Free energy and molecular dynamics calculations for the cubic-tetragonal phase transition in zirconia

The high-temperature cubic-tetragonal phase transition of pure stoichiometric zirconia is studied by molecular dynamics (MD) simulations and within the framework of the Landau theory of phase transformations. The interatomic forces are calculated using an empirical, self-consistent, orthogonal tight-binding (SC-TB) model, which includes atomic polarizabilities up to the quadrupolar level. A first set of standard MD calculations shows that, on increasing temperature, one particular vibrational frequency softens. The temperature evolution of the free energy surfaces around the phase transition is then studied with a second set of calculations. These combine the thermodynamic integration technique with constrained MD simulations. The results seem to support the thesis of a second-order phase transition but with unusual, very anharmonic behaviour above the transition temperature

Electrospun amplified fiber optics

A lot of research is focused on all-optical signal processing, aiming to obtain effective alternatives to existing data transmission platforms. Amplification of light in fiber optics, such as in Erbium-doped fiber amplifiers, is especially important for an efficient signal transmission. However, the complex fabrication methods, involving high-temperature processes performed in highly pure environment, slow down the fabrication and make amplified components expensive with respect to an ideal, high-throughput and room temperature production. Here, we report on near infrared polymer fiber amplifiers, working over a band of about 20 nm. The fibers are cheap, spun with a process entirely carried out at room temperature, and show amplified spontaneous emission with good gain coefficients as well as low optical losses (a few cm^-1). The amplification process is favoured by the high fiber quality and low self-absorption. The found performance metrics promise to be suitable for short-distance operation, and the large variety of commercially-available doping dyes might allow for effective multi-wavelength operation by electrospun amplified fiber optics.Comment: 27 pages, 8 figure

Combinations of β-lactam or aminoglycoside antibiotics with plectasin are synergistic against methicillin-sensitive and methicillin-resistant Staphylococcus aureus.

Bacterial infections remain the leading killer worldwide which is worsened by the continuous emergence of antibiotic resistance. In particular, methicillin-sensitive (MSSA) and methicillin-resistant Staphylococcus aureus (MRSA) are prevalent and the latter can be difficult to treat. The traditional strategy of novel therapeutic drug development inevitably leads to emergence of resistant strains, rendering the new drugs ineffective. Therefore, rejuvenating the therapeutic potentials of existing antibiotics offers an attractive novel strategy. Plectasin, a defensin antimicrobial peptide, potentiates the activities of other antibiotics such as β-lactams, aminoglycosides and glycopeptides against MSSA and MRSA. We performed in vitro and in vivo investigations to test against genetically diverse clinical isolates of MSSA (n = 101) and MRSA (n = 115). Minimum inhibitory concentrations (MIC) were determined by the broth microdilution method. The effects of combining plectasin with β-lactams, aminoglycosides and glycopeptides were examined using the chequerboard method and time kill curves. A murine neutropenic thigh model and a murine peritoneal infection model were used to test the effect of combination in vivo. Determined by factional inhibitory concentration index (FICI), plectasin in combination with aminoglycosides (gentamicin, neomycin or amikacin) displayed synergistic effects in 76-78% of MSSA and MRSA. A similar synergistic response was observed when plectasin was combined with β-lactams (penicillin, amoxicillin or flucloxacillin) in 87-89% of MSSA and MRSA. Interestingly, no such interaction was observed when plectasin was paired with vancomycin. Time kill analysis also demonstrated significant synergistic activities when plectasin was combined with amoxicillin, gentamicin or neomycin. In the murine models, plectasin at doses as low as 8 mg/kg augmented the activities of amoxicillin and gentamicin in successful treatment of MSSA and MRSA infections. We demonstrated that plectasin strongly rejuvenates the therapeutic potencies of existing antibiotics in vitro and in vivo. This is a novel strategy that can have major clinical implications in our fight against bacterial infections

Immunotherapy of lung cancer: An update

In Germany lung cancer is the leading cause of cancer-associated death in men. Surgery, chemotherapy and radiation may enhance survival of patients suffering from lung cancer but the enhancement is typically transient and mostly absent with advanced disease; eventually more than 90% of lung cancer patients will die of disease. New approaches to the treatment of lung cancer are urgently needed. Immunotherapy may represent one new approach with low toxicity and high specificity but implementation has been a challenge because of the poor antigenic characterization of these tumors and their ability to escape immune responses. Several different immunotherapeutic treatment strategies have been developed. This review examines the current state of development and recent advances with respect to non-specific immune stimulation, cellular immunotherapy ( specific and non-specific), therapeutic cancer vaccines and gene therapy for lung cancer. The focus is primarily placed on immunotherapeutic cancer treatments that are already in clinical trial or well progressed in preclinical studies. Although there seems to be a promising future for immunotherapy in lung cancer, presently there is not standard immunotherapy available for clinical routine

Relative energetics and structural properties of zirconia using a self-consistent tight-binding model

We describe an empirical, self-consistent, orthogonal tight-binding model for zirconia, which allows for the polarizability of the anions at dipole and quadrupole levels and for crystal field splitting of the cation d orbitals. This is achieved by mixing the orbitals of different symmetry on a site with coupling coefficients driven by the Coulomb potentials up to octapole level. The additional forces on atoms due to the self-consistency and polarizabilities are exactly obtained by straightforward electrostatics, by analogy with the Hellmann-Feynman theorem as applied in first-principles calculations. The model correctly orders the zero temperature energies of all zirconia polymorphs. The Zr-O matrix elements of the Hamiltonian, which measure covalency, make a greater contribution than the polarizability to the energy differences between phases. Results for elastic constants of the cubic and tetragonal phases and phonon frequencies of the cubic phase are also presented and compared with some experimental data and first-principles calculations. We suggest that the model will be useful for studying finite temperature effects by means of molecular dynamics.Comment: to be published in Physical Review B (1 march 2000

Measurement of the Proton and Deuteron Spin Structure Function g_1 in the Resonance Region

We have measured the proton and deuteron spin structure functions g_1^p and g_1^d in the region of the nucleon resonances for W^2 < 5 GeV^2 and $Q^2\simeq 0.5$ and $Q^2\simeq 1.2$ GeV^2 by inelastically scattering 9.7 GeV polarized electrons off polarized $^{15}NH_3$ and $^{15}ND_3$ targets. We observe significant structure in g_1^p in the resonance region. We have used the present results, together with the deep-inelastic data at higher W^2, to extract $\Gamma(Q^2)\equiv\int_0^1 g_1(x,Q^2) dx$. This is the first information on the low-Q^2 evolution of Gamma toward the Gerasimov-Drell-Hearn limit at Q^2 = 0.Comment: 7 pages, 2 figure

Experimental Quantum Hamiltonian Learning

Efficiently characterising quantum systems, verifying operations of quantum devices and validating underpinning physical models, are central challenges for the development of quantum technologies and for our continued understanding of foundational physics. Machine-learning enhanced by quantum simulators has been proposed as a route to improve the computational cost of performing these studies. Here we interface two different quantum systems through a classical channel - a silicon-photonics quantum simulator and an electron spin in a diamond nitrogen-vacancy centre - and use the former to learn the latter's Hamiltonian via Bayesian inference. We learn the salient Hamiltonian parameter with an uncertainty of approximately $10^{-5}$. Furthermore, an observed saturation in the learning algorithm suggests deficiencies in the underlying Hamiltonian model, which we exploit to further improve the model itself. We go on to implement an interactive version of the protocol and experimentally show its ability to characterise the operation of the quantum photonic device. This work demonstrates powerful new quantum-enhanced techniques for investigating foundational physical models and characterising quantum technologies

Activation of Methanogenesis in Arid Biological Soil Crusts Despite the Presence of Oxygen

Methanogenesis is traditionally thought to occur only in highly reduced, anoxic environments. Wetland and rice field soils are well known sources for atmospheric methane, while aerated soils are considered sinks. Although methanogens have been detected in low numbers in some aerated, and even in desert soils, it remains unclear whether they are active under natural oxic conditions, such as in biological soil crusts (BSCs) of arid regions. To answer this question we carried out a factorial experiment using microcosms under simulated natural conditions. The BSC on top of an arid soil was incubated under moist conditions in all possible combinations of flooding and drainage, light and dark, air and nitrogen headspace. In the light, oxygen was produced by photosynthesis. Methane production was detected in all microcosms, but rates were much lower when oxygen was present. In addition, the δ13C of the methane differed between the oxic/oxygenic and anoxic microcosms. While under anoxic conditions methane was mainly produced from acetate, it was almost entirely produced from H2/CO2 under oxic/oxygenic conditions. Only two genera of methanogens were identified in the BSC-Methanosarcina and Methanocella; their abundance and activity in transcribing the mcrA gene (coding for methyl-CoM reductase) was higher under anoxic than oxic/oxygenic conditions, respectively. Both methanogens also actively transcribed the oxygen detoxifying gene catalase. Since methanotrophs were not detectable in the BSC, all the methane produced was released into the atmosphere. Our findings point to a formerly unknown participation of desert soils in the global methane cycle

Cytoplasmic p53 couples oncogene-driven glucose metabolism to apoptosis and is a therapeutic target in glioblastoma.

Cross-talk among oncogenic signaling and metabolic pathways may create opportunities for new therapeutic strategies in cancer. Here we show that although acute inhibition of EGFR-driven glucose metabolism induces only minimal cell death, it lowers the apoptotic threshold in a subset of patient-derived glioblastoma (GBM) cells. Mechanistic studies revealed that after attenuated glucose consumption, Bcl-xL blocks cytoplasmic p53 from triggering intrinsic apoptosis. Consequently, targeting of EGFR-driven glucose metabolism in combination with pharmacological stabilization of p53 with the brain-penetrant small molecule idasanutlin resulted in synthetic lethality in orthotopic glioblastoma xenograft models. Notably, neither the degree of EGFR-signaling inhibition nor genetic analysis of EGFR was sufficient to predict sensitivity to this therapeutic combination. However, detection of rapid inhibitory effects on [18F]fluorodeoxyglucose uptake, assessed through noninvasive positron emission tomography, was an effective predictive biomarker of response in vivo. Together, these studies identify a crucial link among oncogene signaling, glucose metabolism, and cytoplasmic p53, which may potentially be exploited for combination therapy in GBM and possibly other malignancies