Variability of gait patterns during unconstrained walking assessed by satellite positioning (GPS).

It is established that the ratio between step length (SL) and step frequency (SF) is constant over a large range of walking speed. However, few data are available about the spontaneous variability of this ratio during unconstrained outdoor walking, in particular over a sufficient number of steps. The purpose of the present study was to assess the inter- and intra-subject variability of spatio-temporal gait characteristics [SL, SF and walk ratio (WR=SL/SF)] while walking at different freely selected speeds. Twelve healthy subjects walked three times along a 100-m athletic track at: (1). a slower than preferred speed, (2). preferred speed and (3). a faster than preferred speed. Two professional GPS receivers providing 3D positions assessed the walking speed and SF with high precision (less than 0.5% error). Intra-subject variability was calculated as the variation among eight consecutive 5-s samples. WR was found to be constant at preferred and fast speeds [0.41 (0.04) m.s and 0.41 (0.05) m.s respectively] but was higher at slow speeds [0.44 (0.05) m.s]. In other words, between slow and preferred speed, the speed increase was mediated more by a change in SF than SL. The intra-subject variability of WR was low under preferred [CV, coefficient of variation = 1.9 (0.6)%] and fast [CV=1.8 (0.5)%] speed conditions, but higher under low speed condition [CV=4.1 (1.5)%]. On the other hand, the inter-subject variability of WR was 11%, 10% and 12% at slow, preferred and fast walking speeds respectively. It is concluded that the GPS method is able to capture basic gait parameters over a short period of time (5 s). A specific gait pattern for slow walking was observed. Furthermore, it seems that the walking patterns in free-living conditions exhibit low intra-individual variability, but that there is substantial variability between subjects.

Predictive value of the acid fast smear for detection of Mycobacterium tuberculosis in respiratory specimens in a Reference Center of HIV/Aids in Rio de Janeiro, Brazil

In order to evaluate the predictive value of acid fast bacilii (AFB) smear for the diagnosis of Mycobacterium tuberculosis in respiratory specimens in a setting with a high prevalence of Aids and an unknown prevalence of nontuberculous mycobacteria (NTM), we retrospectively examined specimens cultured for mycobacteria between 1 September 1993 and 30 September 1994 and medical records of patients with positive culture in a General Hospital, Aids reference in Rio de Janeiro, Brazil. Seventy three per cent (1517/2077) of samples were respiratory specimens and mycobacteria were recovered from 20.6% (313/1517) of these. M. tuberculosis was identified in 94.2% (295/313) and NTM in 5.8% (18/313). The yield of positive AFB smear and of positive culture was 6.1% (93/1517) and 20.6% (313/1517), respectively. The positive predictive value (PPV) of AFB for M. tuberculosis was 98.4% in expectorated sputum and 96.4% in bronchoalveolar lavage. Forty four percent (130/295) of specimens with positive culture for M. tuberculosis and 66.7% (12/18) for NTM were from patients HIV positive. The conclusion was that in our study population, the PPV of AFB for M. tuberculosis in respiratory specimens was high and the prevalence of NTM was low despite the high prevalence of HIV positive.

Evaluation of detection methods for Virus, Viroids and Phytoplasmas affecting pear and apple

The RT-PCR technique for the detection of apple stem grooving virus (ASGV), apple stem pitting virus (ASPV), apple chlorotic leaf spot virus (ACLSV), apple mosaic virus (ApMV) and pear blister canker viroid (PBCV) was evaluated for health control of fruit plants from nurseries. The technique was evaluated in purified RNA and crude extracts and also in phloem collected in autumn and from young spring shoots. The results obtained for phytoplasma detection with ribosomal and non-ribosomal primers are also presented.

Comparing Multilevel Clustering Methods on Weighted Graphs : The Case of Worldwide Air Passenger Traffic 2000-2004

Specific properties emerge from the structure of large networks, such as that of worldwide air traffic, including a highly hierarchical node structure and multi-level small world sub-groups that strongly influence future dynamics. We have developed clustering methods to understand the form of these structures, to identify structural properties, and to evaluate the effects of these properties. Graph clustering methods are often constructed from different components: a metric, a clustering index, and a modularity measure to assess the quality of a clustering method. To understand the impact of each of these components on the clustering method, we explore and compare different combinations. These different combinations are used to compare multilevel clustering methods to delineate the effects of geographical distance, hubs, network densities, and bridges on worldwide air passenger traffic. The ultimate goal of this methodological research is to demonstrate evidence of combined effects in the development of an air traffic network. In fact, the network can be divided into different levels of âeurooecohesionâeuro, which can be qualified and measured by comparative studies (Newman, 2002; Guimera et al., 2005; Sales-Pardo et al., 2007).

Improving the performance of positive selection inference by filtering unreliable alignment regions.

Errors in the inferred multiple sequence alignment may lead to false prediction of positive selection. Recently, methods for detecting unreliable alignment regions were developed and were shown to accurately identify incorrectly aligned regions. While removing unreliable alignment regions is expected to increase the accuracy of positive selection inference, such filtering may also significantly decrease the power of the test, as positively selected regions are fast evolving, and those same regions are often those that are difficult to align. Here, we used realistic simulations that mimic sequence evolution of HIV-1 genes to test the hypothesis that the performance of positive selection inference using codon models can be improved by removing unreliable alignment regions. Our study shows that the benefit of removing unreliable regions exceeds the loss of power due to the removal of some of the true positively selected sites.

Imaging molasse and quaternary sediments in Lake Geneva, Switzerland, with 3-D high-resolution seismic reflection methods: A case study

A high-resolution three-dimensional (3-D) seismic reflection survey was conducted in Lake Geneva, near the city of Lausanne, Switzerland, as part of a project for developing such seismic techniques. Using a single 48-channel streamer, the 3-D site with an area of 1200 m x 600 m was surveyed in 10 days. A variety of complex geologic structures (e.g. thrusts, folds, channel-fill) up to similar to150 m below the water bottom were obtained with a 15 in.(3) water gun. The 3-D data allowed the construction of an accurate velocity model and the distinction of five major seismic facies within the Lower Freshwater Molasse (Aquitanian) and the Quaternary sedimentary units. Additionally, the Plateau Molasse (PM) and Subalpine Molasse (SM) erosional surface, "La Paudeze" thrust fault (PM-SM boundary) and the thickness of Quaternary sediments were accurately delineated in 3-D.

Direct methods for detecting picorna-like virus from dead and alive Triatomine insects

In this work we report four different destructive and non-destructive methods for detecting picorna-like virus particles in triatomines. The methods are based on direct observation under transmission electron microscope and they consist of four ways to prepare samples of presumable infected material. The samples are prepared processing dead or alive insect parts, or even dry or fresh insect feces. The methods can be used as analytical or preparative techniques, for quantifying virus infection and checking virus integrity as well. In this work the four methods are applied in order to detect Triatoma virus (TrV) particles in T. infestans colonies.

Analysis of genetic diversity of Trypanosoma cruzi: an application of riboprinting and gradient gel electrophoresis methods

Analysis of restriction fragment length polymorphism (RFLP) profiles derived from digestion of polymerase chain reaction (PCR) products of the ribosomal 18S from Trypanosoma cruzi yields a typical `riboprint' profile that can vary intraspecifically. A selection of 21 stocks of T. cruzi and three outgroup taxa: T. rangeli, T. conorhini and Leishmania braziliensis were analysed by riboprinting to assess divergence within and between taxa. T. rangeli, T. conorhini and L. braziliensis could be easily differentiated from each other and from T. cruzi. Phenetic analysis of PCR-RFLP profiles indicated that, with one or two exceptions, stocks of T. cruzi could be broadly partitioned into two groups that formally corresponded to T. cruzi I and T. cruzi II respectively. To test if ribosomal 18S sequences were homogeneous within each taxon, gradient gel electrophoresis methods were employed utilising either chemical or temperature gradients. Upon interpretation of the melting profiles of riboprints and a section of the 18S independently amplified by PCR, there would appear to be at least two divergent 18S types present within T. cruzi. Heterogeneity within copies of the ribosomal 18S within a single genome has therefore been demonstrated and interestingly, this dimorphic arrangement was also present in the outgroup taxa. Presumably the ancestral duplicative event that led to the divergent 18S types preceded that of speciation within this group. These divergent 18S paralogues may have, or had, different functional pressures or rates of molecular evolution. Whether or not these divergent types are equally transcriptionally active throughout the life cycle, remain to be assessed.

Credit risk contributions under the Vasicek one-factor model: a fast wavelet expansion approximation

To measure the contribution of individual transactions inside the total risk of a credit portfolio is a major issue in financial institutions. VaR Contributions (VaRC) and Expected Shortfall Contributions (ESC) have become two popular ways of quantifying the risks. However, the usual Monte Carlo (MC) approach is known to be a very time consuming method for computing these risk contributions. In this paper we consider the Wavelet Approximation (WA) method for Value at Risk (VaR) computation presented in [Mas10] in order to calculate the Expected Shortfall (ES) and the risk contributions under the Vasicek one-factor model framework. We decompose the VaR and the ES as a sum of sensitivities representing the marginal impact on the total portfolio risk. Moreover, we present technical improvements in the Wavelet Approximation (WA) that considerably reduce the computational effort in the approximation while, at the same time, the accuracy increases.

Analysis of parity between protein-based electrophoretic methods for the characterization of oral Candida species

Electrophoretic studies of multilocus-enzymes (MLEE) and whole-cell protein (SDS-PAGE) were carried out in order to evaluate the parity between different methods for the characterization of five Candida species commonly isolated from oral cavity of humans by numerical taxonomy methods. The obtained data revealed that sodium dodecyl sulfate polyacrylamide gel electrophoresis is more efficient in grouping strains in their respective species while MLEE has much limited resolution in organizing all strains in their respective species-specific clusters. MLEE technique must be regarded for surveys in which just one species of Candida is involved.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.

Muscle recovery after repair of short and long peripheral nerve gaps using fibrin conduits.

Peripheral nerve injuries with loss of nervous tissue are a significant clinical problem and are currently treated using autologous nerve transplants. To avoid the need for donor nerve, which results in additional morbidity such as loss of sensation and scarring, alternative bridging methods have been sought. Recently we showed that an artificial nerve conduit moulded from fibrin glue is biocompatible to nerve regeneration. In this present study, we have used the fibrin conduit or a nerve graft to bridge either a 10 mm or 20 mm sciatic nerve gap and analyzed the muscle recovery in adult rats after 16 weeks. The gastrocnemius muscle weights of the operated side were similar for both gap sizes when treated with nerve graft. In contrast, muscle weight was 48.32 ± 4.96% of the contra-lateral side for the 10 mm gap repaired with fibrin conduit but only 25.20 ± 2.50% for the 20 mm gap repaired with fibrin conduit. The morphology of the muscles in the nerve graft groups showed an intact, ordered structure, with the muscle fibers grouped in fascicles whereas the 20 mm nerve gap fibrin group had a more chaotic appearance. The mean area and diameter of fast type fibers in the 20 mm gap repaired with fibrin conduits were significantly (P<0.01) worse than those of the corresponding 10 mm gap group. In contrast, both gap sizes treated with nerve graft showed similar fiber size. Furthermore, the 10 mm gaps repaired with either nerve graft or fibrin conduit showed similar muscle fiber size. These results indicate that the fibrin conduit can effectively treat short nerve gaps but further modification such as the inclusion of regenerative cells may be required to attain the outcomes of nerve graft for long gaps.

Test methods: anabolics.

In the International Olympic Committee (IOC) accredited laboratories, specific methods have been developed to detect anabolic steroids in athletes' urine. The technique of choice to achieve this is gas-chromatography coupled with mass spectrometry (GC-MS). In order to improve the efficiency of anti-doping programmes, the laboratories have defined new analytical strategies. The final sensitivity of the analytical procedure can be improved by choosing new technologies for use in detection, such as tandem mass spectrometry (MS-MS) or high resolution mass spectrometry (HRMS). A better sample preparation using immuno-affinity chromatography (IAC) is also a good tool for improving sensitivity. These techniques are suitable for the detection of synthetic anabolic steroids whose structure is not found naturally in the human body. The more and more evident use, on a large scale, of substances chemically similar to the endogenous steroids obliges both the laboratory and the sports authorities to use the steroid profile of the athlete in comparison with reference ranges from a population or with intraindividual reference values.

Hepatitis C prevalence and risk factors in hemodialysis patients in Central Brazil: a survey by polymerase chain reaction and serological methods

An hemodialysis population in Central Brazil was screened by polymerase chain reaction (PCR) and serological methods to assess the prevalence of hepatitis C virus (HCV) infection and to investigate associated risk factors. All hemodialysis patients (n=428) were interviewed in eight dialysis units in Goiânia city. Blood samples were collected and serum samples screened for anti-HCV antibodies by an enzyme-linked immunosorbent assay (ELISA). Positive samples were retested for confirmation with a line immunoassay (LIA). All samples were also tested for HCV RNA by the PCR. An overall prevalence of 46.7% (CI 95%: 42-51.5) was found, ranging from 20.7% (CI 95%: 8.8-38.1) to 90.4% (CI 95%: 79.9-96.4) depending on the dialysis unit. Of the 428 patients, 185 were found to be seropositive by ELISA, and 167 were confirmed positive by LIA, resulting in an anti-HCV prevalence of 39%. A total of 131 patients were HCV RNA-positive. HCV viremia was present in 63.5% of the anti-HCV-positive patients and in 10.3% of the anti-HCV-negative patients. Univariate analysis of risk factors showed that the number of previous blood transfusions, transfusion of blood before mandatory screening for anti-HCV, length of time on hemodialysis, and treatment in multiple units were associated with HCV positivity. However, multivariate analysis revealed that blood transfusion before screening for anti-HCV and length of time on hemodialysis were significantly associated with HCV infection in this population. These data suggest that nosocomial transmission may play a role in the spread of HCV in the dialysis units studied. In addition to anti-HCV screening, HCV RNA detection is necessary for the diagnosis of HCV infection in hemodialysis patients.