Critical fluctuations and random-anisotropy glass transition in nematic elastomers

We carry out a detailed deuterium NMR study of local nematic ordering in polydomain nematic elastomers. This system has a close analogy to the random-anisotropy spin glass. We find that, in spite of the quadrupolar nematic symmetry in 3-dimensions requiring a first-order transition, the order parameter in the quenched ``nematic glass'' emerges via a continuous phase transition. In addition, by a careful analysis of the NMR line shape, we deduce that the local director fluctuations grow in a critical manner around the transition point. This could be the experimental evidence for the Aizenman-Wehr theorem about the quenched impurities changing the order of discontinuous transition

A model for the generic alpha relaxation of viscous liquids

Dielectric measurements on molecular liquids just above the glass transition indicate that alpha relaxation is characterized by a generic high-frequency loss varying as $\omega^{-1/2}$, whereas deviations from this come from one or more low-lying beta processes [Olsen et al, Phys. Rev. Lett. {\bf 86} (2001) 1271]. Assuming that long-wavelength fluctuations dominate the dynamics, a model for the dielectric alpha relaxation based on the simplest coupling between the density and dipole density fields is proposed here. The model, which is solved in second order perturbation theory in the Gaussian approximation, reproduces the generic features of alpha relaxation

Diffusion on random site percolation clusters. Theory and NMR microscopy experiments with model objects

Quasi two-dimensional random site percolation model objects were fabricate based on computer generated templates. Samples consisting of two compartments, a reservoir of H$_2$O gel attached to a percolation model object which was initially filled with D$_2$O, were examined with NMR (nuclear magnetic resonance) microscopy for rendering proton spin density maps. The propagating proton/deuteron inter-diffusion profiles were recorded and evaluated with respect to anomalous diffusion parameters. The deviation of the concentration profiles from those expected for unobstructed diffusion directly reflects the anomaly of the propagator for diffusion on a percolation cluster. The fractal dimension of the random walk, $d_w$, evaluated from the diffusion measurements on the one hand and the fractal dimension, $d_f$, deduced from the spin density map of the percolation object on the other permits one to experimentally compare dynamical and static exponents. Approximate calculations of the propagator are given on the basis of the fractional diffusion equation. Furthermore, the ordinary diffusion equation was solved numerically for the corresponding initial and boundary conditions for comparison. The anomalous diffusion constant was evaluated and is compared to the Brownian case. Some ad hoc correction of the propagator is shown to pay tribute to the finiteness of the system. In this way, anomalous solutions of the fractional diffusion equation could experimentally be verified for the first time.Comment: REVTeX, 12 figures in GIF forma

Pomalidomide and dexamethasone grant rapid haematologic responses in patients with relapsed and refractory AL amyloidosis: a European retrospective series of 153 patients

Pomalidomide demonstrated activity in the treatment of AL amyloidosis in three phase II clinical trials. We evaluated the safety and efficacy of 28-day cycles of pomalidomide and dexamethasone in 153 previously treated patients with systemic AL amyloidosis. Ninety-nine (65%) were refractory to the last line of therapy and 54 (35%) had relapsed. The median number of previous lines of therapy was 3 (range: 2–7): 143 patients (93%) previously received bortezomib, 124 (81%) lenalidomide, 114 (75%) oral melphalan, and 37 (24%) underwent autologous stem cell transplant. At the completion of cycle 6, 68 (44%) patients obtained at least partial haematologic response, with 5 complete responses (CR, 3%), 35 very good partial responses (VGPR, 23%). Haematologic response resulted in improved overall survival (median survival 50 vs. 27 months, p = .033) in a 6 months landmark analysis. Obtaining at least partial response was also associated with a significant improvement of the progression-free survival (median PFS 37 vs. 18 months, p < .001). Pomalidomide is an effective treatment for heavily pre-treated patients with AL amyloidosis. Haematologic responses are associated with an overall survival advantage

Proton Spin-Lattice Relaxation in Organic Molecular Solids: Polymorphism and the Dependence on Sample Preparation

We report solid‐state nuclear magnetic resonance 1H spin‐lattice relaxation, single‐crystal X‐ray diffraction, powder X‐ray diffraction, field emission scanning electron microscopy, and differential scanning calorimetry in solid samples of 2‐ethylanthracene (EA) and 2‐ethylanthraquinone (EAQ) that have been physically purified in different ways from the same commercial starting compounds. The solid‐state 1H spin‐lattice relaxation is always non‐exponential at high temperatures as expected when CH3 rotation is responsible for the relaxation. The 1H spin‐lattice relaxation experiments are very sensitive to the “several‐molecule” (clusters) structure of these van der Waals molecular solids. In the three differently prepared samples of EAQ, the relaxation also becomes very non‐exponential at low temperatures. This is very unusual and the decay of the nuclear magnetization can be fitted with both a stretched exponential and a double exponential. This unusual result correlates with the powder X‐ray diffractometry results and suggests that the anomalous relaxation is due to crystallites of two (or more) different polymorphs (concomitant polymorphism)

Magnetic Resonance Water Proton Relaxation in Protein Solutions and Tissue: T1ρ Dispersion Characterization

BACKGROUND: Image contrast in clinical MRI is often determined by differences in tissue water proton relaxation behavior. However, many aspects of water proton relaxation in complex biological media, such as protein solutions and tissue are not well understood, perhaps due to the limited empirical data. PRINCIPAL FINDINGS: Water proton T(1), T(2), and T(1rho) of protein solutions and tissue were measured systematically under multiple conditions. Crosslinking or aggregation of protein decreased T(2) and T(1rho), but did not change high-field T(1). T(1rho) dispersion profiles were similar for crosslinked protein solutions, myocardial tissue, and cartilage, and exhibited power law behavior with T(1rho)(0) values that closely approximated T(2). The T(1rho) dispersion of mobile protein solutions was flat above 5 kHz, but showed a steep curve below 5 kHz that was sensitive to changes in pH. The T(1rho) dispersion of crosslinked BSA and cartilage in DMSO solvent closely resembled that of water solvent above 5 kHz but showed decreased dispersion below 5 kHz. CONCLUSIONS: Proton exchange is a minor pathway for tissue T(1) and T(1rho) relaxation above 5 kHz. Potential models for relaxation are discussed, however the same molecular mechanism appears to be responsible across 5 decades of frequencies from T(1rho) to T(1)

Mesodynamics in the SARS nucleocapsid measured by NMR field cycling

Protein motions on all timescales faster than molecular tumbling are encoded in the spectral density. The dissection of complex protein dynamics is typically performed using relaxation rates determined at high and ultra-high field. Here we expand this range of the spectral density to low fields through field cycling using the nucleocapsid protein of the SARS coronavirus as a model system. The field-cycling approach enables site-specific measurements of R1 at low fields with the sensitivity and resolution of a high-field magnet. These data, together with high-field relaxation and heteronuclear NOE, provide evidence for correlated rigid-body motions of the entire β-hairpin, and corresponding motions of adjacent loops with a time constant of 0.8 ns (mesodynamics). MD simulations substantiate these findings and provide direct verification of the time scale and collective nature of these motions

Gaussian Process-based prediction of memory performance and biomarker status in ageing and Alzheimer's disease-A systematic model evaluation

Neuroimaging markers based on Magnetic Resonance Imaging (MRI) combined with various other measures (such as genetic covariates, biomarkers, vascular risk factors, neuropsychological tests etc.) might provide useful predictions of clinical outcomes during the progression towards Alzheimer's disease (AD). The use of multiple features in predictive frameworks for clinical outcomes has become increasingly prevalent in AD research. However, many studies do not focus on systematically and accurately evaluating combinations of multiple input features. Hence, the aim of the present work is to explore and assess optimal combinations of various features for MR-based prediction of (1) cognitive status and (2) biomarker positivity with a multi kernel learning Gaussian process framework. The explored features and parameters included (A) combinations of brain tissues, modulation, smoothing, and image resolution;(B) incorporating demographics & clinical covariates;(C) the impact of the size of the training data set;(D) the influence of dimensionality reduction and the choice of kernel types. The approach was tested in a large German cohort including 959 subjects from the multicentric longitudinal study of cognitive impairment and dementia (DELCODE). Our evaluation suggests the best prediction of memory performance was obtained for a combination of neuroimaging markers, demographics, genetic information (ApoE4) and CSF biomarkers explaining 57% of outcome variance in out-of sample predictions. The highest performance for A 42/40 status classification was achieved for a combination of demographics, ApoE4, and a memory score while usage of structural MRI further improved the classification of individual patient's pTau status

Gaussian Process-based prediction of memory performance and biomarker status in ageing and Alzheimer's disease-A systematic model evaluation

Neuroimaging markers based on Magnetic Resonance Imaging (MRI) combined with various other measures (such as genetic covariates, biomarkers, vascular risk factors, neuropsychological tests etc.) might provide useful predictions of clinical outcomes during the progression towards Alzheimer's disease (AD). The use of multiple features in predictive frameworks for clinical outcomes has become increasingly prevalent in AD research. However, many studies do not focus on systematically and accurately evaluating combinations of multiple input features. Hence, the aim of the present work is to explore and assess optimal combinations of various features for MR-based prediction of (1) cognitive status and (2) biomarker positivity with a multi kernel learning Gaussian process framework. The explored features and parameters included (A) combinations of brain tissues, modulation, smoothing, and image resolution;(B) incorporating demographics & clinical covariates;(C) the impact of the size of the training data set;(D) the influence of dimensionality reduction and the choice of kernel types. The approach was tested in a large German cohort including 959 subjects from the multicentric longitudinal study of cognitive impairment and dementia (DELCODE). Our evaluation suggests the best prediction of memory performance was obtained for a combination of neuroimaging markers, demographics, genetic information (ApoE4) and CSF biomarkers explaining 57% of outcome variance in out-of sample predictions. The highest performance for A 42/40 status classification was achieved for a combination of demographics, ApoE4, and a memory score while usage of structural MRI further improved the classification of individual patient's pTau status