On the General Analytical Solution of the Kinematic Cosserat Equations

Based on a Lie symmetry analysis, we construct a closed form solution to the kinematic part of the (partial differential) Cosserat equations describing the mechanical behavior of elastic rods. The solution depends on two arbitrary analytical vector functions and is analytical everywhere except a certain domain of the independent variables in which one of the arbitrary vector functions satisfies a simple explicitly given algebraic relation. As our main theoretical result, in addition to the construction of the solution, we proof its generality. Based on this observation, a hybrid semi-analytical solver for highly viscous two-way coupled fluid-rod problems is developed which allows for the interactive high-fidelity simulations of flagellated microswimmers as a result of a substantial reduction of the numerical stiffness.Comment: 14 pages, 3 figure

Setting limits on Effective Field Theories: the case of Dark Matter

The usage of Effective Field Theories (EFT) for LHC new physics searches is receiving increasing attention. It is thus important to clarify all the aspects related with the applicability of the EFT formalism in the LHC environment, where the large available energy can produce reactions that overcome the maximal range of validity, i.e. the cutoff, of the theory. We show that this does forbid to set rigorous limits on the EFT parameter space through a modified version of the ordinary binned likelihood hypothesis test, which we design and validate. Our limit-setting strategy can be carried on in its full-fledged form by the LHC experimental collaborations, or performed externally to the collaborations, through the Simplified Likelihood approach, by relying on certain approximations. We apply it to the recent CMS mono-jet analysis and derive limits on a Dark Matter (DM) EFT model. DM is selected as a case study because the limited reach on the DM production EFT Wilson coefficient and the structure of the theory suggests that the cutoff might be dangerously low, well within the LHC reach. However our strategy can also be applied to EFT's parametrising the indirect effects of heavy new physics in the Electroweak and Higgs sectors

Transcriptional and functional profilling of human embryonic stem cell-derived cardiomyocytes

Human embryonic stemcells (hESCs) can serve as a potentially limitless source of cells that may enable regeneration of diseased tissue and organs. Here we investigate the use of human embryonic stemcell-derived cardiomyocytes (hESC-CMs) in promoting recovery from cardiac ischemia reperfusion injury in a mouse model. Using microarrays, we have described the hESC-CM transcriptome within the spectrum of changes that occur between undifferentiated hESCs and fetal heart cells. The hESC-CMs expressed cardiomyocyte genes at levels similar to those found in 20-week fetal heart cells, making this population a good source of potential replacement cells in vivo. Echocardiographic studies showed significant improvement in heart function by 8 weeks after transplantation. Finally, we demonstrate long-term engraftment of hESC-CMs by using molecular imaging to track cellular localization, survival, and proliferation in vivo. Taken together, global gene expression profiling of hESC differentiation enables a systems-based analysis of the biological processes, networks, and genes that drive hESC fate decisions, and studies such as this will serve as the foundation for future clinical applications of stem cell therapies. © 2008 Cao et al.published_or_final_versio

Remineralization of demineralized dentin using a dual analog system.

ObjectiveImproved methods are needed to remineralize dentin caries in order to promote conservation of dentin tissue and minimize the surgical interventions that are currently required for clinical treatment. Here, we test the hypothesis that bulk substrates can be effectively mineralized via a dual analog system proposed by others, using a tripolyphosphate (TPP) "templating analog" and a poly(acrylic acid) (PAA) or poly(aspartic acid) (pAsp) "sequestration analog," the latter of which generates the polymer-induced liquid-precursor (PILP) mineralization process studied in our laboratory.Material & methodsDemineralized human dentin slices were remineralized with and without pre-treatment with TPP, using either PAA or pAsp as the PILP process-directing agent. A control experiment with no polymer present was used for comparison.ResultsNo mineralization was observed in any of the PAA groups. In both the pAsp and no polymer groups, TPP inhibited mineralization on the surfaces of the specimens but promoted mineralization within the interiors. Pre-treatment with TPP enhanced overall mineralization of the pAsp group. However, when analysed via TEM, regions with little mineral were still present.ConclusionPoly(acrylic acid) was unable to remineralize demineralized dentin slices under the conditions employed, even when pre-treated with TPP. However, pre-treatment with TPP enhanced overall mineralization of specimens that were PILP-remineralized using pAsp

Health-related quality of life as measured with EQ-5D among populations with and without specific chronic conditions: A population-based survey in Shaanxi province, China

© 2013 Tan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Introduction: The aim of this study was to examine health-related quality of life (HRQoL) as measured by EQ-5D and to investigate the influence of chronic conditions and other risk factors on HRQoL based on a distributed sample located in Shaanxi Province, China. Methods: A multi-stage stratified cluster sampling method was performed to select subjects. EQ-5D was employed to measure the HRQoL. The likelihood that individuals with selected chronic diseases would report any problem in the EQ-5D dimensions was calculated and tested relative to that of each of the two reference groups. Multivariable linear regression models were used to investigate factors associated with EQ VAS. Results: The most frequently reported problems involved pain/discomfort (8.8%) and anxiety/depression (7.6%). Nearly half of the respondents who reported problems in any of the five dimensions were chronic patients. Higher EQ VAS scores were associated with the male gender, higher level of education, employment, younger age, an urban area of residence, access to free medical service and higher levels of physical activity. Except for anemia, all the selected chronic diseases were indicative of a negative EQ VAS score. The three leading risk factors were cerebrovascular disease, cancer and mental disease. Increases in age, number of chronic conditions and frequency of physical activity were found to have a gradient effect. Conclusion: The results of the present work add to the volume of knowledge regarding population health status in this area, apart from the known health status using mortality and morbidity data. Medical, policy, social and individual attention should be given to the management of chronic diseases and improvement of HRQoL. Longitudinal studies must be performed to monitor changes in HRQoL and to permit evaluation of the outcomes of chronic disease intervention programs. © 2013 Tan et al.National Nature Science Foundation (No. 8107239

Gravitational Chern-Simons Lagrangians and black hole entropy

We analyze the problem of defining the black hole entropy when Chern-Simons terms are present in the action. Extending previous works, we define a general procedure, valid in any odd dimensions both for purely gravitational CS terms and for mixed gauge-gravitational ones. The final formula is very similar to Wald's original formula valid for covariant actions, with a significant modification. Notwithstanding an apparent violation of covariance we argue that the entropy formula is indeed covariant.Comment: 39 page

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

Evidence of a metabolic memory to early-life dietary restriction in male C57BL/6 mice

&lt;p&gt;Background: Dietary restriction (DR) extends lifespan and induces beneficial metabolic effects in many animals. What is far less clear is whether animals retain a metabolic memory to previous DR exposure, that is, can early-life DR preserve beneficial metabolic effects later in life even after the resumption of ad libitum (AL) feeding. We examined a range of metabolic parameters (body mass, body composition (lean and fat mass), glucose tolerance, fed blood glucose, fasting plasma insulin and insulin-like growth factor 1 (IGF-1), insulin sensitivity) in male C57BL/6 mice dietary switched from DR to AL (DR-AL) at 11 months of age (mid life). The converse switch (AL-DR) was also undertaken at this time. We then compared metabolic parameters of the switched mice to one another and to age-matched mice maintained exclusively on an AL or DR diet from early life (3 months of age) at 1 month, 6 months or 10 months post switch.&lt;/p&gt; &lt;p&gt;Results: Male mice dietary switched from AL-DR in mid life adopted the metabolic phenotype of mice exposed to DR from early life, so by the 10-month timepoint the AL-DR mice overlapped significantly with the DR mice in terms of their metabolic phenotype. Those animals switched from DR-AL in mid life showed clear evidence of a glycemic memory, with significantly improved glucose tolerance relative to mice maintained exclusively on AL feeding from early life. This difference in glucose tolerance was still apparent 10 months after the dietary switch, despite body mass, fasting insulin levels and insulin sensitivity all being similar to AL mice at this time.&lt;/p&gt; &lt;p&gt;Conclusions: Male C57BL/6 mice retain a long-term glycemic memory of early-life DR, in that glucose tolerance is enhanced in mice switched from DR-AL in mid life, relative to AL mice, even 10 months following the dietary switch. These data therefore indicate that the phenotypic benefits of DR are not completely dissipated following a return to AL feeding. The challenge now is to understand the molecular mechanisms underlying these effects, the time course of these effects and whether similar interventions can confer comparable benefits in humans.&lt;/p&gt

Caspase-2 is upregulated after sciatic nerve transection and its inhibition protects dorsal root ganglion neurons from Apoptosis after serum withdrawal

Sciatic nerve (SN) transection-induced apoptosis of dorsal root ganglion neurons (DRGN) is one factor determining the efficacy of peripheral axonal regeneration and the return of sensation. Here, we tested the hypothesis that caspase-2(CASP2) orchestrates apoptosis of axotomised DRGN both in vivo and in vitro by disrupting the local neurotrophic supply to DRGN. We observed significantly elevated levels of cleaved CASP2 (C-CASP2), compared to cleaved caspase-3 (C-CASP3), within TUNEL+DRGN and DRG glia (satellite and Schwann cells) after SN transection. A serum withdrawal cell culture model, which induced 40% apoptotic death in DRGN and 60% in glia, was used to model DRGN loss after neurotrophic factor withdrawal. Elevated C-CASP2 and TUNEL were observed in both DRGN and DRG glia, with C-CASP2 localisation shifting from the cytosol to the nucleus, a required step for induction of direct CASP2-mediated apoptosis. Furthermore, siRNAmediated downregulation of CASP2 protected 50% of DRGN from apoptosis after serum withdrawal, while downregulation of CASP3 had no effect on DRGN or DRG glia survival. We conclude that CASP2 orchestrates the death of SN-axotomised DRGN directly and also indirectly through loss of DRG glia and their local neurotrophic factor support. Accordingly, inhibiting CASP2 expression is a potential therapy for improving both the SN regeneration response and peripheral sensory recovery

Retinal image enhancement via a multiscale morphological approach with OCCO filter.

Retinal images are widely used for diagnosis and eye disease detection. However, due to the acquisition process, retinal images often have problems such as low contrast, blurry details or artifacts. These problems may severely affect the diagnosis. Therefore, it is very impor tant to enhance the visual quality of such images. Contrast enhancement is a pre-processing applied to images to improve their visual quality. This technique betters the identification of retinal structures in degraded reti nal images. In this work, a novel algorithm based on multi-scale mathe matical morphology is presented. First, the original image is blurred us ing the Open-Close Close-Open (OCCO) filter to reduce any artifacts in the image. Next, multiple bright and dark features are extracted from the filtered image by the Top-Hat transform. Finally, the maximum bright values are added to the original image and the maximum dark values are subtracted from the original image, previously adjusted by a weight. The algorithm was tested on 397 retinal images from the public STARE database. The proposed algorithm was compared with state of the art al gorithms and results show that the proposal is more efficient in improving contrast, maintaining similarity with the original image and introducing less distortion than the other algorithms. According to ophthalmologists, the algorithm, by improving retinal images, provides greater clarity in the blood vessels of the retina and would facilitate the identification of pathologies.CONACYT - Consejo Nacional de Ciencia y TecnologíaPROCIENCI