Movement variability in stroke patients and controls performing two upper limb functional tasks: a new assessment methodology

Background: In the evaluation of upper limb impairment post stroke there remains a gap between detailed kinematic analyses with expensive motion capturing systems and common clinical assessment tests. In particular, although many clinical tests evaluate the performance of functional tasks, metrics to characterise upper limb kinematics are generally not applicable to such tasks and very limited in scope. This paper reports on a novel, user-friendly methodology that allows for the assessment of both signal magnitude and timing variability in upper limb movement trajectories during functional task performance. In order to demonstrate the technique, we report on a study in which the variability in timing and signal magnitude of data collected during the performance of two functional tasks is compared between a group of subjects with stroke and a group of individually matched control subjects. Methods: We employ dynamic time warping for curve registration to quantify two aspects of movement variability: 1) variability of the timing of the accelerometer signals' characteristics and 2) variability of the signals' magnitude. Six stroke patients and six matched controls performed several trials of a unilateral ('drinking') and a bilateral ('moving a plate') functional task on two different days, approximately 1 month apart. Group differences for the two variability metrics were investigated on both days. Results: For 'drinking from a glass' significant group differences were obtained on both days for the timing variability of the acceleration signals' characteristics (p = 0.002 and p = 0.008 for test and retest, respectively); all stroke patients showed increased signal timing variability as compared to their corresponding control subject. 'Moving a plate' provided less distinct group differences. Conclusion: This initial application establishes that movement variability metrics, as determined by our methodology, appear different in stroke patients as compared to matched controls during unilateral task performance ('drinking'). Use of a user-friendly, inexpensive accelerometer makes this methodology feasible for routine clinical evaluations. We are encouraged to perform larger studies to further investigate the metrics' usefulness when quantifying levels of impairment

Resident macrophages influence stem cell activity in the mammary gland

Introduction Macrophages in the mammary gland are essential for morphogenesis of the ductal epithelial tree and have been implicated in promoting breast tumor metastasis. Although it is well established that macrophages influence normal mammopoiesis, the mammary cell types that these accessory cells influence have not been determined. Here we have explored a role for macrophages in regulating mammary stem cell (MaSC) activity, by assessing the ability of MaSCs to reconstitute a mammary gland in a macrophage-depleted fat pad. Methods Two different in vivo models were used to deplete macrophages from the mouse mammary fat pad, allowing us to examine the effect of macrophage deficiency on the mammary repopulating activity of MaSCs. Both the Csf1(op/op) mice and clodronate liposome-mediated ablation models entailed transplantation studies using the MaSC-enriched population. Results We show that mammary repopulating ability is severely compromised when the wild-type MaSC-enriched subpopulation is transplanted into Csf1(op/op) fat pads. In reciprocal experiments, the MaSC-enriched subpopulation from Csf1(op/op) glands had reduced regenerative capacity in a wildtype environment. Utilizing an alternative strategy for selective depletion of macrophages from the mammary gland, we demonstrate that co-implantation of the MaSC-enriched subpopulation with clodronate-liposomes leads to a marked decrease in repopulating frequency and outgrowth potential. Conclusions Our data reveal a key role for mammary gland macrophages in supporting stem/progenitor cell function and suggest that MaSCs require macrophage-derived factors to be fully functional. Macrophages may therefore constitute part of the mammary stem cell nich

I-TRAP: A method to identify transcriptional regulator activated promoters

BACKGROUND: The differential expression of virulence genes is often used by microbial pathogens in adapting to the environment of their host. The differential expression of such sets of genes can be regulated by RNA polymerase sigma factors. Some sigma factors are differentially expressed, which can provide a means to identifying other differentially expressed genes such as those whose expression are controlled by the sigma factor. METHODS: To identify sigma factor-regulated genes, we developed a method, termed I-TRAP, for the identification of transcriptional regulator activated promoters. The I-TRAP method is based on the fact that some genes will be differentially expressed in the presence and absence of a transcriptional regulator. I-TRAP uses a DNA library in a promoter-trap vector that contains two reporter genes, one to allow the selection of active promoters in the presence of the transcriptional regulator and a second to allow screening for promoter activity in the absence of the transcriptional regulator. RESULTS: To illustrate the development and use of the I-TRAP approach, the construction of the vectors, host strains, and library necessary to identify SigmaE-regulated genes of Mycobacterium tuberculosis is described. CONCLUSION: The I-TRAP method should be a versatile and useful method for identifying and characterizing promoter activity under a variety of conditions and in response to various regulatory proteins. In our study, we isolated 360 clones that may contain plasmids carrying SigmaE-regulated promoters genes of M. tuberculosis

Enteric Neural Crest Differentiation in Ganglioneuromas Implicates Hedgehog Signaling in Peripheral Neuroblastic Tumor Pathogenesis

Peripheral neuroblastic tumors (PNTs) share a common origin in the sympathetic nervous system, but manifest variable differentiation and growth potential. Malignant neuroblastoma (NB) and benign ganglioneuroma (GN) stand at opposite ends of the clinical spectrum. We hypothesize that a common PNT progenitor is driven to variable differentiation by specific developmental signaling pathways. To elucidate developmental pathways that direct PNTs along the differentiation spectrum, we compared the expression of genes related to neural crest development in GN and NB. In GNs, we found relatively low expression of sympathetic markers including adrenergic biosynthesis enzymes, indicating divergence from sympathetic fate. In contrast, GNs expressed relatively high levels of enteric neuropeptides and key constituents of the Hedgehog (HH) signaling pathway, including Dhh, Gli1 and Gli3. Predicted HH targets were also differentially expressed in GN, consistent with transcriptional response to HH signaling. These findings indicate that HH signaling is specifically active in GN. Together with the known role of HH activity in enteric neural development, these findings further suggested a role for HH activity in directing PNTs away from the sympathetic lineage toward a benign GN phenotype resembling enteric ganglia. We tested the potential for HH signaling to advance differentiation in PNTs by transducing NB cell lines with Gli1 and determining phenotypic and transcriptional response. Gli1 inhibited proliferation of NB cells, and induced a pattern of gene expression that resembled the differential pattern of gene expression of GN, compared to NB (p<0.00001). Moreover, the transcriptional response of SY5Y cells to Gli1 transduction closely resembled the transcriptional response to the differentiation agent retinoic acid (p<0.00001). Notably, Gli1 did not induce N-MYC expression in neuroblastoma cells, but strongly induced RET, a known mediator of RA effect. The decrease in NB cell proliferation induced by Gli1, and the similarity in the patterns of gene expression induced by Gli1 and by RA, corroborated by closely matched gene sets in GN tumors, all support a model in which HH signaling suppresses PNT growth by promoting differentiation along alternative neural crest pathways

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

The Adjuvanticity of an O. volvulus-Derived rOv-ASP-1 Protein in Mice Using Sequential Vaccinations and in Non-Human Primates

Adjuvants potentiate antigen-specific protective immune responses and can be key elements promoting vaccine effectiveness. We previously reported that the Onchocerca volvulus recombinant protein rOv-ASP-1 can induce activation and maturation of naïve human DCs and therefore could be used as an innate adjuvant to promote balanced Th1 and Th2 responses to bystander vaccine antigens in mice. With a few vaccine antigens, it also promoted a Th1-biased response based on pronounced induction of Th1-associated IgG2a and IgG2b antibody responses and the upregulated production of Th1 cytokines, including IL-2, IFN-γ, TNF-α and IL-6. However, because it is a protein, the rOv-ASP-1 adjuvant may also induce anti-self-antibodies. Therefore, it was important to verify that the host responses to self will not affect the adjuvanticity of rOv-ASP-1 when it is used in subsequent vaccinations with the same or different vaccine antigens. In this study, we have established rOv-ASP-1's adjuvanticity in mice during the course of two sequential vaccinations using two vaccine model systems: the receptor-binding domain (RBD) of SARS-CoV spike protein and a commercial influenza virus hemagglutinin (HA) vaccine comprised of three virus strains. Moreover, the adjuvanticity of rOv-ASP-1 was retained with an efficacy similar to that obtained when it was used for a first vaccination, even though a high level of anti-rOv-ASP-1 antibodies was present in the sera of mice before the administration of the second vaccine. To further demonstrate its utility as an adjuvant for human use, we also immunized non-human primates (NHPs) with RBD plus rOv-ASP-1 and showed that rOv-ASP-1 could induce high titres of functional and protective anti-RBD antibody responses in NHPs. Notably, the rOv-ASP-1 adjuvant did not induce high titer antibodies against self in NHPs. Thus, the present study provided a sound scientific foundation for future strategies in the development of this novel protein adjuvant

Systems Biology by the Rules: Hybrid Intelligent Systems for Pathway Modeling and Discovery

Background: Expert knowledge in journal articles is an important source of data for reconstructing biological pathways and creating new hypotheses. An important need for medical research is to integrate this data with high throughput sources to build useful models that span several scales. Researchers traditionally use mental models of pathways to integrate information and development new hypotheses. Unfortunately, the amount of information is often overwhelming and these are inadequate for predicting the dynamic response of complex pathways. Hierarchical computational models that allow exploration of semi-quantitative dynamics are useful systems biology tools for theoreticians, experimentalists and clinicians and may provide a means for cross-communication. Results: A novel approach for biological pathway modeling based on hybrid intelligent systems or soft computing technologies is presented here. Intelligent hybrid systems, which refers to several related computing methods such as fuzzy logic, neural nets, genetic algorithms, and statistical analysis, has become ubiquitous in engineering applications for complex control system modeling and design. Biological pathways may be considered to be complex control systems, which medicine tries to manipulate to achieve desired results. Thus, hybrid intelligent systems may provide a useful tool for modeling biological system dynamics and computational exploration of new drug targets. A new modeling approach based on these methods is presented in the context of hedgehog regulation of the cell cycle in granule cells. Code and input files can be found at the Bionet website: www.chip.ord/~wbosl/Software/Bionet. Conclusion: This paper presents the algorithmic methods needed for modeling complicated biochemical dynamics using rule-based models to represent expert knowledge in the context of cell cycle regulation and tumor growth. A notable feature of this modeling approach is that it allows biologists to build complex models from their knowledge base without the need to translate that knowledge into mathematical form. Dynamics on several levels, from molecular pathways to tissue growth, are seamlessly integrated. A number of common network motifs are examined and used to build a model of hedgehog regulation of the cell cycle in cerebellar neurons, which is believed to play a key role in the etiology of medulloblastoma, a devastating childhood brain cancer

Persistence of DNA threads in human anaphase cells suggests late completion of sister chromatid decatenation

PICH (Plk1-interacting checkpoint helicase) was recently identified as an essential component of the spindle assembly checkpoint and shown to localize to kinetochores, inner centromeres, and thin threads connecting separating chromosomes even during anaphase. In this paper, we have used immuno-fiber fluorescence in situ hybridization and chromatin-immunoprecipitation to demonstrate that PICH associates with centromeric chromatin during anaphase. Furthermore, by careful analysis of PICH-positive anaphase threads through FISH as well as bromo-deoxyurdine and CREST labeling, we strengthen the evidence that these threads comprise mainly alphoid centromere deoxyribonucleic acid. Finally, by timing the addition of ICRF-193 (a specific inhibitor of topoisomerase-II alpha) to cells synchronized in anaphase, we demonstrate that topoisomerase activity is required specifically to resolve PICH-positive threads during anaphase (as opposed to being required to prevent the formation of such threads during earlier cell cycle stages). These data indicate that PICH associates with centromeres during anaphase and that most PICH-positive threads evolve from inner centromeres as these stretch in response to tension. Moreover, they show that topoisomerase activity is required during anaphase for the resolution of PICH-positive threads, implying that the complete separation of sister chromatids occurs later than previously assumed

Changes in Brain MicroRNAs Contribute to Cholinergic Stress Reactions

Mental stress modifies both cholinergic neurotransmission and alternative splicing in the brain, via incompletely understood mechanisms. Here, we report that stress changes brain microRNA (miR) expression and that some of these stress-regulated miRs regulate alternative splicing. Acute and chronic immobilization stress differentially altered the expression of numerous miRs in two stress-responsive regions of the rat brain, the hippocampal CA1 region and the central nucleus of the amygdala. miR-134 and miR-183 levels both increased in the amygdala following acute stress, compared to unstressed controls. Chronic stress decreased miR-134 levels, whereas miR-183 remained unchanged in both the amygdala and CA1. Importantly, miR-134 and miR-183 share a common predicted mRNA target, encoding the splicing factor SC35. Stress was previously shown to upregulate SC35, which promotes the alternative splicing of acetylcholinesterase (AChE) from the synapse-associated isoform AChE-S to the, normally rare, soluble AChE-R protein. Knockdown of miR-183 expression increased SC35 protein levels in vitro, whereas overexpression of miR-183 reduced SC35 protein levels, suggesting a physiological role for miR-183 regulation under stress. We show stress-induced changes in miR-183 and miR-134 and suggest that, by regulating splicing factors and their targets, these changes modify both alternative splicing and cholinergic neurotransmission in the stressed brain