Precision Oncology via NMR-Based Metabolomics: A Review on Breast Cancer

Precision oncology is an emerging approach in cancer care. It aims at selecting the optimal therapy for the right patient by considering each patient’s unique disease and individual health status. In the last years, it has become evident that breast cancer is an extremely heterogeneous disease, and therefore, patients need to be appropriately stratified to maximize survival and quality of life. Gene-expression tools have already positively assisted clinical decision making by estimating the risk of recurrence and the potential benefit from adjuvant chemotherapy. However, these approaches need refinement to further reduce the proportion of patients potentially exposed to unnecessary chemotherapy. Nuclear magnetic resonance (NMR) metabolomics has demonstrated to be an optimal approach for cancer research and has provided significant results in BC, in particular for prognostic and stratification purposes. In this review, we give an update on the status of NMR-based metabolomic studies for the biochemical characterization and stratification of breast cancer patients using different biospecimens (breast tissue, blood serum/plasma, and urine).     

Effect of deposition conditions on the properties and annealing behavior of cold-sprayed copper

The deposition of copper by cold gas dynamic spraying has attracted much interest in recent years due to the capability to deposit low-porosity oxide-free coatings. However, it is generally found that as-deposited copper has a signicantly greater hardness, and potentially lower ductility, than bulk material. In this article, copper was deposited by cold spraying using helium as the driving gas at both 298 and 523 K. Evidence is presented indicating that the material sprayed at the lower temperature exhibits a lower dislocation density throughout the grain structure than the material sprayed at the higher temperature. The low stacking fault energy of copper restricts recovery during annealing, and thus microstructural changes during annealing only proceed once recrystallization begins. The material sprayed at low temperature (with the low dislocation density) exhibited recrystallization at annealing temperatures as low as 373 K with a corresponding reduction in hardness. However, the copper sprayed with helium at 523 K was resistant to annealing at temperatures up to 473 K where the dislocations in the structure prevented recrystallization. However, at higher temperatures, recrystallization did proceed (with corresponding reductions in hardness). The fracture behavior of the copper that was cold sprayed with helium at 523 K, both in the as-sprayed condition and following annealing, was measured and explained in terms of the annealing mechanisms proposed. The original version of this paper was published in the CD ROM Thermal Spray Connects: Explore Its Surfacing Potential, International Thermal Spray Conference, sponsored by DVS, ASM International, and HW International Institute of Welding, Basel, Switzerland, May 2–4, 2005, DVS-Verlag GmbH, Düsseldorf, Germany.     

A model to predict the evolution of pitting corrosion and the pit-to-crack transition incorporating statistically distributed input parameters

A model based on deterministic equations with statistically distributed input parameters has been developed for simulating the evolution of the pit depth distribution at different exposure times and the percentage of pits that transform to stress corrosion cracks. The model has been applied to the specific case of steam turbine disc steel exposed to a range of environments under applied stress. With preliminary fitting at one exposure time, the simulation not only reflects the trends in the experimental measurement but also the model, uniquely, reproduces the statistical variability or “noise” associated with the measurements.     

Effect of cold spray deposition of a titanium coating on fatigue behavior of a titanium alloy

The deposition of titanium on a titanium alloy substrate is being examined for potential use as a surface treatment for medical prostheses. A Ti6Al4V alloy was coated with pure titanium by cold gas dynamic spraying. Coatings were deposited onto samples with two different surface preparation methods (as-received and grit-blasted). The fatigue life of the as-received and grit-blasted materials, both before and after coating, was measured with a rotating-bend fatigue rig. A 15% reduction in fatigue endurance limit was observed after application of the coating to the as-received substrate, but no significant reduction was observed on its application to the grit-blasted substrate. The reduction in fatigue endurance limit has been related to the substrate-coating interface properties, the elastic modulus, and the residual stress states. This article was originally published inBuilding on 100 Years of Success, Proceedings of the 2006 International Thermal Spray Conference, (Seattle, WA), May 15–18, 2006, B.R. Marple, M.M. Hyland, Y.-Ch. Lau, R.S. Lima, and J. Voyer, Ed., ASM International, Materials Park, 2006.     

An SDP Primal-Dual Algorithm for Approximating the Lovász-Theta Function

The Lovász ?-function (Lovász in IEEE Trans. Inf. Theory, 25:1–7, 1979) of a graph G=(V,E) can be defined as the maximum of the sum of the entries of a positive semidefinite matrix X, whose trace Tr(X) equals 1, and X _ij =0 whenever {i,j}∈E. This function appears as a subroutine for many algorithms for graph problems such as maximum independent set and maximum clique. We apply Arora and Kale’s primal-dual method for SDP to design an algorithm to approximate the ?-function within an additive error of δ>0, which runs in time $O(\frac{\vartheta ^{2} n^{2}}{\delta^{2}} \log n \cdot M_{e})$ , where ?=?(G) and M _e =O(n ³) is the time for a matrix exponentiation operation. It follows that for perfect graphs G, our primal-dual method computes ?(G) exactly in time O(? ² n ⁵logn). Moreover, our techniques generalize to the weighted Lovász ?-function, and both the maximum independent set weight and the maximum clique weight for vertex weighted perfect graphs can be approximated within a factor of (1+?) in time O(? ^?2 n ⁵logn).     

A Comparison of the Levels of Lutein and Zeaxanthin in Corn Germ Oil,Corn Fiber Oil and Corn Kernel Oil

All commercial corn oil is obtained by pressing corn germ and/or extracting the germ with hexane. In the current study, six types of corn oil were prepared by extracting corn germ, corn fiber and ground corn, each with hexane or with ethanol. The levels of lutein, zeaxanthin and other carotenoids were quantitatively analyzed in the six corn oils. The levels of lutein + zeaxanthin in the oil ranged from 2.3 μg/g for hexane-extracted corn germ oil to 220.9 μg/g for ethanol-extracted ground corn oil. These results indicate that a diet that includes 30 g (~2 tbsp) per day of the unrefined corn oil obtained by extracting ground corn with ethanol would provide ~6 mg of lutein + zeaxanthin, the daily dosage that is currently considered to be necessary to slow the progression of age-related macular degeneration. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.     

Toward seed-insensitive solutions to local community detection

Local community detection aims at finding a community structure starting from a seed which is a given vertex in a network without global information, such as online social networks that are too large and dynamic to ever be known fully. Nonetheless, the existing approaches to local community detection are usually sensitive to seeds, i.e., some seeds may lead to missing of some true communities. In this paper, we present a seed-insensitive method called GMAC and its variation iGMAC for local community detection. They estimate the similarity among vertices by investigating vertices’ neighborhoods, and reveal a local community by maximizing its internal similarity and minimizing its external similarity simultaneously. Extensive experimental results on both synthetic and real-world data sets verify the effectiveness of our algorithms.     

Summarizing high-level scene behavior

We present several novel techniques to summarize the high-level behavior in surveillance video. Our proposed methods can employ either optical flow or trajectories as input, and incorporate spatial and temporal information together, which improve upon existing approaches for summarization. To begin, we extract common pathway regions by performing graph-based clustering on similarity matrices describing the relationships between location/orientation states. We then employ the activities along the pathway regions to extract the aggregate behavioral patterns throughout scenes. We show how our summarization methods can be applied to detect anomalies, retrieve video clips of interest, and generate adaptive-speed summary videos. We examine our approaches on multiple complex urban scenes and present experimental results.     

Dynamic distributed lanes: motion planning for multiple autonomous vehicles

Unorganized traffic is a generalized form of travel wherein vehicles do not adhere to any predefined lanes and can travel in-between lanes. Such travel is visible in a number of countries e.g. India, wherein it enables a higher traffic bandwidth, more overtaking and more efficient travel. These advantages are visible when the vehicles vary considerably in size and speed, in the absence of which the predefined lanes are near-optimal. Motion planning for multiple autonomous vehicles in unorganized traffic deals with deciding on the manner in which every vehicle travels, ensuring no collision either with each other or with static obstacles. In this paper the notion of predefined lanes is generalized to model unorganized travel for the purpose of planning vehicles travel. A uniform cost search is used for finding the optimal motion strategy of a vehicle, amidst the known travel plans of the other vehicles. The aim is to maximize the separation between the vehicles and static obstacles. The search is responsible for defining an optimal lane distribution among vehicles in the planning scenario. Clothoid curves are used for maintaining a lane or changing lanes. Experiments are performed by simulation over a set of challenging scenarios with a complex grid of obstacles. Additionally behaviours of overtaking, waiting for a vehicle to cross and following another vehicle are exhibited.     

Generating hydrogen-rich fuel-cell feeds from dimethyl ether (DME) using physical mixtures of a commercial Cu/Zn/Al2O3 catalyst and several solid–acid catalysts

Homogeneous physical mixtures containing a commercial Cu/ZnO/Al₂O₃ catalyst and a solid–acid catalyst were used to examine the acidity effects on dimethyl ether hydrolysis and their subsequent effects on dimethyl ether steam reforming (DME-SR). The acid catalysts used were zeolites Y [Si/Al = 2.5 and 15: denoted Y(Si/Al)], ZSM-5 [Si/Al = 15, 25, 40, and 140: denoted Z(Si/Al)] and other conventional catalyst supports (ZrO₂, and γ-Al₂O₃). The homogeneous physical mixtures contained equal amounts, by volume, of the solid–acid catalyst and the commercial Cu/ZnO/Al₂O₃ catalyst (BASF K3-110, denoted as K3). The steam reforming of dimethyl ether was carried out in an isothermal packed-bed reactor at ambient pressure.

The most promising physical mixtures for the low-temperature production of hydrogen from DME contained ZSM-5 as the solid–acid catalyst, with hydrogen yields exceeding 90% (T = 275 °C, S/C = 1.5, τ = 1.0 s and P = 0.78 atm) and hydrogen selectivities exceeding 94%, comparable to those observed for methanol steam reforming (MeOH-SR) over BASF K3-110, with values equaling 95% and 99%, respectively (T = 225 °C, S/C = 1.0, τ = 1.0 s and P = 0.78 atm). Large production rates of hydrogen were directly related to the type of acid catalyst used. The hydrogen production activity trend as a function of physical mixture was