Balance control in hemiparetic stroke patients: Main tools for evaluation

Balance problems in hemiparetic patients after stroke can be caused by different impairments in the physiological systems involved in Postural control, including sensory afferents, movement strategies, biomechanical constraints, cognitive processing, and perception of verticality. Balance impairments and disabilities must be appropriately addressed. This article reviews the most common balance abnormalities in hemiparetic patients with stroke and the main tools used to diagnose them.

Postural changes in women with chronic pelvic pain: a case control study

Background: Chronic pelvic pain (CPP) is a lower abdominal pain lasting at least 6 months, occurring continuously or intermittently and not associated exclusively with menstruation or intercourse. Although the musculoskeletal system has been found to be involved in CPP, few studies have assessed the contribution of posture in women with CPP. We aimed to determine if the frequency of postural changes was higher in women with CPP than healthy subjects. Methods: A case-control study included 108 women with CPP of more than 6 months' duration (CPP group) who consecutively attended at the Hospital of the University of Sao Paulo and 48 healthy female volunteers (control group). Postural assessment was noninvasive and performed in the standing position, with the reference points of Kendall used as normal parameters. Factors associated with CPP were assessed by logistic regression analysis. Results: Logistic regression showed that the independent factors associated with CPP were postural changes in the cervical spine (OR 4.1; 95% CI 1.6-10.7; p < 0.01) and scapulae (OR 2.9; 95% CI 1.1-7.6; p < 0.05). Conclusion: Musculoskeletal changes were associated with CPP in 34% of women. These findings suggest that a more detailed assessment of women with CPP is necessary for better diagnosis and for more effective treatment.

A Dynamic Analysis of Tuberculosis Dissemination to Improve Control and Surveillance

Background: Detailed analysis of the dynamic interactions among biological, environmental, social, and economic factors that favour the spread of certain diseases is extremely useful for designing effective control strategies. Diseases like tuberculosis that kills somebody every 15 seconds in the world, require methods that take into account the disease dynamics to design truly efficient control and surveillance strategies. The usual and well established statistical approaches provide insights into the cause-effect relationships that favour disease transmission but they only estimate risk areas, spatial or temporal trends. Here we introduce a novel approach that allows figuring out the dynamical behaviour of the disease spreading. This information can subsequently be used to validate mathematical models of the dissemination process from which the underlying mechanisms that are responsible for this spreading could be inferred. Methodology/Principal Findings: The method presented here is based on the analysis of the spread of tuberculosis in a Brazilian endemic city during five consecutive years. The detailed analysis of the spatio-temporal correlation of the yearly geo-referenced data, using different characteristic times of the disease evolution, allowed us to trace the temporal path of the aetiological agent, to locate the sources of infection, and to characterize the dynamics of disease spreading. Consequently, the method also allowed for the identification of socio-economic factors that influence the process. Conclusions/Significance: The information obtained can contribute to more effective budget allocation, drug distribution and recruitment of human skilled resources, as well as guiding the design of vaccination programs. We propose that this novel strategy can also be applied to the evaluation of other diseases as well as other social processes.

Revisiting clinical trials on glycemic control and cardiovascular risk

The most relevant clinical trials, assessing the role of glycemic control in reducing cardiovascular risk, are examined. The UKPDS was the first to address this issue. More recent trials (ACCORD, ADVANCE and VADT) are controversial and evidences did not support that strict glycemic control (reflected by normal glycated hemoglobin) exclusively is sufficient to reduce cardiovascular risk in complicated individuals with long-term type 2 diabetes mellitus. Some possible reasons for controversies are included.

Endophytic and entomopathogenic strains of Beauveria sp to control the bovine tick Rhipicephalus (Boophilus) microplus

Pathogenicity of strains of the entomopathogenic fungus Beauveria bassiana and endophytic strains of Beauveria sp against the bovine tick Rhipicephalus (Boophilus) microplus was tested in laboratory bioassays and under field conditions. Suspensions containing 10(5), 10(7) and 10(9) conidia/mL were prepared of each fungal strain for laboratory bioassays. The ticks were maintained at 28 degrees C, 90 +/- 5% relative humidity, and the following variables were evaluated: initial female weight, egg weight, hatching percentage, reproductive efficiency, and percentage control. For tests under field conditions, a Beauveria suspension containing 10(6) conidia/mL was sprayed on tick-infested cows. After 72 h, the ticks were collected to estimate mortality under field conditions. Laboratory bioassays showed a mortality of 20 to 50% of the ticks seven days after inoculation with 10(7) Beauveria conidia/mL. Under field conditions 10(6) Beauveria conidia/mL induced 18-32% mortality. All Beauveria strains were effective in biological control of R. (Boophilus) microplus under laboratory and field test conditions. This is the first demonstration that endophytic fungi can be used for biological control of the cattle tick; this could help reduce environmental contamination by diminishing the need for chemical acaricides. Two endophytic strains were isolated from maize leaves and characterized by molecular sequencing of 5.8S rDNA ITS1 and ITS2 and morphological analyses of conidia. We found that these two endophytic Beauveria isolates, designated B95 and B157, are close to Beauveria amorpha.

Detection of polymorphisms of the mtDNA control region of Caretta caretta (Testudines: Cheloniidae) by PCR-SSCP

Marine turtles are increasingly being threatened worldwide by anthropogenic activities. Better understanding of their life cycle, behavior and population structure is imperative for the design of adequate conservation strategies. The mtDNA control region is a fast-evolving matrilineal marker that has been employed in the study of marine turtle populations. We developed and tested a simple molecular tracing system for Caretta caretta mtDNA haplotypes by polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP). Using this technique, we were able to distinguish the SSCP patterns of 18 individuals of the haplotypes CC-A4, CC-A24 and CCxLO, which are commonly found in turtles sampled on the Brazilian coast. When we analyzed 15 turtles with previously unknown sequences, we detected two other haplotypes, in addition to the other four. Based on DNA sequencing, they were identified as the CC-A17 and CC-A1 haplotypes. Further analyses were made with the sea turtles, Chelonia mydas (N = 8), Lepidochelys olivacea (N = 3) and Eretmochelys imbricata (N = 1), demonstrating that the PCR-SSCP technique is able to distinguish intra-and interspecific variation in the family Cheloniidae. We found that this technique can be useful for identifying sea turtle mtDNA haplotypes, reducing the need for sequencing.

Control of the Intracellular Redox State by Glucose Participates in the Insulin Secretion Mechanism

Background: Production of reactive oxygen species (ROS) due to chronic exposure to glucose has been associated with impaired beta cell function and diabetes. However, physiologically, beta cells are well equipped to deal with episodic glucose loads, to which they respond with a fine tuned glucose-stimulated insulin secretion (GSIS). In the present study, a systematic investigation in rat pancreatic islets about the changes in the redox environment induced by acute exposure to glucose was carried out. Methodology/Principal Findings: Short term incubations were performed in isolated rat pancreatic islets. Glucose dose- and time-dependently reduced the intracellular ROS content in pancreatic islets as assayed by fluorescence in a confocal microscope. This decrease was due to activation of pentose-phosphate pathway (PPP). Inhibition of PPP blunted the redox control as well as GSIS in a dose-dependent manner. The addition of low doses of ROS scavengers at high glucose concentration acutely improved beta cell function. The ROS scavenger N-acetyl-L-cysteine increased the intracellular calcium response to glucose that was associated with a small decrease in ROS content. Additionally, the presence of the hydrogen peroxide-specific scavenger catalase, in its membrane-permeable form, nearly doubled glucose metabolism. Interestingly, though an increase in GSIS was also observed, this did not match the effect on glucose metabolism. Conclusions: The control of ROS content via PPP activation by glucose importantly contributes to the mechanisms that couple the glucose stimulus to insulin secretion. Moreover, we identified intracellular hydrogen peroxide as an inhibitor of glucose metabolism intrinsic to rat pancreatic islets. These findings suggest that the intracellular adjustment of the redox environment by glucose plays an important role in the mechanism of GSIS.

Social Networks Shape the Transmission Dynamics of Hepatitis C Virus

Hepatitis C virus (HCV) infects 170 million people worldwide, and is a major public health problem in Brazil, where over 1% of the population may be infected and where multiple viral genotypes co-circulate. Chronically infected individuals are both the source of transmission to others and are at risk for HCV-related diseases, such as liver cancer and cirrhosis. Before the adoption of anti-HCV control measures in blood banks, this virus was mainly transmitted via blood transfusion. Today, needle sharing among injecting drug users is the most common form of HCV transmission. Of particular importance is that HCV prevalence is growing in non-risk groups. Since there is no vaccine against HCV, it is important to determine the factors that control viral transmission in order to develop more efficient control measures. However, despite the health costs associated with HCV, the factors that determine the spread of virus at the epidemiological scale are often poorly understood. Here, we sequenced partial NS5b gene sequences sampled from blood samples collected from 591 patients in Sao Paulo state, Brazil. We show that different viral genotypes entered Sao Paulo at different times, grew at different rates, and are associated with different age groups and risk behaviors. In particular, subtype 1b is older and grew more slowly than subtypes 1a and 3a, and is associated with multiple age classes. In contrast, subtypes 1a and 3b are associated with younger people infected more recently, possibly with higher rates of sexual transmission. The transmission dynamics of HCV in Sao Paulo therefore vary by subtype and are determined by a combination of age, risk exposure and underlying social network. We conclude that social factors may play a key role in determining the rate and pattern of HCV spread, and should influence future intervention policies.

Particle competition for complex network community detection

In many real situations, randomness is considered to be uncertainty or even confusion which impedes human beings from making a correct decision. Here we study the combined role of randomness and determinism in particle dynamics for complex network community detection. In the proposed model, particles walk in the network and compete with each other in such a way that each of them tries to possess as many nodes as possible. Moreover, we introduce a rule to adjust the level of randomness of particle walking in the network, and we have found that a portion of randomness can largely improve the community detection rate. Computer simulations show that the model has good community detection performance and at the same time presents low computational complexity. (C) 2008 American Institute of Physics.

Generalized connectivity between any two nodes in a complex network

This article focuses on the identification of the number of paths with different lengths between pairs of nodes in complex networks and how these paths can be used for characterization of topological properties of theoretical and real-world complex networks. This analysis revealed that the number of paths can provide a better discrimination of network models than traditional network measurements. In addition, the analysis of real-world networks suggests that the long-range connectivity tends to be limited in these networks and may be strongly related to network growth and organization.

Finding Quasi-Optimal Network Topologies for Information Transmission in Active Networks

This work clarifies the relation between network circuit (topology) and behaviour (information transmission and synchronization) in active networks, e.g. neural networks. As an application, we show how one can find network topologies that are able to transmit a large amount of information, possess a large number of communication channels, and are robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements) whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.

Network of recurrent events for the Olami-Feder-Christensen model

We numerically study the dynamics of a discrete spring-block model introduced by Olami, Feder, and Christensen (OFC) to mimic earthquakes and investigate to what extent this simple model is able to reproduce the observed spatiotemporal clustering of seismicity. Following a recently proposed method to characterize such clustering by networks of recurrent events [J. Davidsen, P. Grassberger, and M. Paczuski, Geophys. Res. Lett. 33, L11304 (2006)], we find that for synthetic catalogs generated by the OFC model these networks have many nontrivial statistical properties. This includes characteristic degree distributions, very similar to what has been observed for real seismicity. There are, however, also significant differences between the OFC model and earthquake catalogs, indicating that this simple model is insufficient to account for certain aspects of the spatiotemporal clustering of seismicity.

Engineering interactions for quasiperfect transfer of polariton states through nonideal bosonic networks of distinct topologies

We present a scheme for quasiperfect transfer of polariton states from a sender to a spatially separated receiver, both composed of high-quality cavities filled by atomic samples. The sender and the receiver are connected by a nonideal transmission channel -the data bus- modelled by a network of lossy empty cavities. In particular, we analyze the influence of a large class of data-bus topologies on the fidelity and transfer time of the polariton state. Moreover, we also assume dispersive couplings between the polariton fields and the data-bus normal modes in order to achieve a tunneling-like state transfer. Such a tunneling-transfer mechanism, by which the excitation energy of the polariton effectively does not populate the data-bus cavities, is capable of attenuating appreciably the dissipative effects of the data-bus cavities. After deriving a Hamiltonian for the effective coupling between the sender and the receiver, we show that the decay rate of the fidelity is proportional to a cooperativity parameter that weighs the cost of the dissipation rate against the benefit of the effective coupling strength. The increase of the fidelity of the transfer process can be achieved at the expense of longer transfer times. We also show that the dependence of both the fidelity and the transfer time on the network topology is analyzed in detail for distinct regimes of parameters. It follows that the data-bus topology can be explored to control the time of the state-transfer process.

Equivalence between Redfield- and master-equation approaches for a time-dependent quantum system and coherence control

We present a derivation of the Redfield formalism for treating the dissipative dynamics of a time-dependent quantum system coupled to a classical environment. We compare such a formalism with the master equation approach where the environments are treated quantum mechanically. Focusing on a time-dependent spin-1/2 system we demonstrate the equivalence between both approaches by showing that they lead to the same Bloch equations and, as a consequence, to the same characteristic times T(1) and T(2) (associated with the longitudinal and transverse relaxations, respectively). These characteristic times are shown to be related to the operator-sum representation and the equivalent phenomenological-operator approach. Finally, we present a protocol to circumvent the decoherence processes due to the loss of energy (and thus, associated with T(1)). To this end, we simply associate the time dependence of the quantum system to an easily achieved modulated frequency. A possible implementation of the protocol is also proposed in the context of nuclear magnetic resonance.

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.