Interface-induced d-wave pairing

We discuss a scenario for interface-induced superconductivity involving pairing by dipolar excitations proximate to a two-dimensional electron system controlled by a transverse electric field. If the interface consists of transition metal oxide materials, the repulsive on-site Coulomb interaction is typically strong and a superconducting state is formed via exchange of non-local dipolar excitations in the d-wave channel. Perspectives to enhance the superconducting transition temperature are discussed.Comment: 4 pages, 3 figure

Calculation of the kinematics of hypoid gears towards developing a method for an equivalent crossed helical gear pair selection for use in tribological experimental evaluations

To experimentally verify power loss and friction for hypoid gears, measurements in a closed power-loop test rig are necessary. However, these are costly and mechanically complex, since they require additional spur gear reducers in the loop. ISO directives document the use of crossed helical gear pairs as virtual gears for hypoids to calculate the sliding velocity since, the flank geometry at the mean point can be precisely represented. The use of such pairs can be a cost effective and simpler alternative for testing purposes. However, the validity of this analogy regarding contact mechanics and tribology for the full mesh cycle has not been investigated hitherto. In the current study a new method for calculating the sliding and rolling speed along the full path of contact of a hypoid gear pair is presented. Cutter kinematics are considered, for the accurate definition of the contact bodies. Using TCA, the load distribution on the tooth under quasi-static conditions and the sliding velocity are calculated for comparison purposes. By applying a selection algorithm, a single experimental crossed helical gear pair is chosen aiming to simulate the contact conditions of hypoid gears. Two test scenarios are studied using EHL film thickness equations and friction models for evaluating the power loss. The contact is an elongated ellipse with varying directions of the sliding and sum velocities, which are considered in the model. The kinematic equivalence shows good agreement while the tribological equivalence is achievable using a reduced input torque

Structural characterization of cationic lipid–tRNA complexes

Despite considerable interest and investigations on cationic lipid–DNA complexes, reports on lipid–RNA interaction are very limited. In contrast to lipid–DNA complexes where lipid binding induces partial B to A and B to C conformational changes, lipid–tRNA complexation preserves tRNA folded state. This study is the first attempt to investigate the binding of cationic lipid with transfer RNA and the effect of lipid complexation on tRNA aggregation and condensation. We examine the interaction of tRNA with cholesterol (Chol), 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP), dioctadecyldimethylammoniumbromide (DDAB) and dioleoylphosphatidylethanolamine (DOPE), at physiological condition, using constant tRNA concentration and various lipid contents. FTIR, UV-visible, CD spectroscopic methods and atomic force microscopy (AFM) were used to analyze lipid binding site, the binding constant and the effects of lipid interaction on tRNA stability, conformation and condensation. Structural analysis showed lipid–tRNA interactions with G–C and A–U base pairs as well as the backbone phosphate group with overall binding constants of KChol = 5.94 (± 0.8) × 104 M–1, KDDAB = 8.33 (± 0.90) × 105 M–1, KDOTAP = 1.05 (± 0.30) × 105 M–1 and KDOPE = 2.75 (± 0.50) × 104 M–1. The order of stability of lipid–tRNA complexation is DDAB > DOTAP > Chol > DOPE. Hydrophobic interactions between lipid aliphatic tails and tRNA were observed. RNA remains in A-family structure, while biopolymer aggregation and condensation occurred at high lipid concentrations

Structural characterization of cationic lipid–tRNA complexes

Despite considerable interest and investigations on cationic lipid–DNA complexes, reports on lipid–RNA interaction are very limited. In contrast to lipid–DNA complexes where lipid binding induces partial B to A and B to C conformational changes, lipid–tRNA complexation preserves tRNA folded state. This study is the first attempt to investigate the binding of cationic lipid with transfer RNA and the effect of lipid complexation on tRNA aggregation and condensation. We examine the interaction of tRNA with cholesterol (Chol), 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP), dioctadecyldimethylammoniumbromide (DDAB) and dioleoylphosphatidylethanolamine (DOPE), at physiological condition, using constant tRNA concentration and various lipid contents. FTIR, UV-visible, CD spectroscopic methods and atomic force microscopy (AFM) were used to analyze lipid binding site, the binding constant and the effects of lipid interaction on tRNA stability, conformation and condensation. Structural analysis showed lipid–tRNA interactions with G–C and A–U base pairs as well as the backbone phosphate group with overall binding constants of KChol = 5.94 (± 0.8) × 104 M–1, KDDAB = 8.33 (± 0.90) × 105 M–1, KDOTAP = 1.05 (± 0.30) × 105 M–1 and KDOPE = 2.75 (± 0.50) × 104 M–1. The order of stability of lipid–tRNA complexation is DDAB > DOTAP > Chol > DOPE. Hydrophobic interactions between lipid aliphatic tails and tRNA were observed. RNA remains in A-family structure, while biopolymer aggregation and condensation occurred at high lipid concentrations

Transcriptional evidence for the "Reverse Warburg Effect" in human breast cancer tumor stroma and metastasis: Similarities with oxidative stress, inflammation, Alzheimer's disease, and "Neuron-Glia Metabolic Coupling"

Caveolin-1 (-/-) null stromal cells are a novel genetic model for cancer-associated fibroblasts and myofibroblasts. Here, we used an unbiased informatics analysis of transcriptional gene profiling to show that Cav-1 (-/-) bone-marrow derived stromal cells bear a striking resemblance to the activated tumor stroma of human breast cancers. More specifically, the transcriptional profiles of Cav-1 (-/-) stromal cells were most closely related to the primary tumor stroma of breast cancer patients that had undergone lymph-node (LN) metastasis. This is consistent with previous morphological data demonstrating that a loss of stromal Cav-1 protein (by immuno-histochemical staining in the fibroblast compartment) is significantly associated with increased LN-metastasis. We also provide evidence that the tumor stroma of human breast cancers shows a transcriptional shift towards oxidative stress, DNA damage/repair, inflammation, hypoxia, and aerobic glycolysis, consistent with the "Reverse Warburg Effect". Finally, the tumor stroma of "metastasis-prone" breast cancer patients was most closely related to the transcriptional profiles derived from the brains of patients with Alzheimer's disease. This suggests that certain fundamental biological processes are common to both an activated tumor stroma and neuro-degenerative stress. These processes may include oxidative stress, NO over-production (peroxynitrite formation), inflammation, hypoxia, and mitochondrial dysfunction, which are thought to occur in Alzheimer's disease pathology. Thus, a loss of Cav-1 expression in cancer-associated myofibroblasts may be a protein biomarker for oxidative stress, aerobic glycolysis, and inflammation, driving the "Reverse Warburg Effect" in the tumor micro-environment and cancer cell metastasis

Computational Fluorescence Suppression in Shifted Excitation Raman Spectroscopy

Fiber-based Raman spectroscopy in the context of &lt;italic&gt;in vivo&lt;/italic&gt; biomedical application suffers from the presence of background fluorescence from the surrounding tissue that might mask the crucial but inherently weak Raman signatures. One method that has shown potential for suppressing the background to reveal the Raman spectra is shifted excitation Raman spectroscopy (SER). SER collects multiple emission spectra by shifting the excitation by small amounts and uses these spectra to computationally suppress the fluorescence background based on the principle that Raman spectrum shifts with excitation while fluorescence spectrum does not. We introduce a method that utilizes the spectral characteristics of the Raman and fluorescence spectra to estimate them more effectively, and compare this approach against existing methods on real world datasets.</p