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1.  Kinematic Gait Analysis Using Inertial Sensors with Subjects after Stroke in Two Different Arteries 
Journal of Physical Therapy Science  2014;26(8):1307-1311.
[Purpose] The aim of the present study was described the kinematic characteristics of gait in stroke patients with two different arteries involved. [Subjects and Methods] Two patients who had suffered a basilar (A) or middle (B) cerebral artery ischemic stroke were compared with a control (C). Seventeen inertial sensors were used with acquisition rate of 120 Hz. The participants walked 3 times on a 10 meter walkway. From the raw data, the three gait cycles from the middle of each trial were chosen and analyzed. [Results] During the stance phase, patients A and B had a lower hip angle at initial contact and maximum flexion angle during load response than the control. Patient A and the control subject had similar knee angle values at initial contact, and patient B presented a flexed position in the initial phase of the gait cycle. The maximum flexion angles during loading response were also higher for patient B. The sagittal plane excursion for the ankle joint was lower for patient B in comparison with the other subjects. [Conclusion] Differences during walking between patients who had stroke in different arteries may be related to an alternative compensatory strategy. Patient A and the control subject had similar gait cycle curves at all joints, while patient B showed a rigid synergic pattern.
PMCID: PMC4155242  PMID: 25202203
Stroke; Gait; Kinematic
2.  The First Steps of Adaptation of Escherichia coli to the Gut Are Dominated by Soft Sweeps 
PLoS Genetics  2014;10(3):e1004182.
The accumulation of adaptive mutations is essential for survival in novel environments. However, in clonal populations with a high mutational supply, the power of natural selection is expected to be limited. This is due to clonal interference - the competition of clones carrying different beneficial mutations - which leads to the loss of many small effect mutations and fixation of large effect ones. If interference is abundant, then mechanisms for horizontal transfer of genes, which allow the immediate combination of beneficial alleles in a single background, are expected to evolve. However, the relevance of interference in natural complex environments, such as the gut, is poorly known. To address this issue, we have developed an experimental system which allows to uncover the nature of the adaptive process as Escherichia coli adapts to the mouse gut. This system shows the invasion of beneficial mutations in the bacterial populations and demonstrates the pervasiveness of clonal interference. The observed dynamics of change in frequency of beneficial mutations are consistent with soft sweeps, where different adaptive mutations with similar phenotypes, arise repeatedly on different haplotypes without reaching fixation. Despite the complexity of this ecosystem, the genetic basis of the adaptive mutations revealed a striking parallelism in independently evolving populations. This was mainly characterized by the insertion of transposable elements in both coding and regulatory regions of a few genes. Interestingly, in most populations we observed a complete phenotypic sweep without loss of genetic variation. The intense clonal interference during adaptation to the gut environment, here demonstrated, may be important for our understanding of the levels of strain diversity of E. coli inhabiting the human gut microbiota and of its recombination rate.
Author Summary
Adaptation to novel environments involves the accumulation of beneficial mutations. If these are rare the process will proceed slowly with each one sweeping to fixation on its own. On the contrary if they are common in clonal populations, individuals carrying different beneficial alleles will experience intense competition and only those clones carrying the stronger effect mutations will leave a future line of descent. This phenomenon is known as clonal interference and the extent to which it occurs in natural environments is unknown. One of the most complex natural environments for E. coli is the mammalian intestine, where it evolves in the presence of many species comprising the gut microbiota. We have studied the dynamics of adaptation of E. coli populations evolving in this relevant ecosystem. We show that clonal interference is pervasive in the mouse gut and that the targets of natural selection are similar in independently E. coli evolving populations. These results illustrate how experimental evolution in natural environments allows us to dissect the mechanisms underlying adaptation and its complex dynamics and further reveal the importance of mobile genetic elements in contributing to the adaptive diversification of bacterial populations in the gut.
PMCID: PMC3945185  PMID: 24603313
3.  Isolation and functional characterization of a cotton ubiquitination-related promoter and 5'UTR that drives high levels of expression in root and flower tissues 
BMC Biotechnology  2011;11:115.
Cotton (Gossypium spp.) is an important crop worldwide that provides raw material to 40% of the textile fiber industry. Important traits have been studied aiming the development of genetically modified crops including resistance to insect and diseases, and tolerance to drought, cold and herbicide. Therefore, the characterization of promoters and regulatory regions is also important to achieve high gene expression and/or a specific expression pattern. Commonly, genes involved in ubiquitination pathways are highly and differentially expressed. In this study, we analyzed the expression of a cotton ubiquitin-conjugating enzyme (E2) family member with no previous characterization.
Nucleotide analysis revealed high identity with cotton E2 homologues. Multiple alignment showed a premature stop codon, which prevents the encoding of the conserved cysteine residue at the E2 active site, and an intron that is spliced in E2 homologues, but not in GhGDRP85. The GhGDRP85 gene is highly expressed in different organs of cotton plants, and has high transcript levels in roots. Its promoter (uceApro2) and the 5'UTR compose a regulatory region named uceA1.7, and were isolated from cotton and studied in Arabidopsis thaliana. uceA1.7 shows strong expression levels, equaling or surpassing the expression levels of CaMV35S. The uceA1.7 regulatory sequence drives GUS expression 7-fold higher in flowers, 2-fold in roots and at similar levels in leaves and stems. GUS expression levels are decreased 7- to 15-fold when its 5'UTR is absent in uceApro2.
uceA1.7 is a strong constitutive regulatory sequence composed of a promoter (uceApro2) and its 5'UTR that will be useful in genetic transformation of dicots, having high potential to drive high levels of transgene expression in crops, particularly for traits desirable in flower and root tissues.
PMCID: PMC3239415  PMID: 22115195
4.  Communication Structure of Cortical Networks 
Large-scale cortical networks exhibit characteristic topological properties that shape communication between brain regions and global cortical dynamics. Analysis of complex networks allows the description of connectedness, distance, clustering, and centrality that reveal different aspects of how the network's nodes communicate. Here, we focus on a novel analysis of complex walks in a series of mammalian cortical networks that model potential dynamics of information flow between individual brain regions. We introduce two new measures called absorption and driftness. Absorption is the average length of random walks between any two nodes, and takes into account all paths that may diffuse activity throughout the network. Driftness is the ratio between absorption and the corresponding shortest path length. For a given node of the network, we also define four related measurements, namely in- and out-absorption as well as in- and out-driftness, as the averages of the corresponding measures from all nodes to that node, and from that node to all nodes, respectively. We find that the cat thalamo-cortical system incorporates features of two classic network topologies, Erdös–Rényi graphs with respect to in-absorption and in-driftness, and configuration models with respect to out-absorption and out-driftness. Moreover, taken together these four measures separate the network nodes based on broad functional roles (visual, auditory, somatomotor, and frontolimbic).
PMCID: PMC3052476  PMID: 21427794
complex networks; cortical networks; Markov chains; accessibility

Results 1-4 (4)