Gait and risk of falls associated with frontal cognitive functions at different stages of Alzheimer's disease

The decline in frontal cognitive functions contributes to alterations of gait and increases the risk of falls in patients with dementia, a category which included Alzheimer's disease (AD). The objective of the present study was to compare the gait parameters and the risk of falls among patients at different stages of AD, and to relate these variables with cognitive functions. This is a cross-sectional study with 23 patients with mild and moderate AD. The Clinical Dementia Rating was used to classify the dementia severity. The kinematic parameters of gait (cadence, stride length, and stride speed) were analyzed under two conditions: (a) single task (free gait) and (b) dual task (walking and counting down). The risk of falls was evaluated using the Timed Up-and-Go test. The frontal cognitive functions were evaluated using the Frontal Assessment Battery (FAB), the Clock Drawing Test (CDT) and the Symbol Search Subtest. The patients who were at the moderate stage suffered reduced performance in their stride length and stride speed in the single task and had made more counting errors in the dual task and still had a higher fall risk. Both the mild and the moderate patients exhibited significant decreases in stride length, stride speed and cadence in the dual task. Was detected a significant correlation between CDT, FAB, and stride speed in the dual task condition. We also found a significant correlation between subtest Similarities, FAB and cadence in the dual task condition. The dual task produced changes in the kinematic parameters of gait for the mild and moderate AD patients and the gait alterations are related to frontal cognitive functions, particularly executive functions.

Intelligence functions disorders in patients with complex partial epilepsy

Objective: To compare the performance of patients with complex partial epilepsy with the normal controls in the subtests of an instrument used to assess intelligence function. Method: Fifty epileptic patients, whose ages ranged from 19 to 49 years and 20 normal controls without any neuropsychiatric disorders. The Wechsler-Bellevue adult intelligence test was applied in groups, epileptic patients and control subjects. This test is composed of several subtests that assess specific cognitive functions. A statistical analysis was performed using non-parametric tests. Results: All the Wechsler-Bellevue subtests revealed that the intelligence functions of the patients were significantly inferior to that of the controls (p<0.05). This performance was supported by the patient's complaints in relation to their cognitive performance. Conclusion: Patients with complex partial epilepsy presented poorer results in the intelligence test when compared with individuals without neuropsychiatric disorders.

Early impairment of cognitive functions in Parkinson's disease

Background: Impairment in non-motor functions such as disturbances of some executive functions are also common events in Parkinson's disease patients. Objective: To verify the performance of Parkinson's disease patients in activities requiring visuoconstructive and visuospatial skills. Method: Thirty elderly patients with mild or moderate stages of Parkinson's disease were studied. The assessment of the clinical condition was based on the unified Parkinson's disease rating scale (56.28; SD=33.48), Hoehn and Yahr (2.2; SD=0.83), Schwab and England (78.93%), clock drawing test (7.36; SD=2.51), and mini-mental state examination (26.48; SD=10.11). Pearson's correlation and stepwise multiple regression were used for statistical analyses. Results: The patients presented deterioration in visuospatial and visuoconstructive skills. Conclusion: The clock drawing test proved to be a useful predictive tool for identifying early cognitive impairment in these individuals.

Multimodal exercise intervention improves frontal cognitive functions and gait in Alzheimer's disease: A controlled trial

Aim: The objective of the present study was to investigate the effect of a multimodal exercise intervention on frontal cognitive functions and kinematic gait parameters in patients with Alzheimer's disease. Methods: A sample of elderly patients with Alzheimer's disease (n=27) were assigned to a training group (n=14; aged 78.0±7.3years) and a control group (n=13; aged 77.1±7.4years). Multimodal exercise intervention includes motor activities and cognitive tasks simultaneously. The participants attended a 1-h session three times a week for 16weeks, and the control participants maintained their regular daily activities during the same period. The frontal cognitive functions were evaluated using the Frontal Assessment Battery, the Clock Drawing Test and the Symbol Search Subtest. The kinematic parameters of gait-cadence, stride length and stride speed were analyzed under two conditions: (i) free gait (single task); and (ii) gait with frontal cognitive task (walking and counting down from 20 - dual task). Results and discussion: The patients in the intervention group significantly increased the scores in frontal cognitive variables, Frontal Assessment Battery (P<0.001) and Symbol Search Subtest (P<0.001) after the 16-week period. The control group decreased the scores in the Clock Drawing Test (P=0.001) and increased the number of counting errors during the dual task (P=0.008) after the same period. Conclusion: The multimodal exercise intervention improved the frontal cognitive functions in patients with Alzheimer's disease. © 2012 Japan Geriatrics Society.

Benefits of Multimodal Exercise Intervention for Postural Control and Frontal Cognitive Functions in Individuals with Alzheimer's Disease: A Controlled Trial

Objective To verify the effects of a systematized multimodal exercise intervention program on frontal cognitive function, postural control, and functional capacity components of individuals with Alzheimer's disease (AD).DesignNonrandomized controlled trial with pre- and posttraining tests in a training group and a control group.SettingKinesiotherapy program for seniors with AD, SAo Paulo State University.ParticipantsConvenience sample of older adults with AD (n=30) were assigned to a training (n=14; aged 78.67.1) and a control (n=16; aged 77.06.3) group.InterventionThe intervention program was structured with the aim of simultaneously promoting better balance and frontal cognitive capacity. The participants attended a 1-hour session three times a week for 16weeks, whereas the control group did not participate in any activity during the same period.MeasurementsFrontal cognitive function was evaluated using the Montreal Cognitive Assessment, the Clock Drawing Test, the Frontal Assessment Battery, and the Symbol Search Subtest. Postural control (center of pressure area) was analyzed under four dual-task conditions. Functional capacity components were analyzed using the Timed Up and Go Test, the 30-second sit-to-stand test, the sit-and-reach test, and the Berg Functional Balance Scale.ResultsIntervention group participants showed a significant increase in frontal cognitive function (P<.001, partial (2)=0.838), with less body sway (P=.04, partial (2)=0.04) during the dual tasks, and greater functional capacity (P=.001, partial (2)=0.676) after the 16-week period.ConclusionIntervention participants performed better on dual-task activities and had better postural balance and greater functional capacity than controls.

Physical Exercise Improves Peripheral BDNF Levels and Cognitive Functions in Mild Cognitive Impairment Elderly with Different BDNF Val66Met Genotypes

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

Preliminary Findings on the Effects of Occupational Exposure to Mercury Vapor Below Safety Levels on Visual and Neuropsychological Functions

Objective: To evaluate whether there are visual and neurophysical decrements in workers with low exposure to Hg vapor. Methods: Visual fields, contrast sensitivity, color vision, and neuropsychological functions were measured in 10 workers (32.5 +/- 8.5 years) chronically exposed to Hg vapor (4.3 +/- 2.8 years; urinary Hg concentration 22.3 +/- 9.3 mu g/g creatinine). Results: For the worst eyes, we found altered visual field thresholds, lower contrast sensitivity, and color discrimination compared with controls (P < 0.05). There were no significant differences between Hg-exposed subjects and controls on. neuropsychological tests. Nevertheless, duration of exposure was statistically correlated to verbal memory and depression scores. Conclusions: Chronic exposure to Hg vapor at currently accepted safety levels was found to be associated with visual losses but not with neuropsychological dysfunctions in the sample of workers studied. (J Occup Environ Med. 2009,51:1403-1412)

Kurzweil integral for Riesz space-valued functions: Uniform convergence theorem

Our objective here is to prove that the uniform convergence of a sequence of Kurzweil integrable functions implies the convergence of the sequence formed by its corresponding integrals.

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

LOCALIZATION OF DNA REPAIR FUNCTIONS TO THE NUCLEAR MATRIX

The nucleus of a eukaryotic cell contains both structural and functional elements that contribute to the controlled operation of the cell. In this context, functional components refers to those nuclear constituents that perform metabolic activities such as DNA replication and RNA transcription. Structural nuclear components, designated nuclear matrix, organize the DNA into loops or domains and appear to provide a framework for nuclear DNA organization. However, the boundary between structural and functional components is not clear cut as evinced by reports of associations between metabolic functions and the nuclear matrix. The studies reported here attempt to determine the relationship of another nuclear function, DNA repair, to the nuclear matrix.^ One objective of these studies was to study the initiation of DNA repair by directly measuring the UV-incision activities in human cells and determine the influence of various extractable nuclear components on these activities. The assay for incision activities required the development of a nuclear isolation protocol that produced nuclei with intact DNA; the conformation of the nuclear DNA and its physical characteristics in response to denaturing conditions were determined.^ The nuclei produced with this protocol were then used as substrates for endogenous UV-specific nuclease activities. The isolated nuclei were shown to contain activities that cause breaks in nuclear DNA in response to UV-irradiation. These UV-responsive activities were tightly associated with nuclear components, being unextractable with salt concentration of up to 0.6 M.^ The tight association of the incision activities with salt-extracted nuclei suggested that other repair function might also be associated with salt-stable components of the nucleus. The site of unscheduled DNA synthesis (UDS) was determined in salt-extracted nuclei (nucleoids) using autoradiography and fluorescent microscopy. UDS was found to occur in association with the nuclear matrix following low-doses (2.55 J/M('2)) of ultraviolet light, but the association became looser after higher doses of ultraviolet light (10-30 J/m('2)). ^

A hardware in the loop design methodology for FPGA system and its application to complex functions

In this work, a unified algorithm-architecture-circuit co-design environment for complex FPGA system development is presented. The main objective is to find an efficient methodology for designing a configurable optimized FPGA system by using as few efforts as possible in verification stage, so as to speed up the development period. A proposed high performance FFT/iFFT processor for Multiband Orthogonal Frequency Division Multiplexing Ultra Wideband (MB-OFDM UWB) system design process is given as an example to demonstrate the proposed methodology. This efficient design methodology is tested and considered to be suitable for almost all types of complex FPGA system designs and verifications.

Distinct contrast response functions in striate and extra-striate regions of visual cortex revealed with magnetoencephalography (MEG)

Objective: To spatially and temporally characterise the cortical contrast response function to pattern onset stimuli in humans. Methods: Magnetoencephalography (MEG) was used to investigate the human cortical contrast response function to pattern onset stimuli with high temporal and spatial resolution. A beamformer source reconstruction approach was used to spatially localise and identify the time courses of activity at various visual cortical loci. Results: Consistent with the findings of previous studies, MEG beamformer analysis revealed two simultaneous generators of the pattern onset evoked response. These generators arose from anatomically discrete locations in striate and extra-striate visual cortex. Furthermore, these loci demonstrated notably distinct contrast response functions, with striate cortex increasing approximately linearly with contrast, whilst extra-striate visual cortex followed a saturating function. Conclusions: The generators that underlie the pattern onset visual evoked response arise from two distinct regions in striate and extra-striate visual cortex. Significance: The spatially, temporally and functionally distinct mechanisms of contrast processing within the visual cortex may account for the disparate results observed across earlier studies and assist in elucidating causal mechanisms of aberrant contrast processing in neurological disorders. © 2005 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

A rule based model for the objective determination of the e-business requirements of a manufacturing organisation

The starting point of this research was the belief that manufacturing and similar industries need help with the concept of e-business, especially in assessing the relevance of possible e-business initiatives. The research hypotheses was that it should be possible to produce a systematic model that defines, at a useful level of detail, the probable e-business requirements of an organisation based on objective criteria with an accuracy of 85%-90%. This thesis describes the development and validation of such a model. A preliminary model was developed from a variety of sources, including a survey of current and planned e-business activity and representative examples of e-business material produced by e-business solution providers. The model was subject to a process of testing and refinement based on recursive case studies, with controls over the improving accuracy and stability of the model. Useful conclusions were also possible as to the relevance of e-business functions to the case study participants themselves. Techniques were evolved to synthesise the e-business requirements of an organisation and present them at a management summary level of detail. The results of applying these techniques to all the case studies used in this research were discussed. The conclusion of the research was that the case study methodology employed was successful. A model was achieved suitable for practical application in a manufacturing organisation requiring help with a requirements definition process.

Development of safety performance functions for empirical Bayes estimation of crash reduction factors

Crash reduction factors (CRFs) are used to estimate the potential number of traffic crashes expected to be prevented from investment in safety improvement projects. The method used to develop CRFs in Florida has been based on the commonly used before-and-after approach. This approach suffers from a widely recognized problem known as regression-to-the-mean (RTM). The Empirical Bayes (EB) method has been introduced as a means to addressing the RTM problem. This method requires the information from both the treatment and reference sites in order to predict the expected number of crashes had the safety improvement projects at the treatment sites not been implemented. The information from the reference sites is estimated from a safety performance function (SPF), which is a mathematical relationship that links crashes to traffic exposure. The objective of this dissertation was to develop the SPFs for different functional classes of the Florida State Highway System. Crash data from years 2001 through 2003 along with traffic and geometric data were used in the SPF model development. SPFs for both rural and urban roadway categories were developed. The modeling data used were based on one-mile segments that contain homogeneous traffic and geometric conditions within each segment. Segments involving intersections were excluded. The scatter plots of data show that the relationships between crashes and traffic exposure are nonlinear, that crashes increase with traffic exposure in an increasing rate. Four regression models, namely, Poisson (PRM), Negative Binomial (NBRM), zero-inflated Poisson (ZIP), and zero-inflated Negative Binomial (ZINB), were fitted to the one-mile segment records for individual roadway categories. The best model was selected for each category based on a combination of the Likelihood Ratio test, the Vuong statistical test, and the Akaike's Information Criterion (AIC). The NBRM model was found to be appropriate for only one category and the ZINB model was found to be more appropriate for six other categories. The overall results show that the Negative Binomial distribution model generally provides a better fit for the data than the Poisson distribution model. In addition, the ZINB model was found to give the best fit when the count data exhibit excess zeros and over-dispersion for most of the roadway categories. While model validation shows that most data points fall within the 95% prediction intervals of the models developed, the Pearson goodness-of-fit measure does not show statistical significance. This is expected as traffic volume is only one of the many factors contributing to the overall crash experience, and that the SPFs are to be applied in conjunction with Accident Modification Factors (AMFs) to further account for the safety impacts of major geometric features before arriving at the final crash prediction. However, with improved traffic and crash data quality, the crash prediction power of SPF models may be further improved.

Parametric CAD model based shape optimization using adjoint functions

Adjoint methods have proven to be an efficient way of calculating the gradient of an objective function with respect to a shape parameter for optimisation, with a computational cost nearly independent of the number of the design variables [1]. The approach in this paper links the adjoint surface sensitivities (gradient of objective function with respect to the surface movement) with the parametric design velocities (movement of the surface due to a CAD parameter perturbation) in order to compute the gradient of the objective function with respect to CAD variables.
For a successful implementation of shape optimization strategies in practical industrial cases, the choice of design variables or parameterisation scheme used for the model to be optimized plays a vital role. Where the goal is to base the optimization on a CAD model the choices are to use a NURBS geometry generated from CAD modelling software, where the position of the NURBS control points are the optimisation variables [2] or to use the feature based CAD model with all of the construction history to preserve the design intent [3]. The main advantage of using the feature based model is that the optimized model produced can be directly used for the downstream applications including manufacturing and process planning.
This paper presents an approach for optimization based on the feature based CAD model, which uses CAD parameters defining the features in the model geometry as the design variables. In order to capture the CAD surface movement with respect to the change in design variable, the “Parametric Design Velocity” is calculated, which is defined as the movement of the CAD model boundary in the normal direction due to a change in the parameter value.
The approach presented here for calculating the design velocities represents an advancement in terms of capability and robustness of that described by Robinson et al. [3]. The process can be easily integrated to most industrial optimisation workflows and is immune to the topology and labelling issues highlighted by other CAD based optimisation processes. It considers every continuous (“real value”) parameter type as an optimisation variable, and it can be adapted to work with any CAD modelling software, as long as it has an API which provides access to the values of the parameters which control the model shape and allows the model geometry to be exported. To calculate the movement of the boundary the methodology employs finite differences on the shape of the 3D CAD models before and after the parameter perturbation. The implementation procedure includes calculating the geometrical movement along a normal direction between two discrete representations of the original and perturbed geometry respectively. Parametric design velocities can then be directly linked with adjoint surface sensitivities to extract the gradients to use in a gradient-based optimization algorithm.
The optimisation of a flow optimisation problem is presented, in which the power dissipation of the flow in an automotive air duct is to be reduced by changing the parameters of the CAD geometry created in CATIA V5. The flow sensitivities are computed with the continuous adjoint method for a laminar and turbulent flow [4] and are combined with the parametric design velocities to compute the cost function gradients. A line-search algorithm is then used to update the design variables and proceed further with optimisation process.