Examining the cancellation mechanism of neutron EDM in a model with dilaton-dominated susy breaking

We examine the cancellation mechanism between the different contributions to the electric dipole moment of the neutron in a model with dilaton-dominated SUSY breaking. We find these accidental cancellations occur at few points in parameter space. For a wide region of this space we must constrain the phase of $\mu$ to be of order $10^{-1}$ and have the phases of $A$ and $\mu$ strongly correlated in order to have small neutron EDM. Moreover, we consider the indirect CP violation parameter $\epsilon$ in this region where the electric dipole moment is less than the experimental limit and find that we can generate $\epsilon$ of order $10^{-6}$

On the EDM Cancellations in D-brane models

We analyze the possibility of simultaneous electron, neutron, and mercury electric dipole moment (EDM) cancellations in the mSUGRA and D--brane models. We find that the mercury EDM constraint practically rules out the cancellation scenario in D-brane models whereas in the context of mSUGRA it is still allowed with some fine-tuning.Comment: 10 pages, to appear in Phys. Rev. Let

From Behavioral and Communication Intervention to Interaction Design: User Perspectives from Clinicians

To improve functional communication and behavioral management, many children with disabilities receive behavioral and communication-related intervention from professionals such as behavioral analysts and speech and language therapists. This paper presents user perspectives from three clinicians who have used and/or designed assistive technology with children with disabilities, and calls for researchers to recognize and leverage clinicians' knowledge to design accessible technology for children with complex sensory and communication needs

Understanding the Situated Practices of School Technology Leaders in the Early Stages of Educational Technology Adoption

School-driven technological innovation has the potential to positively impact on classroom practice, yet it can also be disrupted by incompatibilities between the existing school ecology and new educational technologies. To help mitigate this disruption a particular staff member often takes on a facilitative leadership role to champion new technology initiatives. However little is known about how this technology leader role impacts on the adoption of new technologies in the classroom. Taking a situated lens, we embarked on a multiple case study of four schools who were aiming to adopt a new literacy game in the classroom. Through interviews with technology leaders and fieldnotes from our site observations, we systematically analysed their actions and concerns over two academic terms. This highlighted an overwhelming concern with managing the material dimension of the technology, teacher agency and division of labour and mechanisms for communication and monitoring. Our findings raise important considerations for HCI researchers seeking to embed their technologies into practice alongside recommendations for supporting leaders tasked with coordinating this process

Inferring gene regulatory networks from gene expression data by a dynamic Bayesian network-based model

Enabled by recent advances in bioinformatics, the inference of gene regulatory networks (GRNs) from gene expression data has garnered much interest from researchers. This is due to the need of researchers to understand the dynamic behavior and uncover the vast information lay hidden within the networks. In this regard, dynamic Bayesian network (DBN) is extensively used to infer GRNs due to its ability to handle time-series microarray data and modeling feedback loops. However, the efficiency of DBN in inferring GRNs is often hampered by missing values in expression data, and excessive computation time due to the large search space whereby DBN treats all genes as potential regulators for a target gene. In this paper, we proposed a DBN-based model with missing values imputation to improve inference efficiency, and potential regulators detection which aims to lessen computation time by limiting potential regulators based on expression changes. The performance of the proposed model is assessed by using time-series expression data of yeast cell cycle. The experimental results showed reduced computation time and improved efficiency in detecting gene-gene relationships

Inferring gene regulatory networks from gene expression data by a dynamic Bayesian network-based model

Enabled by recent advances in bioinformatics, the inference of gene regulatory networks (GRNs) from gene expression data has garnered much interest from researchers. This is due to the need of researchers to understand the dynamic behavior and uncover the vast information lay hidden within the networks. In this regard, dynamic Bayesian network (DBN) is extensively used to infer GRNs due to its ability to handle time-series microarray data and modeling feedback loops. However, the efficiency of DBN in inferring GRNs is often hampered by missing values in expression data, and excessive computation time due to the large search space whereby DBN treats all genes as potential regulators for a target gene. In this paper, we proposed a DBN-based model with missing values imputation to improve inference efficiency, and potential regulators detection which aims to lessen computation time by limiting potential regulators based on expression changes. The performance of the proposed model is assessed by using time-series expression data of yeast cell cycle. The experimental results showed reduced computation time and improved efficiency in detecting gene-gene relationships

NRF2 regulates HER1 signaling pathway to modulate the sensitivity of ovarian cancer cells to lapatinib and erlotinib

NF-E2-related factor 2 (NRF2) regulates the transcription of a battery of metabolic and cytoprotective genes. NRF2 and epidermal growth factor receptors (EGFRs/HERs) are regulators of cellular proliferation and determinants of cancer initiation and progression. NRF2 and HERs confer cancers with resistance to several therapeutic agents. Nevertheless, there is limited understanding of the regulation of HER expression and activation and the link between NRF2 and HER signalling pathways. We show that NRF2 regulates both basal and inducible expression of HER1, as treatment of ovarian cancer cells (PEO1, OVCAR3, and SKOV3) with NRF2 activator tBHQ inducing HER1, while inhibition of NRF2 by siRNA knockdown or with retinoid represses HER1. Furthermore, treatment of cells with tBHQ increased total and phosphorylated NRF2, HER1, and AKT levels and compromised the cytotoxic effect of lapatinib or erlotinib. Treatment with siRNA or retinoid antagonised the effect of tBHQ on NRF2 and HER1 levels and enhanced the sensitivity of ovarian cancer cells to lapatinib or erlotinib. Pharmacological or genetic inhibition of NRF2 and/or treatment with lapatinib or erlotinib elevated cellular ROS and depleted glutathione. This extends the understanding of NRF2 and its regulation of HER family receptors and opens a strategic target for improving cancer therapy

Weak Isospin Violations in Charged and Neutral Higgs Couplings from SUSY Loop Corrections

Supersymmetric QCD and supersymmetric electroweak loop corrections to the violations of weak isospin to Yukawa couplings are investigated. Specifically it involves an analysis of the supersymmetric loop corrections to the Higgs couplings to the third generation quarks and leptons. Here we analyze the SUSY loop corrections to the charged Higgs couplings which are then compared with the supersymmetric loop corrections to the neutral Higgs couplings previously computed. It is found that the weak isospin violations can be quite significant, i.e, as much as 40-50% or more of the total loop correction to the Yukawa coupling. The effects of CP phases are also studied and it is found that these effects can either enhance or suppress the weak isospin violations. We also investigate the weak isospin violation effects on the branching ratio $BR(H^-\to\bar t b)/ BR(H^-\to \bar\nu_{\tau}\tau^-)$ and show that the effects are sensitive to CP phases. Thus an accurate measurement of this branching ratio along with the branching ratio of the neutral Higgs boson decays can provide a measure of weak isospin violation along with providing a clue to the presence of supersymmetry.Comment: 20 pages, 9 figure

Phenotypic Properties of Collagen in Dentinogenesis Imperfecta Associated with Osteogenesis Imperfecta

Introduction: Dentinogenesis imperfecta type 1 (OIDI) is considered a relatively rare genetic disorder (1:5000 to 1:45,000) associated with osteogenesis imperfecta. OIDI impacts the formation of collagen fibrils in dentin, leading to morphological and structural changes that affect the strength and appearance of teeth. However, there is still a lack of understanding regarding the nanoscale characterization of the disease, in terms of collagen ultrastructure and mechanical properties. Therefore, this research presents a qualitative and quantitative report into the phenotype and characterization of OIDI in dentin, by using a combination of imaging, nanomechanical approaches. Methods: For this study, 8 primary molars from OIDI patients and 8 primary control molars were collected, embedded in acrylic resin and cut into longitudinal sections. Sections were then demineralized in 37% phosphoric acid using a protocol developed in-house. Initial experiments demonstrated the effectiveness of the demineralization protocol, as the ATR-FTIR spectral fingerprints showed an increase in the amide bands together with a decrease in phosphate content. Structural and mechanical analyses were performed directly on both the mineralized and demineralized samples using a combination of scanning electron microscopy, atomic force microscopy, and Wallace indentation. Results: Mesoscale imaging showed alterations in dentinal tubule morphology in OIDI patients, with a reduced number of tubules and a decreased tubule diameter compared to healthy controls. Nanoscale collagen ultrastructure presented a similar D-banding periodicity between OIDI and controls. Reduced collagen fibrils diameter was also recorded for the OIDI group. The hardness of the (mineralized) control dentin was found to be significantly higher (p<0.05) than that of the OIDI (mineralized) dentine. Both the exposed peri- and intratubular dentinal collagen presented bimodal elastic behaviors (Young's moduli). The control samples presented a stiffening of the intratubular collagen when compared to the peritubular collagen. In case of the OIDI, this stiffening in the collagen between peri- and intratubular dentinal collagen was not observed and the exposed collagen presented overall a lower elasticity than the control samples. Conclusion: This study presents a systematic approach to the characterization of collagen structure and properties in OIDI as diagnosed in dentin. Structural markers for OIDI at the mesoscale and nanoscale were found and correlated with an observed lack of increased elastic moduli of the collagen fibrils in the intratubular OIDI dentin. These findings offer an explanation of how structural changes in the dentin could be responsible for the failure of some adhesive restorative materials as observed in patients affected by OIDI

Unhappiness, health and cognitive ability in old age

Background To test whether scores on depression inventories on entry to a longitudinal study predict mental ability over the next 4–16 years. Method Associations between scores on the Beck Depression Inventory and on tests of intelligence, vocabulary and memory were analysed in 5070 volunteers aged 49–93 years after differences in prescribed drug consumption, death and drop-out, sex, socio-economic advantage and recruitment cohort effects had also been considered. Results On all cognitive tasks Beck scores on entry, even in the range 0–7 indicating differences in above average contentment, affected overall levels of cognitive performance but not rates of age-related cognitive decline suggesting effects of differences in life satisfaction rather than in depression. Conclusions A new finding is that, in old age, increments in life satisfaction are associated with better cognitive performance. Implications for interpreting associations between depression inventory scores and cognitive performance in elderly samples are discussed