Patterned anvils for high pressure measurements at low temperature

Multiprobe high pressure measurements require electrical leads in the sample chamber. Compared to conventional wire-based techniques, metallic tracks patterned onto the anvil surface improve reliability and ease of use, and enable novel and more demanding measurements under high pressure. We have developed new anvil designs based on sputter-deposited tracks on alumina and moissanite anvils. These anvils allow convenient and reliable measurements of electrical transport properties or of the magnetic susceptibility under hydrostatic conditions, as demonstrated by test measurements on Pb and Ca(3)Ru(2)O(7).     

Mechanical robustness of Pseudomonas aeruginosa biofilms

Biofilms grow on various surfaces and in many different environments, a phenomenon that constitutes major problems in industry and medicine. Despite their importance little is known about the viscoelastic properties of biofilms and how these depend on the chemical microenvironment. Here, we find that the mechanical properties of Pseudomonas aeruginosa (P.a.) biofilms are highly robust towards chemical perturbations. Specifically, we observe that P.a. biofilms are able to fully regain their initial stiffness after yielding is enforced, even in the presence of chemicals. Moreover, only trivalent ions and citric acid significantly affect the biofilm elasticity, the first of which also alter the texture of the material. Finally, our results indicate that biofilm mechanics and bacteria viability inside the biofilm are not necessarily linked which suggests that targeting bacteria alone might not be sufficient for biofilm removal strategies.     

CtpB Facilitates Mycobacterium tuberculosis Growth in Copper-Limited Niches

Copper is required for aerobic respiration by Mycobacterium tuberculosis and its human host, but this essential element is toxic in abundance. Copper nutritional immunity refers to host processes that modulate levels of free copper to alternately starve and intoxicate invading microbes. Bacteria engulfed by macrophages are initially contained within copper-limited phagosomes, which fuse with ATP7A vesicles that pump in toxic levels of copper. In this report, we examine how CtpB, a P-type ATPase in M. tuberculosis, aids in response to nutritional immunity. In vitro, the induced expression of ctpB in copper-replete medium inhibited mycobacterial growth, while deletion of the gene impaired growth only in copper-starved medium and within copper-limited host cells, suggesting a role for CtpB in copper acquisition or export to the copper-dependent respiration supercomplex. Unexpectedly, the absence of ctpB resulted in hypervirulence in the DBA/2 mouse infection model. As ctpB null strains exhibit diminished growth only in copper-starved conditions, reduced copper transport may have enabled the mutant to acquire a “Goldilocks” amount of the metal during transit through copper-intoxicating environments within this model system. This work reveals CtpB as a component of the M. tuberculosis toolkit to counter host nutritional immunity and underscores the importance of elucidating copper-uptake mechanisms in pathogenic mycobacteria.     

Transparent conducting indium oxide thin films grown by low-temperature metal organic chemical vapor deposition

We have grown indium oxide thin films on silicon substrates at low temperature by metal organic chemical vapor deposition. Polycrystalline film growth could only be obtained at temperatures below 400 °C. Above 400 °C, metallic indium deposition dominated. We have investigated the effect of substrate temperature and reactor pressure on the film growth and structural properties in the range of 250-350 °C and 5 ^? 10³-4 ^? 10⁴ Pa. The film grown at 300 °C exhibited a resistivity of about 3.6 × 10^− 3 Ω cm and a maximal optical transmittance of more than 95% in the visible range. The film showed an optical band gap of about 3.6 eV.     

Molecular Subtyping of Invasive Breast Cancer Using a PAM50-Based Multigene Expression Test-Comparison with Molecular-Like Subtyping by Tumor Grade/Immunohistochemistry and Influence on Oncologist’s Decision on Systemic Therapy in a Real-World Setting

In intermediate risk hormone receptor (HR) positive, HER2 negative breast cancer (BC), the decision regarding adjuvant chemotherapy might be facilitated by multigene expression tests. In all, 142 intermediate risk BCs were investigated using the PAM50-based multigene expression test Prosigna® in a prospective multicentric study. In 119/142 cases, Prosigna® molecular subtyping was compared with local and two central (C1 and C6) molecular-like subtypes relying on both immunohistochemistry (IHC; HRs, HER2, Ki-67) and IHC + tumor grade (IHC+G) subtyping. According to local IHC, 35.4% were Luminal A-like and 64.6% Luminal B-like subtypes (local IHC+G subtype: 31.9% Luminal A-like; 68.1% Luminal B-like). In contrast to local and C1 subtyping, C6 classified >2/3 of cases as Luminal A-like. Pairwise agreement between Prosigna® subtyping and molecular-like subtypes was fair to moderate depending on molecular-like subtyping method and center. The best agreement was observed between Prosigna® (53.8% Luminal A; 44.5% Luminal B) and C1 surrogate subtyping (Cohen’s kappa = 0.455). Adjuvant chemotherapy was suggested to 44.2% and 88.6% of Prosigna® Luminal A and Luminal B cases, respectively. Out of all Luminal A-like cases (locally IHC/IHC+G subtyping), adjuvant chemotherapy was recommended if Prosigna® testing classified as Prosigna® Luminal A at high / intermediate risk or upgraded to Prosigna® Luminal B.     

Protein–Protein Interaction Prediction for Targeted Protein Degradation

Protein–protein interactions (PPIs) play a fundamental role in various biological functions; thus, detecting PPI sites is essential for understanding diseases and developing new drugs. PPI prediction is of particular relevance for the development of drugs employing targeted protein degradation, as their efficacy relies on the formation of a stable ternary complex involving two proteins. However, experimental methods to detect PPI sites are both costly and time-intensive. In recent years, machine learning-based methods have been developed as screening tools. While they are computationally more efficient than traditional docking methods and thus allow rapid execution, these tools have so far primarily been based on sequence information, and they are therefore limited in their ability to address spatial requirements. In addition, they have to date not been applied to targeted protein degradation. Here, we present a new deep learning architecture based on the concept of graph representation learning that can predict interaction sites and interactions of proteins based on their surface representations. We demonstrate that our model reaches state-of-the-art performance using AUROC scores on the established MaSIF dataset. We furthermore introduce a new dataset with more diverse protein interactions and show that our model generalizes well to this new data. These generalization capabilities allow our model to predict the PPIs relevant for targeted protein degradation, which we show by demonstrating the high accuracy of our model for PPI prediction on the available ternary complex data. Our results suggest that PPI prediction models can be a valuable tool for screening protein pairs while developing new drugs for targeted protein degradation.     

New wireless connection between user and VE using speech processing

This paper presents a novel speak-to-VR virtual-reality peripheral network (VRPN) server based on speech processing. The server uses a microphone array as a speech source and streams the results of the process through a Wi-Fi network. The proposed VRPN server provides a handy, portable and wireless human machine interface that can facilitate interaction in a variety interfaces and application domains including HMD- and CAVE-based virtual reality systems, flight and driving simulators and many others. The VRPN server is based on a speech processing software development kits and VRPN library in C++. Speak-to-VR VRPN works well even in the presence of background noise or the voices of other users in the vicinity. The speech processing algorithm is not sensitive to the user’s accent because it is trained while it is operating. Speech recognition parameters are trained by hidden Markov model in real time. The advantages and disadvantages of the speak-to-VR server are studied under different configurations. Then, the efficiency and the precision of the speak-to-VR server for a real application are validated via a formal user study with ten participants. Two experimental test setups are implemented on a CAVE system by using either Kinect Xbox or array microphone as input device. Each participant is asked to navigate in a virtual environment and manipulate an object. The experimental data analysis shows promising results and motivates additional research opportunities.     

Tailoring Electron‐Transfer Barriers for Zinc Oxide/C60 Fullerene Interfaces

The interfacial electronic structure between oxide thin films and organic semiconductors remains a key parameter for optimum functionality and performance of next‐generation organic/hybrid electronics. By tailoring defect concentrations in transparent conductive ZnO films, we demonstrate the importance of controlling the electron transfer barrier at the interface with organic acceptor molecules such as C₆₀. A combination of electron spectroscopy, density functional theory computations, and device characterization is used to determine band alignment and electron injection barriers. Extensive experimental and first principles calculations reveal the controllable formation of hybridized interface states and charge transfer between shallow donor defects in the oxide layer and the molecular adsorbate. Importantly, it is shown that removal of shallow donor intragap states causes a larger barrier for electron injection. Thus, hybrid interface states constitute an important gateway for nearly barrier‐free charge carrier injection. These findings open new avenues to understand and tailor interfaces between organic semiconductors and transparent oxides, of critical importance for novel optoelectronic devices and applications in energy‐conversion and sensor technologies.     

BETaaS: A Platform for Development and Execution of Machine-to-Machine Applications in the Internet of Things

Wireless Personal Communications - The integration of everyday objects into the Internet represents the foundation of the forthcoming Internet of Things (IoT). Smart objects will be the building...     

Metabolomic Evidence for Peroxisomal Dysfunction in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic and debilitating disease characterized by unexplained physical fatigue, cognitive and sensory dysfunction, sleeping disturbances, orthostatic intolerance, and gastrointestinal problems. People with ME/CFS often report a prodrome consistent with infections. Using regression, Bayesian and enrichment analyses, we conducted targeted and untargeted metabolomic analysis of plasma from 106 ME/CFS cases and 91 frequency-matched healthy controls. Subjects in the ME/CFS group had significantly decreased levels of plasmalogens and phospholipid ethers (p < 0.001), phosphatidylcholines (p < 0.001) and sphingomyelins (p < 0.001), and elevated levels of dicarboxylic acids (p = 0.013). Using machine learning algorithms, we were able to differentiate ME/CFS or subgroups of ME/CFS from controls with area under the receiver operating characteristic curve (AUC) values up to 0.873. Our findings provide the first metabolomic evidence of peroxisomal dysfunction, and are consistent with dysregulation of lipid remodeling and the tricarboxylic acid cycle. These findings, if validated in other cohorts, could provide new insights into the pathogenesis of ME/CFS and highlight the potential use of the plasma metabolome as a source of biomarkers for the disease.