depressive symptoms, and cognitive impairment in oldest-old elders from rural areas of the Brazilian State of Rio Grande do Sul. A cross-sectional, descriptive correlational design was used to conduct the study. 137 Brazilian elders age 80 years or over. A target population data form, a county data form, a demographic questionnaire, the Mini-Mental State Examination, and the Depressive Cognition Scale were used to collect the data. A significant difference was found between males and females in regard to cognitive impairment. In addition, educational level and depressive symptoms were correlated with cognitive impairment. Depressive symptoms were a weak but significant predictor of cognitive impairment after controlling for the effect of age, gender, and educational level of the oldest-old elders. The findings need to be interpreted cautiously since the sample scored above the cutoff points for cognitive impairment, and had low scores on depressive symptoms. Despite several limitations, findings from this study can be a foundation for further studies, and well-designed correlational or experimental approaches, are warranted.

A Cost-Benefit Analysis on Modulation Formats for 40-Gb/s Optical Communication Systems

This article discusses possible approaches for optical network capacity upgrade by considering the use of different modulation formats at 40 Gb/s. First, a performance evaluation is carried out regarding tolerance to three impairments: spectral narrowing due to filter cascading, chromatic dispersion, and self-phase modulation. Next, a cost-benefit analysis is conducted, considering the specific optoelectronic components required for the optical transmitter/receiver configuration of each format.

An algorithm for computerized automatic tuning of power system stabilizers

The main objective of this paper is to relieve the power system engineers from the burden of the complex and time-consuming process of power system stabilizer (PSS) tuning. To achieve this goal, the paper proposes an automatic process for computerized tuning of PSSs, which is based on an iterative process that uses a linear matrix inequality (LMI) solver to find the PSS parameters. It is shown in the paper that PSS tuning can be written as a search problem over a non-convex feasible set. The proposed algorithm solves this feasibility problem using an iterative LMI approach and a suitable initial condition, corresponding to a PSS designed for nominal operating conditions only (which is a quite simple task, since the required phase compensation is uniquely defined). Some knowledge about the PSS tuning is also incorporated in the algorithm through the specification of bounds defining the allowable PSS parameters. The application of the proposed algorithm to a benchmark test system and the nonlinear simulation of the resulting closed-loop models demonstrate the efficiency of this algorithm. (C) 2009 Elsevier Ltd. All rights reserved.

Automatic tuning method for the design of supplementary damping controllers for flexible alternating current transmission system devices

The design of supplementary damping controllers to mitigate the effects of electromechanical oscillations in power systems is a highly complex and time-consuming process, which requires a significant amount of knowledge from the part of the designer. In this study, the authors propose an automatic technique that takes the burden of tuning the controller parameters away from the power engineer and places it on the computer. Unlike other approaches that do the same based on robust control theories or evolutionary computing techniques, our proposed procedure uses an optimisation algorithm that works over a formulation of the classical tuning problem in terms of bilinear matrix inequalities. Using this formulation, it is possible to apply linear matrix inequality solvers to find a solution to the tuning problem via an iterative process, with the advantage that these solvers are widely available and have well-known convergence properties. The proposed algorithm is applied to tune the parameters of supplementary controllers for thyristor controlled series capacitors placed in the New England/New York benchmark test system, aiming at the improvement of the damping factor of inter-area modes, under several different operating conditions. The results of the linear analysis are validated by non-linear simulation and demonstrate the effectiveness of the proposed procedure.

Classification of normal swallowing and oropharyngeal dysphagia using wavelet

Oropharyngeal dysphagia is characterized by any alteration in swallowing dynamics which may lead to malnutrition and aspiration pneumonia. Early diagnosis is crucial for the prognosis of patients with dysphagia, and the best method for swallowing dynamics assessment is swallowing videofluoroscopy, an exam performed with X-rays. Because it exposes patients to radiation, videofluoroscopy should not be performed frequently nor should it be prolonged. This study presents a non-invasive method for the pre-diagnosis of dysphagia based on the analysis of the swallowing acoustics, where the discrete wavelet transform plays an important role to increase sensitivity and specificity in the identification of dysphagic patients. (C) 2008 Elsevier Inc. All rights reserved.

A classification methodology for the risk of weed infestation using fuzzy logic

Despite modern weed control practices, weeds continue to be a threat to agricultural production. Considering the variability of weeds, a classification methodology for the risk of infestation in agricultural zones using fuzzy logic is proposed. The inputs for the classification are attributes extracted from estimated maps for weed seed production and weed coverage using kriging and map analysis and from the percentage of surface infested by grass weeds, in order to account for the presence of weed species with a high rate of development and proliferation. The output for the classification predicts the risk of infestation of regions of the field for the next crop. The risk classification methodology described in this paper integrates analysis techniques which may help to reduce costs and improve weed control practices. Results for the risk classification of the infestation in a maize crop field are presented. To illustrate the effectiveness of the proposed system, the risk of infestation over the entire field is checked against the yield loss map estimated by kriging and also with the average yield loss estimated from a hyperbolic model.

An approach of optimal sensitivity applied in the tertiary loop of the automatic generation control

This paper proposes an approach of optimal sensitivity applied in the tertiary loop of the automatic generation control. The approach is based on the theorem of non-linear perturbation. From an optimal operation point obtained by an optimal power flow a new optimal operation point is directly determined after a perturbation, i.e., without the necessity of an iterative process. This new optimal operation point satisfies the constraints of the problem for small perturbation in the loads. The participation factors and the voltage set point of the automatic voltage regulators (AVR) of the generators are determined by the technique of optimal sensitivity, considering the effects of the active power losses minimization and the network constraints. The participation factors and voltage set point of the generators are supplied directly to a computational program of dynamic simulation of the automatic generation control, named by power sensitivity mode. Test results are presented to show the good performance of this approach. (C) 2008 Elsevier B.V. All rights reserved.

On the classification of mixed construction and demolition waste aggregate by porosity and its impact on the mechanical performance of concrete

The properties of recycled aggregate produced from mixed (masonry and concrete) construction and demolition (C&D) waste are highly variable, and this restricts the use of such aggregate in structural concrete production. The development of classification techniques capable of reducing this variability is instrumental for quality control purposes and the production of high quality C&D aggregate. This paper investigates how the classification of C&D mixed coarse aggregate according to porosity influences the mechanical performance of concrete. Concretes using a variety of C&D aggregate porosity classes and different water/cement ratios were produced and the mechanical properties measured. For concretes produced with constant volume fractions of water, cement, natural sand and coarse aggregate from recycled mixed C&D waste, the compressive strength and Young modulus are direct exponential functions of the aggregate porosity. Sink and float technique is a simple laboratory density separation tool that facilitates the separation of cement particles with lower porosity, a difficult task when done only by visual sorting. For this experiment, separation using a 2.2 kg/dmA(3) suspension produced recycled aggregate (porosity less than 17%) which yielded good performance in concrete production. Industrial gravity separators may lead to the production of high quality recycled aggregate from mixed C&D waste for structural concrete applications.