Multi-Lattice Kinetic Monte Carlo Simulations from First-Principles: Reduction of the Pd(100) Surface Oxide by CO

We present a multi-lattice kinetic Monte Carlo (kMC) approach that efficiently describes the atomistic dynamics of morphological transitions between commensurate structures at crystal surfaces. As an example we study the reduction of a $(\sqrt{5}\times \sqrt{5})R27^{\circ}$ PdO(101) overlayer on Pd(100) in a CO atmosphere. Extensive density-functional theory calculations are used to establish an atomistic pathway for the oxide reduction process. First-principles multi-lattice kMC simulations on the basis of this pathway fully reproduce the experimental temperature dependence of the reduction rate [Fernandes et al., Surf. Sci. 2014, 621, 31-39] and highlight the crucial role of elementary processes special to the boundary between oxide and metal domains.Comment: 19 pages, 10 figure

Employing Environmental Data and Machine Learning to Improve Mobile Health Receptivity

Behavioral intervention strategies can be enhanced by recognizing human activities using eHealth technologies. As we find after a thorough literature review, activity spotting and added insights may be used to detect daily routines inferring receptivity for mobile notifications similar to just-in-time support. Towards this end, this work develops a model, using machine learning, to analyze the motivation of digital mental health users that answer self-assessment questions in their everyday lives through an intelligent mobile application. A uniform and extensible sequence prediction model combining environmental data with everyday activities has been created and validated for proof of concept through an experiment. We find that the reported receptivity is not sequentially predictable on its own, the mean error and standard deviation are only slightly below by-chance comparison. Nevertheless, predicting the upcoming activity shows to cover about 39% of the day (up to 58% in the best case) and can be linked to user individual intervention preferences to indirectly find an opportune moment of receptivity. Therefore, we introduce an application comprising the influences of sensor data on activities and intervention thresholds, as well as allowing for preferred events on a weekly basis. As a result of combining those multiple approaches, promising avenues for innovative behavioral assessments are possible. Identifying and segmenting the appropriate set of activities is key. Consequently, deliberate and thoughtful design lays the foundation for further development within research projects by extending the activity weighting process or introducing a model reinforcement.BMBF, 13GW0157A, Verbundprojekt: Self-administered Psycho-TherApy-SystemS (SELFPASS) - Teilvorhaben: Data Analytics and Prescription for SELFPASSTU Berlin, Open-Access-Mittel - 201

A practical approach to the sensitivity analysis for kinetic Monte Carlo simulation of heterogeneous catalysis

Lattice kinetic Monte Carlo simulations have become a vital tool for predictive quality atomistic understanding of complex surface chemical reaction kinetics over a wide range of reaction conditions. In order to expand their practical value in terms of giving guidelines for the atomic level design of catalytic systems, it is very desirable to readily evaluate a sensitivity analysis for a given model. The result of such a sensitivity analysis quantitatively expresses the dependency of the turnover frequency, being the main output variable, on the rate constants entering the model. In the past, the application of sensitivity analysis, such as degree of rate control, has been hampered by its exuberant computational effort required to accurately sample numerical derivatives of a property that is obtained from a stochastic simulation method. In this study, we present an efficient and robust three-stage approach that is capable of reliably evaluating the sensitivity measures for stiff microkinetic models as we demonstrate using the CO oxidation on RuO2(110) as a prototypical reaction. In the first step, we utilize the Fisher information matrix for filtering out elementary processes which only yield negligible sensitivity. Then we employ an estimator based on the linear response theory for calculating the sensitivity measure for non- critical conditions which covers the majority of cases. Finally, we adapt a method for sampling coupled finite differences for evaluating the sensitivity measure for lattice based models. This allows for an efficient evaluation even in critical regions near a second order phase transition that are hitherto difficult to control. The combined approach leads to significant computational savings over straightforward numerical derivatives and should aid in accelerating the nano-scale design of heterogeneous catalysts

Adenosine receptor 2B activity promotes autonomous growth, migration as well as vascularization of head and neck squamous cell carcinoma cells

Adenosine is a signaling molecule that exerts dual effects on tumor growth: while it inhibits immune cell function and thereby prevents surveillance by the immune system, it influences tumorigenesis directly via activation of adenosine receptors on tumor cells at the same time. However, the adenosine-mediated mechanisms affecting oncogenic processes particularly in head and neck squamous cell carcinomas (HNSCC) are not fully understood. Here, we investigated the role of adenosine receptor activity on HNSCC-derived cell lines. Targeting the adenosine receptor A2B (ADORA2B) on these cells with the inverse agonist/antagonist PSB-603 leads to inhibition of cell proliferation, transmigration as well as VEGFA secretion in vitro. At the molecular level, these effects were associated with cell cycle arrest as well as the induction of the apoptotic pathway. In addition, shRNA-mediated downmodulation of ADORA2B expression caused decreased proliferation. Moreover, in in vivo xenograft experiments, chemical and genetic abrogation of ADORA2B activity impaired tumor growth associated with decreased tumor vascularization. Together, our findings characterize ADORA2B as a crucial player in the maintenance of HNSCC and, therefore, as a potential therapeutic target for HNSCC treatment

Cytotoxicity of ZnO Nanoparticles Can Be Tailored by Modifying Their Surface Structure: A Green Chemistry Approach for Safer Nanomaterials

ZnO nanoparticles (NP) are extensively used in numerous nanotechnology applications; however, they also happen to be one of the most toxic nanomaterials. This raises significant environmental and health concerns and calls for the need to develop new synthetic approaches to produce safer ZnO NP, while preserving their attractive optical, electronic, and structural properties. In this work, we demonstrate that the cytotoxicity of ZnO NP can be tailored by modifying their surface-bound chemical groups, while maintaining the core ZnO structure and related properties. Two equally sized (9.26 ± 0.11 nm) ZnO NP samples were synthesized from the same zinc acetate precursor using a forced hydrolysis process, and their surface chemical structures were modified by using different reaction solvents. X-ray diffraction and optical studies showed that the lattice parameters, optical properties, and band gap (3.44 eV) of the two ZnO NP samples were similar. However, FTIR spectroscopy showed significant differences in the surface structures and surface-bound chemical groups. This led to major differences in the zeta potential, hydrodynamic size, photocatalytic rate constant, and more importantly, their cytotoxic effects on Hut-78 cancer cells. The ZnO NP sample with the higher zeta potential and catalytic activity displayed a 1.5-fold stronger cytotoxic effect on cancer cells. These results suggest that by modifying the synthesis parameters/conditions and the surface chemical structures of the nanocrystals, their surface charge density, catalytic activity, and cytotoxicity can be tailored. This provides a green chemistry approach to produce safer ZnO NP

Uniform convergence of discrete curvatures from nets of curvature lines

We study discrete curvatures computed from nets of curvature lines on a given smooth surface, and prove their uniform convergence to smooth principal curvatures. We provide explicit error bounds, with constants depending only on properties of the smooth limit surface and the shape regularity of the discrete net.Comment: 21 pages, 8 figure

Comparative Genomics of Helicobacter pylori Strains of China Associated with Different Clinical Outcome

In this study, a whole-genome CombiMatrix Custom oligonucleotide tiling microarray with 90000 probes covering six sequenced Helicobacter pylori (H. pylori) genomes was designed. This microarray was used to compare the genomic profiles of eight unsequenced strains isolated from patients with different gastroduodenal diseases in Heilongjiang province of China. Since significant genomic variation was found among these strains, an additional 76 H. pylori strains associated with different clinical outcomes were isolated from various provinces of China. These strains were tested by polymerase chain reaction to demonstrate this distinction. We identified several highly variable regions in strains associated with gastritis, gastric ulceration, and gastric cancer. These regions are associated with genes involved in the bacterial type I, type II, and type III R-M systems. They were also associated with the virB gene, which lies on the well-studied cag pathogenic island. While previous studies have reported on the diverse genetic characterization of this pathogenic island, in this study, we find that it is conserved in all strains tested by microarray. Moreover, a number of genes involved in the type IV secretion system, which is related to horizontal DNA transfer between H. pylori strains, were identified in the comparative analysis of the strain-specific genes. These findings may provide insight into new biomarkers for the prediction of gastric diseases

Diagnostic value of Pentraxin-3 in patients with sepsis and septic shock in accordance with latest sepsis-3 definitions

Background: Pentraxin-3 (PTX-3) is an acute-phase protein involved in inflammatory and infectious processes. This study assesses its diagnostic and prognostic value in patients with sepsis or septic shock in a medical intensive care unit (ICU). Methods: The study includes 213 ICU patients with clinical criteria of sepsis and septic shock. 77 donors served as controls. Plasma levels of PTX-3, procalcitonin (PCT) and interleukin-6 were measured on day 1, 3 and 8. Results: PTX-3 correlated with higher lactate levels as well as with APACHE II and SOFA scores (p = 0.0001). PTX-3 levels of patients with sepsis or septic shock were consistently significantly higher than in the control group (p ≤ 0.001). Plasma levels were able to discriminate sepsis and septic shock significantly on day 1, 3 and 8 (range of AUC 0.73–0.92, p = 0.0001). Uniform cut-off levels were defined at ≥5 ng/ml for at least sepsis, ≥9 ng/ml for septic shock (p = 0.0001). Conclusion: PTX-3 reveals diagnostic value for sepsis and septic shock during the first week of intensive care treatment, comparable to interleukin-6 according to latest Sepsis-3 definitions. Trial registration: NCT01535534. Registered 14.02.201