Nonclassical correlation in NMR quadrupolar systems

The existence of quantum correlation (as revealed by quantum discord), other than entanglement and its role in quantum-information processing (QIP), is a current subject for discussion. In particular, it has been suggested that this nonclassical correlation may provide computational speedup for some quantum algorithms. In this regard, bulk nuclear magnetic resonance (NMR) has been successfully used as a test bench for many QIP implementations, although it has also been continuously criticized for not presenting entanglement in most of the systems used so far. In this paper, we report a theoretical and experimental study on the dynamics of quantum and classical correlations in an NMR quadrupolar system. We present a method for computing the correlations from experimental NMR deviation-density matrices and show that, given the action of the nuclear-spin environment, the relaxation produces a monotonic time decay in the correlations. Although the experimental realizations were performed in a specific quadrupolar system, the main results presented here can be applied to whichever system uses a deviation-density matrix formalism.

Reverse engineering in many-body quantum physics: Correspondence between many-body systems and effective single-particle equations

The mapping, exact or approximate, of a many-body problem onto an effective single-body problem is one of the most widely used conceptual and computational tools of physics. Here, we propose and investigate the inverse map of effective approximate single-particle equations onto the corresponding many-particle system. This approach allows us to understand which interacting system a given single-particle approximation is actually describing, and how far this is from the original physical many-body system. We illustrate the resulting reverse engineering process by means of the Kohn-Sham equations of density-functional theory. In this application, our procedure sheds light on the nonlocality of the density-potential mapping of density-functional theory, and on the self-interaction error inherent in approximate density functionals.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

Lossless filter for multiple repeats with bounded edit distance

Background: Identifying local similarity between two or more sequences, or identifying repeats occurring at least twice in a sequence, is an essential part in the analysis of biological sequences and of their phylogenetic relationship. Finding such fragments while allowing for a certain number of insertions, deletions, and substitutions, is however known to be a computationally expensive task, and consequently exact methods can usually not be applied in practice. Results: The filter TUIUIU that we introduce in this paper provides a possible solution to this problem. It can be used as a preprocessing step to any multiple alignment or repeats inference method, eliminating a possibly large fraction of the input that is guaranteed not to contain any approximate repeat. It consists in the verification of several strong necessary conditions that can be checked in a fast way. We implemented three versions of the filter. The first is simply a straightforward extension to the case of multiple sequences of an application of conditions already existing in the literature. The second uses a stronger condition which, as our results show, enable to filter sensibly more with negligible (if any) additional time. The third version uses an additional condition and pushes the sensibility of the filter even further with a non negligible additional time in many circumstances; our experiments show that it is particularly useful with large error rates. The latter version was applied as a preprocessing of a multiple alignment tool, obtaining an overall time (filter plus alignment) on average 63 and at best 530 times smaller than before (direct alignment), with in most cases a better quality alignment. Conclusion: To the best of our knowledge, TUIUIU is the first filter designed for multiple repeats and for dealing with error rates greater than 10% of the repeats length.

Feature selection environment for genomic applications

Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e., for dimensionality reduction). There are many genomic and proteomic applications that rely on feature selection to answer questions such as selecting signature genes which are informative about some biological state, e. g., normal tissues and several types of cancer; or inferring a prediction network among elements such as genes, proteins and external stimuli. In these applications, a recurrent problem is the lack of samples to perform an adequate estimate of the joint probabilities between element states. A myriad of feature selection algorithms and criterion functions have been proposed, although it is difficult to point the best solution for each application. Results: The intent of this work is to provide an open-source multiplataform graphical environment for bioinformatics problems, which supports many feature selection algorithms, criterion functions and graphic visualization tools such as scatterplots, parallel coordinates and graphs. A feature selection approach for growing genetic networks from seed genes ( targets or predictors) is also implemented in the system. Conclusion: The proposed feature selection environment allows data analysis using several algorithms, criterion functions and graphic visualization tools. Our experiments have shown the software effectiveness in two distinct types of biological problems. Besides, the environment can be used in different pattern recognition applications, although the main concern regards bioinformatics tasks.

Construct and Compare Gene Coexpression Networks with DAPfinder and DAPview

Background: DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes. Results: Each significant difference in gene-gene association represents a Differentially Associated Pair (DAP). Our tools include several choices of filtering methods, gene-gene association metrics, statistical testing methods and multiple comparison adjustments. Network results are easily displayed in Cytoscape. Analyses of glioma experiments and microarray simulations demonstrate the utility of these tools. Conclusions: DAPfinder is a new friendly-user tool for reconstruction and comparison of biological networks.

The impact of measurement errors in the identification of regulatory networks

Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

Chromic materials for responsive surface-enhanced resonance Raman scattering systems: a nanometric pH sensor

The use of chromic materials for responsive surface-enhanced resonance Raman scattering (SERRS) based nanosensors is reported. The potential of nano-chromic SERRS is demonstrated with the use of the halochrome methyl yellow to fabricate an ultrasensitive pH optical sensor. Some of the challenges of the incorporation of chromic materials with metal nanostructures are addressed through the use of computational calculations and a comparison to measured SERRS and surface-enhanced Raman scattering (SERS) spectra is presented. A strong correlation between the measured SERRS and the medium's proton concentration is demonstrated for the pH range 2-6. The high sensitivity achieved by the use of resonance Raman conditions is shown through responsive SERRS measurements from only femtolitres of volume and with the concentration of the reporting molecules approaching the single molecule regime.

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.

Evaluation of alternative technical markers for the pelvic coordinate system

In this study, we evaluated alternative technical markers for the motion analysis of the pelvic segment. Thirteen subjects walked eight times while tri-dimensional kinematics were recorded for one stride of each trial. Five marker sets were evaluated, and we compared the tilt, obliquity, and rotation angles of the pelvis segment: (1) standard: markers at the anterior and posterior superior iliac spines (ASIS and PSIS); (2) markers at the PSIS and at the hip joint centers, HJCs (estimated by a functional method and described with clusters of markers at the thighs); (3) markers at the PSIS and HJCs (estimated by a predictive method and described with clusters of markers at the thighs); (4) markers at the PSIS and HJCs (estimated by a predictive method and described with skin-mounted markers at the thighs based on the Helen-Hayes marker set); (5) markers at the PSIS and at the iliac spines. Concerning the pelvic angles, evaluation of the alternative technical marker sets evinced that all marker sets demonstrated similar precision across trials (about 1 degrees) but different accuracies (ranging from 1 degrees to 3 degrees) in comparison to the standard marker set. We suggest that all the investigated marker sets are reliable alternatives to the standard pelvic marker set. (C) 2009 Elsevier Ltd. All rights reserved.

Neuromuscular activity during bench press exercise performed with and without the preexhaustion method

Brennecke, A, Guimaraees, TM, Leone, R, Cadarci, M, Mochizuki, L, Simao, R, Amadio, AC, and Serrao, J. Neuromuscular activity during bench press exercise performed with and without the preexhaustion method. J Strength Cond Res 23(7): 1933-1940, 2009-The purpose of the present study was to investigate the effects of exercise order on the tonic and phasic characteristics of upper-body muscle activity during bench press exercise in trained subjects. The preexhaustion method involves working a muscle or a muscle group combining a single-joint exercise immediately followed by a multi-joint exercise (e. g., flying exercise followed by bench press exercise). Twelve subjects performed 1 set of bench press exercises with and without the preexhaustion method following 2 protocols (P1-flying before bench press; P2-bench press). Both exercises were performed at a load of 10 repetition maximum (10RM). Electromyography (EMG) sampled at 1 kHz was recorded from the pectoralis major (PM), anterior deltoid (DA), and triceps brachii (TB). Kinematic data (60 Hz) were synchronized to define upward and downward phases of exercise. No significant (p > 0.05) changes were seen in tonic control of PM and DA muscles between P1 and P2. However, TB tonic aspect of neurophysiologic behavior of motor units was significantly higher (p < 0.05) during P1. Moreover, phasic control of PM, DA, and TB muscles were not affected (p > 0.05). The kinematic pattern of movement changed as a result of muscular weakness in P1. Angular velocity of the right shoulder performed during the upward phase of the bench press exercise was significantly slower (p < 0.05) during P1. Our results suggest that the strategies set by the central nervous system to provide the performance required by the exercise are held constant throughout the exercise, but the tonic aspects of the central drive are increased so as to adapt to the progressive occurrence of the neuromuscular fatigue. Changes in tonic control as a result of the muscular weakness and fatigue can cause changes in movement techniques. These changes may be related to limited ability to control mechanical loads and mechanical energy transmission to joints and passive structures.

Comparison of three-dimensional lower extremity running kinematics of young adult and elderly runners

The objective of this study was to compare the three-dimensional lower extremity running kinematics of young adult runners and elderly runners. Seventeen elderly adults (age 67-73 years) and 17 young adults (age 26-36 years) ran at 3.1ms-1 on a treadmill while the movements of the lower extremity during the stance phase were recorded at 120Hz using three-dimensional video. The three-dimensional kinematics of the lower limb segments and of the ankle and knee joints were determined, and selected variables were calculated to describe the movement. Our results suggest that elderly runners have a different movement pattern of the lower extremity from that of young adults during the stance phase of running. Compared with the young adults, the elderly runners had a substantial decrease in stride length (1.97 vs. 2.23m; P=0.01), an increase in stride frequency (1.58 vs. 1.37Hz; P=0.002), less knee flexion/extension range of motion (26 vs. 33; P=0.002), less tibial internal/external rotation range of motion (9 vs. 12; P0.001), larger external rotation angle of the foot segment (toe-out angle) at the heel strike (-5.8 vs. -1.0; P=0.009), and greater asynchronies between the ankle and knee movements during running. These results may help to explain why elderly individuals could be more susceptible to running-related injuries.

Joint forces and torques when walking in shallow water

This study reports for the first time an estimation of the internal net joint forces and torques on adults` lower limbs and pelvis when walking in shallow water, taking into account the drag forces generated by the movement of their bodies in the water and the equivalent data when they walk on land. A force plate and a video camera were used to perform a two-dimensional gait analysis at the sagittal plane of 10 healthy young adults walking at comfortable speeds on land and in water at a chest-high level. We estimated the drag force on each body segment and the joint forces and torques at the ankle, knee, and hip of the right side of their bodies using inverse dynamics. The observed subjects` apparent weight in water was about 35% of their weight on land and they were about 2.7 times slower when walking in water. When the subjects walked in water compared with walking on land, there were no differences in the angular displacements but there was a significant reduction in the joint torques which was related to the water`s depth. The greatest reduction was observed for the ankle and then the knee and no reduction was observed for the hip. All joint powers were significantly reduced in water. The compressive and shear joint forces were on average about three times lower during walking in water than on land. These quantitative results substantiate the use of water as a safe environment for practicing low-impact exercises, particularly walking. (C) 2011 Elsevier Ltd. All rights reserved.

Peak torque and rate of torque development in elderly with and without fall history

Background Falls are one of the greatest concerns among the elderly A number of studies have described peak torque as one of the best fall-related predictor. No studies have comprehensively focused on the rate of torque development of the lower limb muscles among elderly fallers. Then, the aim of this study was to determine the relationship between muscle peak torque and rate of torque development of the lower limb joints in elderly with and without fall history It was also aimed to determine whether these parameters of muscle performance (i e, peak torque and rate of torque development) are related to the number of falls. Methods: Thirty-one women volunteered to participate in the study and were assigned in one of the groups according to the number of falls over the 12 months that preceded the present Then, participants with no fall history (Cl; n = 13; 67.6[7.5] years-old), one fall (GII; n = 8, 66 0[4 91 years-old) and two or more falls (GIII, n = 10; 67.8[8.8] years-old) performed a number of lower limb maximal isometric voluntary contractions from which peak torque and rate of torque development were quantified Findings. Primary outcomes indicated no peak torque differences between experimental groups in any lower limb joint. The rate of torque development of the knee flexor muscles observed in the non-fallers (Cl) was greater than that observed in the fallers (P < 0.05) and had a significant relationship with the number of falls (P < 0 05) Interpretation. The greater knee flexor muscles` rate of torque development found in the non-fallers in comparison to the fallers indicated that the ability of the elderly to rapidly reorganise the arrangement of the lower limb may play a significant role in allowing the elderly to recover balance after a trip. Thus, training stimulus aimed to improve the rate of torque development may be more beneficial to prevent falls among the elderly than other training stimulus, which are not specifically designed to improve the ability to rapidly produce large amounts of torque (C) 2010 Published by Elsevier Ltd