Immunotherapy in Advanced Lung Cancer Treatment

Despite the improvement in overall survival (OS) by platinum-based chemotherapy (NSCLC Meta-Analyses Collaborative Group, 2008), prognosis remains unsatisfactory for patients with advanced non-small cell lung cancer (NSCLC). We discuss in this chapter the new era of advanced lung cancer systemic therapy represented by immunotherapy. First of all I presented one of the modalities of immunological diagnostics based on new technology. The mechanism of action of the immunoagents is shortly described. In the in most part of the chapter, the main immunotherapeutic agents used in lung cancer immunotherapy are analyzed: vaccines, cytotoxic T lymphocyte-associated protein 4 (CTLA-4) inhibitors, and checkpoint inhibitors. In the end of the chapter, the combination between immunotherapeutic agents is discussed

Variational Principle for Mixed Classical-Quantum Systems

An extended variational principle providing the equations of motion for a system consisting of interacting classical, quasiclassical and quantum components is presented, and applied to the model of bilinear coupling. The relevant dynamical variables are expressed in the form of a quantum state vector which includes the action of the classical subsystem in its phase factor. It is shown that the statistical ensemble of Brownian state vectors for a quantum particle in a classical thermal environment can be described by a density matrix evolving according to a nonlinear quantum Fokker-Planck equation. Exact solutions of this equation are obtained for a two-level system in the limit of high temperatures, considering both stationary and nonstationary initial states. A treatment of the common time shared by the quantum system and its classical environment, as a collective variable rather than as a parameter, is presented in the Appendix.Comment: 16 pages, LaTex; added Figure 2 and Figure

Tirosyne Kinase Inhibithors (TKIs) in the Treatment of Non –Small Cell Lung Cancer (NSCLC), Practical Pharmacological Aspects

Tyrosine Kinase Inhibitors are new drugs developed in the last decade. For Non-Small Cell Lung Cancer this drug brought more hope for patients with this disease. Also TKIs are better tolerated then chemotherapy. The efficacy of TKIs is dependent of the presence of Epidermal Grows Factor Receptor gene mutation. This mutation account for about 9% of patients with lung cancer in Europe. This short review try to give the minimal knowledge to clinicians, especially medical oncologists, about mechanism of action, pharmacokinetics of TKIs used in the treatment NSCLC. Keywords: Tyrosine Kinase Inhibitors (TKI); Non -Small Cell Lung Cancer; Pharmacokinetics aspect

Quantum Coherence Oscillations in Antiferromagnetic Chains

Macroscopic quantum coherence oscillations in mesoscopic antiferromagnets may appear when the anisotropy potential creates a barrier between the antiferromagnetic states with opposite orientations of the Neel vector. This phenomenon is studied for the physical situation of the nuclear spin system of eight Xe atoms arranged on a magnetic surface along a chain. The oscillation period is calculated as a function of the chain constant. The environmental decoherence effects at finite temperature are accounted assuming a dipole coupling between the spin chain and the fluctuating magnetic field of the surface. The numerical calculations indicate that the oscillations are damped by a rate $\sim (N-1)/ \tau$, where $N$ is the number of spins and $\tau$ is the relaxation time of a single spin.Comment: 10 pages, Latex, two postscript figures; submitted to Phys. Rev.

Simulation of Deformation-induced Martensite Formation and its Influence on the Resonant Behavior in the Very High Cycle Fatigue (VHCF) Regime

AbstractThe exploration of fatigue mechanisms in the VHCF regime is gaining importance since many components have to withstand a very high number of loading cycles due to high frequency or long product life. In this regime, particular attention is paid to the period of fatigue crack initiation and thus the localization of plastic deformation. The resonant behavior of a metastable austenitic stainless steel (AISI304) is studied experimentally in the VHCF regime and shows a distinct transient characteristic. The major contribution of this work is to obtain a physically-based understanding of this characteristic by modeling the underlying microstructural mechanisms and their influence on the resonant behavior. Microscopic examinations indicate that AISI304 undergoes deformation-induced martensite formation starting mostly at intersecting shear bands during fatigue. Therefore, a microstructural shear band model [Hilgendorff et al. (2013)] is extended regarding the mechanism of deformation-induced martensite formation. The model accounts for the microstructural mechanisms occurring in shear bands as documented by experimental results, and nucleation of martensite is assumed to occur at intersecting shear bands following the Olsen-Cohen nucleation model (1972) in combination with the Bogers-Burgers mechanism (1964). The simulation model is numerically solved using the two-dimensional (2-D) boundary element method. By using this method, a 2-D microstructure can be modeled considering grain orientations as well as individual anisotropic elastic properties in each grain. The resonant behavior is characterized by evaluating the force-displacement hysteresis loop. Results show that plastic deformation in shear bands and deformation-induced martensite formation have a major impact on the resonant behavior in the very high cycle fatigue (VHCF) regime

Augmenting graphs to minimize the diameter

We study the problem of augmenting a weighted graph by inserting edges of bounded total cost while minimizing the diameter of the augmented graph. Our main result is an FPT 4-approximation algorithm for the problem.Comment: 15 pages, 3 figure

Detection of curved lines with B-COSFIRE filters: A case study on crack delineation

The detection of curvilinear structures is an important step for various computer vision applications, ranging from medical image analysis for segmentation of blood vessels, to remote sensing for the identification of roads and rivers, and to biometrics and robotics, among others. %The visual system of the brain has remarkable abilities to detect curvilinear structures in noisy images. This is a nontrivial task especially for the detection of thin or incomplete curvilinear structures surrounded with noise. We propose a general purpose curvilinear structure detector that uses the brain-inspired trainable B-COSFIRE filters. It consists of four main steps, namely nonlinear filtering with B-COSFIRE, thinning with non-maximum suppression, hysteresis thresholding and morphological closing. We demonstrate its effectiveness on a data set of noisy images with cracked pavements, where we achieve state-of-the-art results (F-measure=0.865). The proposed method can be employed in any computer vision methodology that requires the delineation of curvilinear and elongated structures.Comment: Accepted at Computer Analysis of Images and Patterns (CAIP) 201

Recognition of architectural and electrical symbols by COSFIRE filters with inhibition

The automatic recognition of symbols can be used to automatically convert scanned drawings into digital representations compatible with computer aided design software. We propose a novel approach to automatically recognize architectural and electrical symbols. The proposed method extends the existing trainable COSFIRE approach by adding an inhibition mechanism that is inspired by shape-selective TEO neurons in visual cortex. A COSFIRE filter with inhibition takes as input excitatory and inhibitory responses from line and edge detectors. The type (excitatory or inhibitory) and the spatial arrangement of low level features are determined in an automatic configuration step that analyzes two types of prototype pattern called positive and negative. Excitatory features are extracted from a positive pattern and inhibitory features are extracted from one or more negative patterns. In our experiments we use four subsets of images with different noise levels from the Graphics Recognition data set (GREC 2011) and demonstrate that the inhibition mechanism that we introduce improves the effectiveness of recognition substantially