Sensitization of MCF7 Cells with High Notch1 Activity by Cisplatin and Histone Deacetylase Inhibitors Applied Together

Histone deacetylase inhibitors (HDIs) are promising anti-cancer agents that inhibit proliferation of many types of cancer cells including breast carcinoma (BC) cells. In the present study, we investigated the influence of the Notch1 activity level on the pharmacological interaction between cisplatin (CDDP) and two HDIs, valproic acid (VPA) and suberoylanilide hydroxamic acid (SAHA, vorinostat), in luminal-like BC cells. The type of drug–drug interaction between CDDP and HDIs was determined by isobolographic analysis. MCF7 cells were genetically modified to express differential levels of Notch1 activity. The cytotoxic effect of SAHA or VPA was higher on cells with decreased Notch1 activity and lower for cells with increased Notch1 activity than native BC cells. The isobolographic analysis demonstrated that combinations of CDDP with SAHA or VPA at a fixed ratio of 1:1 exerted additive or additive with tendency toward synergism interactions. Therefore, treatment of CDDP with HDIs could be used to optimize a combined therapy based on CDDP against Notch1-altered luminal BC. In conclusion, the combined therapy of HDIs and CDDP may be a promising therapeutic tool in the treatment of luminal-type BC with altered Notch1 activity.     

Selective partial oxidation of light paraffins with hydrogen peroxide on thin-layer supported Nafion-H catalysts

Thin-layer carbon supported Nafion-H catalysts were found to be active and highly selective (S>98%) for the partial oxidation of C₁-C₃ alkanes, in a three phase catalytic membrane reactor (3PCMR), under mild conditions and in the presence of H₂O₂. The influences of the catalyst teflon loading and H₂O₂ concentration on the reaction rate have been evaluated. A reaction pathway, based on the electrophilic hydroxylation of the C-H bond of alkanes with protonated hydrogen peroxide (H₃O ₂ ⁺ ), is discussed.     

Optimization techniques for curved path computing

Participating media with an inhomogeneous index of refraction make light follow curved paths. Simulating this in a global illumination environment has usually been neglected due to the complexity of the calculations involved, sacrificing accurate physical simulations for efficient visual results. This paper aims to simulate non-linear media in a more reasonable time than previous works without losing physical correctness. Accuracy is achieved by solving the Eikonal equation of geometrical optics, which describes the path followed by a light beam that traverses a non-linear medium. This equation is used in the context of a photon mapping extension.     

Innovative Membrane-Based Catalytic Process for Environmentally Friendly Synthesis of Oxygenates

Synthesis of liquid oxygenates from light alkanes (C₁--C₃) is achieved in a multifunctional three-phase catalytic membrane reactor (3PCMR) operating under mild conditions (T_R, 80-120 °C; P_R, 140 kPa). The features of superacid catalytic membranes mediated by the Meⁿ⁺/H₂O₂ Fenton system in activating C₁-C₃ alkanes are presented. The effect of operating conditions ([H₂O₂], [Meⁿ⁺]) on the catalyst activity is outlined. A general reaction pathway accounting for the activation of the CH bond of the alkane molecule on the superacid sites and the subsequent reaction of the activated alkane with primary reactive intermediates, generated from the Meⁿ⁺/H₂O₂ system, is proposed. The suitability of the 3PCMR in enabling simultaneous reaction and product separation is discussed.     

Partial oxidation of ethane by in situ generated H2O2

Selective partial oxidation of ethane to ethanol and acetaldehyde by in situ generated H₂O₂ has been achieved under cathodic current passing through a carbon supported Nafion-H catalytic membrane. A correlation between H₂O₂ generation rate and reaction rate has been found.     

Effect of the metal oxide loading on the activity of silica supported MoO3 and V2O5 catalysts in the selective partial oxidation of methane

Precipitated silica catalysts loaded with either MoO₃ (0.2–4.0 wt%) or V₂O₅ (0.2–5.3 wt%) have been studied in the selective partial oxidation of methane to formaldehyde with molecular oxygen at 520 °C. The functionality of the SiO₂ surface towards the formation of HCHO is significantly promoted by V₂O₅, while it is depressed by the MoO₃.     

Binarised regression tasks: methods and evaluation metrics

Some supervised tasks are presented with a numerical output but decisions have to be made in a discrete, binarised, way, according to a particular cutoff. This binarised regression task is a very common situation that requires its own analysis, different from regression and classification—and ordinal regression. We first investigate the application cases in terms of the information about the distribution and range of the cutoffs and distinguish six possible scenarios, some of which are more common than others. Next, we study two basic approaches: the retraining approach, which discretises the training set whenever the cutoff is available and learns a new classifier from it, and the reframing approach, which learns a regression model and sets the cutoff when this is available during deployment. In order to assess the binarised regression task, we introduce context plots featuring error against cutoff. Two special cases are of interest, the \( UCE \) and \( OCE \) curves, showing that the area under the former is the mean absolute error and the latter is a new metric that is in between a ranking measure and a residual-based measure. A comprehensive evaluation of the retraining and reframing approaches is performed using a repository of binarised regression problems created on purpose, concluding that no method is clearly better than the other, except when the size of the training data is small.     

Use of Ontologies as Representation Support of Workflows Oriented to Administrative Management

One of the applications of workflow systems is the management of administrative processes characterized by the transmission of information elements among users of an organization. Tasks contained in these processes are carried out by users responsible for confirming, modifying or adding information throughout. These processes need to be defined in workflow management systems in which all the elements are perfectly identified and are easily adaptable to changes that may arise in the sequences of tasks, in the users involved or in the data transmitted from one task to another. For this kind of processes is easier to reuse those represented in ontologies. On one hand, existing ontologies for representing some domain elements can be reused. At the same time, ontologies have an excellent expressive capacity to define tasks, their relationships and the flow control among them with precision. This paper proposes a complete model, together with the necessary software tools, for tackling this issue.

Optimal Control of Nonlinear Systems Using Experience Inference Human-Behavior Learning

Safety critical control is often trained in a simulated environment to mitigate risk. Subsequent migration of the biased controller requires further adjustments. In this paper, an experience inference human-behavior learning is proposed to solve the migration problem of optimal controllers applied to real-world nonlinear systems. The approach is inspired in the complementary properties that exhibits the hippocampus, the neocortex, and the striatum learning systems located in the brain. The hippocampus defines a physics informed reference model of the real-world nonlinear system for experience inference and the neocortex is the adaptive dynamic programming (ADP) or reinforcement learning (RL) algorithm that ensures optimal performance of the reference model. This optimal performance is inferred to the real-world nonlinear system by means of an adaptive neocortex/striatum control policy that forces the nonlinear system to behave as the reference model. Stability and convergence of the proposed approach is analyzed using Lyapunov stability theory. Simulation studies are carried out to verify the approach.      

Criticality Analysis for Maintenance Purposes: A Study for Complex In‐service Engineering Assets

The purpose of this paper is to establish a basis for a criticality analysis, considered here as a prerequisite, a first required step to review the current maintenance programs, of complex in‐service engineering assets. Review is understood as a reality check, a testing of whether the current maintenance activities are well aligned to actual business objectives and needs. This paper describes an efficient and rational working process and a model resulting in a hierarchy of assets, based on risk analysis and cost–benefit principles, which will be ranked according to their importance for the business to meet specific goals. Starting from a multicriteria analysis, the proposed model converts relevant criteria impacting equipment criticality into a single score presenting the criticality level. Although detailed implementation of techniques like Root Cause Failure Analysis and Reliability Centered Maintenance will be recommended for further optimization of the maintenance activities, the reasons why criticality analysis deserves the attention of engineers and maintenance and reliability managers are precisely explained here. A case study is presented to help the reader understand the process and to operationalize the model. Copyright © 2015 John Wiley & Sons, Ltd.