1,990 research outputs found
Sphingosine kinase 1 in breast cancer: A new molecular marker and a therapy target
It is now well-established that sphingosine kinase 1 (SK1) plays a significant role in breast cancer development, progression, and spread, whereas SK1 knockdown can reverse these processes. In breast cancer cells and tumors, SK1 was shown to interact with various pathways involved in cell survival and chemoresistance, such as nuclear factor-kappa B (NFκB), Notch, Ras/MAPK, PKC, and PI3K. SK1 is upregulated by estrogen signaling, which, in turn, confers cancer cells with resistance to tamoxifen. Sphingosine-1-phosphate (S1P) produced by SK1 has been linked to tumor invasion and metastasis. Both SK1 and S1P are closely linked to inflammation and adipokine signaling in breast cancer. In human tumors, high SK1 expression has been linked with poorer survival and prognosis. SK1 is upregulated in triple negative tumors and basal-like subtypes. It is often associated with high phosphorylation levels of ERK1/2, SFK, LYN, AKT, and NFκB. Higher tumor SK1 mRNA levels were correlated with poor response to chemotherapy. This review summarizes the up-to-date evidence and discusses the therapeutic potential for the SK1 inhibition in breast cancer, with emphasis on the mechanisms of chemoresistance and combination with other therapies such as gefitinib or docetaxel. We have outlined four key areas for future development, including tumor microenvironment, combination therapies, and nanomedicine. We conclude that SK1 may have a potential as a target for precision medicine, its high expression being a negative prognostic marker in ER-negative breast cancer, as well as a target for chemosensitization therapy
A study to trial the use of inertial non-optical motion capture for ergonomic analysis of manufacturing work
It is going to be increasingly important for manufacturing system designers to incorporate human activity data and ergonomic analysis with other performance data in digital design modelling and system monitoring. However, traditional methods of capturing human activity data are not sufficiently accurate to meet the needs of digitised data analysis; qualitative data are subject to bias and imprecision, and optically derived data are hindered by occlusions caused by structures or other people in a working environment. Therefore, to meet contemporary needs for more accurate and objective data, inertial non-optical methods of measurement appear to offer a solution. This article describes a case study conducted within the aerospace manufacturing industry, where data on the human activities involved in aircraft wing system installations was first collected via traditional ethnographic methods and found to have limited accuracy and suitability for digital modelling, but similar human activity data subsequently collected using an automatic non-optical motion capture system in a more controlled environment showed better suitability. Results demonstrate the potential benefits of applying not only the inertial non-optical method in future digital modelling and performance monitoring but also the value of continuing to include qualitative analysis for richer interpretation of important explanatory factors
A critical evaluation of the law of provocation and proposals for its reform
In 2005, the Home Secretary commissioned a new review of the law of murder, with a view to ''resolving many of the recognised problems"^ These centred on the breadth of conduct, and the implications for the 'mandatory life' sentence, both as punishment in law, and as a social label in marking out the gravest offenders against society. It is against these difficulties that the partial defence of provocation has struggled to reliably reflect the reduced culpability of those who kill when provoked to a loss of self-control, particularly concerning situations of domestic violence. The controversial House of Lords decision in Smith led to a separate review of the partial defences. This thesis first considers the definition and scope of problems facing murder and their reform, in establishing the wider framework within which provocation must operate. It then examines problems facing present provocation, assessing the different options for reform, and introducing the experiences of other states. The previous reform dialogue suffered from an absence of common values, and so the different reform options for provocation are assessed through the application of specific criteria, enabling more objective and authoritative conclusions. These conclusions are then reassessed in light of the recommendations made regarding the reform of murder
A Compressed Sensing Approach to Detect Immobilized Nanoparticles Using Superparamagnetic Relaxometry
Superparamagnetic relaxometry (SPMR) is an emerging technology that leverages the unique properties of biologically targeted superparamagnetic iron oxide nanoparticles to detect cancer. The use of ultra-sensitive sensors enables SPMR to detect tumors ten times smaller than current imaging methods. Reconstructing the distribution of cancer-bound nanoparticles from SPMR measurements is challenging because the inverse problem is ill posed. Current methods of source reconstruction rely on prior knowledge of the number of clusters of bound nanoparticles and their approximate locations, which is not known in clinical applications. In this work, we present a novel reconstruction algorithm based on compressed sensing methods that relies on only clinically feasible information. This approach is based on the hypothesis that the true distribution of cancer-bound nanoparticles consists of only a few highly-focal clusters around tumors and metastases, and is therefore the sparsest of all possible distributions with a similar SPMR signal. We tested this hypothesis through three specific aims. First, we calibrated the sensor locations used in the forward model to measured data, and found a 5% agreement between the forward model and the data. Next, we determined the optimal choice of the data fidelity parameter and investigated the effect of experimental factors on the reconstruction. Finally, we compared the compressed sensing-based algorithm with the current reconstruction method on SPMR measurements of phantoms. We found that when a multiple sources were reconstructed simultaneously, the compressed sensing approach was more frequently able to detect the second source. In a blinded user analysis, our compressed sensing-based reconstruction algorithm was able to correctly classify 80% of the test cases, whereas the current reconstruction method had an accuracy of 43%. Therefore, our algorithm has the potential to detect early stage tumors with higher accuracy, advancing the translation of SPMR as a clinical tool for early detection of cancer
Formation and Stability of Cellular Carbon Foam Structures:An {\em Ab Initio} Study
We use ab initio density functional calculations to study the formation and
structural as well as thermal stability of cellular foam-like carbon
nanostructures. These systems with a mixed bonding character may be
viewed as bundles of carbon nanotubes fused to a rigid contiguous 3D honeycomb
structure that can be compressed more easily by reducing the symmetry of the
honeycombs. The foam may accommodate the same type of defects as graphene, and
its surface may be be stabilized by terminating caps. We postulate that the
foam may form under non-equilibrium conditions near grain boundaries of a
carbon-saturated metal surface
Alice in the Land of Artificial Intelligence: Some Practical Ways to Help Survive “Abstract Idea” Challenges Under Section 101
- …