Spheroidal nanoparticles as thermal near-field sensors

We suggest to exploit the shape-dependence of the near-field heat transfer for nanoscale thermal imaging. By utilizing strongly prolate or oblate nanoparticles as sensors one can assess individual components of the correlation tensors characterizing the thermal near field close to a nanostructured surface, and thus obtain directional information beyond the local density of states. Our theoretical considerations are backed by idealized numerical model calculations

Near-field thermal imaging of nanostructured surfaces

We show that a near-field scanning thermal microscope, which essentially detects the local density of states of the thermally excited electromagnetic modes at nanometer distances from some material, can be employed for nanoscale imaging of structures on that material's surface. This finding is explained theoretically by an approach which treats the surface structure perturbatively

Second-order calculation of the local density of states above a nanostructured surface

We have numerically implemented a perturbation series for the scattered electromagnetic fields above rough surfaces, due to Greffet, allowing us to evaluate the local density of states to second order in the surface profile function. We present typical results for thermal near fields of surfaces with regular nanostructures, investigating the relative magnitude of the contributions appearing in successive orders. The method is then employed for estimating the resolution limit of an idealized Near-Field Scanning Thermal Microscope (NSThM).Comment: 10 pages, 7 figure

Perturbation theory for plasmonic eigenvalues

We develop a perturbative approach for calculating, within the quasistatic approximation, the shift of surface resonances in response to a deformation of a dielectric volume. Our strategy is based on the conversion of the homogeneous system for the potential which determines the plasmonic eigenvalues into an inhomogeneous system for the potential's derivative with respect to the deformation strength, and on the exploitation of the corresponding compatibility condition. The resulting general expression for the first-order shift is verified for two explicitly solvable cases, and for a realistic example of a deformed nanosphere. It can be used for scanning the huge parameter space of possible shape fluctuations with only quite small computational effort

Identification of ion-channel modulators that protect against aminoglycoside-induced hair cell death

Aminoglycoside antibiotics are used to treat life-threatening bacterial infections but can cause deafness due to hair cell death in the inner ear. Compounds have been described that protect zebrafish lateral line hair cells from aminoglycosides, but few are effective in the cochlea. As the aminoglycosides interact with several ion channels, including the mechanoelectrical transducer (MET) channels by which they can enter hair cells, we screened 160 ion-channel modulators, seeking compounds that protect cochlear outer hair cells (OHCs) from aminoglycoside-induced death in vitro. Using zebrafish, 72 compounds were identified that either reduced loading of the MET-channel blocker FM 1-43FX, decreased Texas red–conjugated neomycin labeling, or reduced neomycin-induced hair cell death. After testing these 72 compounds, and 6 structurally similar compounds that failed in zebrafish, 13 were found that protected against gentamicin-induced death of OHCs in mouse cochlear cultures, 6 of which are permeant blockers of the hair cell MET channel. None of these compounds abrogated aminoglycoside antibacterial efficacy. By selecting those without adverse effects at high concentrations, 5 emerged as leads for developing pharmaceutical otoprotectants to alleviate an increasing clinical problem

MEMS-based Gyroscopes as Physical Unclonable Functions

We are at the dawn of a hyper connectivity age otherwise known as the Internet of Things (IoT). It is widely accepted that to be able to reap all benefits from the IoT promise, device security will be of paramount importance. A key requirement for most security solutions is the ability to provide secure cryptographic key storage in a way that will easily scale in the IoT age. In this paper, we focus on providing such a solution based on Physical Unclonable Functions (PUFs). To this end, we focus on microelectromechanical systems (MEMS)-based gyroscopes and show via wafer-level measurements and simulations, that it is feasible to use the physical and electrical properties of these sensors for cryptographic key generation. After identifying the most promising features, we propose a novel quantization scheme to extract bit strings from the MEMS analog measurements. We provide upper and lower bounds for the minimum entropy of the bit strings derived from the measurements and fully analyze the intra- and inter-class distributions across the operation range of the MEMS device. We complement these measurements via Monte-Carlo simulations based on the distributions of the parameters measured on actual devices. We also propose and evaluate a key derivation procedure based on fuzzy extractors for Hamming distance, using the min-entropy estimates obtained to derive a full entropy 128-bit key, requiring 1219-bits of helper data with an (authentication) failure probability of 4x10^-7. Thereby, we present a complete cryptographic key generation chain. In addition, we propose a dedicated MEMS-PUF design, which is superior to our measured sensor, in terms of chip area, quality and quantity of key seed features

ITIH5 mediates epigenetic reprogramming of breast cancer cells

Extracellular matrix (ECM) is known to maintain epithelial integrity. In carcinogenesis ECM degradation triggers metastasis by controlling migration and differentiation including cancer stem cell (CSC) characteristics. The ECM-modulator inter- α-trypsin inhibitor heavy chain family member five (ITIH5) was recently identified as tumor suppressor potentially involved in impairing breast cancer progression but molecular mechanisms underlying its function are still elusive