A novel self-assembled oligopeptide amphiphile for biomimetic mineralization of enamel

Background Researchers are looking for biomimetic mineralization of ena/mel to manage dental erosion. This study evaluated biomimetic mineralization of demineralized enamel induced by a synthetic and self-assembled oligopeptide amphiphile (OPA). Results The results showed that the OPA self-assembled into nano-fibres in the presence of calcium ions and in neutral acidity. The OPA was alternately immersed in calcium chloride and sodium hypophosphate solutions to evaluate its property of mineralization. Transmission electron microscopy (TEM) and scanning electron microscopy (SEM) showed nucleation and growth of amorphous calcium phosphate along the self-assembled OPA nano-fibres when it was repetitively exposed to solutions with calcium and phosphate ions. Energy dispersive spectrometry (EDS) confirmed that these nano-particles contained calcium and phosphate. Furthermore, electron diffraction pattern suggested that the nano-particles precipitated on OPA nano-fibres were comparable to amorphous calcium phosphate. Acid-etched human enamel slices were incubated at 37°C in metastable calcium phosphate solution with the OPA for biomimetic mineralization. SEM and X-ray diffraction indicated that the OPA induced the formation of hydroxyapatite crystals in organized bundles on etched enamel. TEM micrographs revealed there were 20–30 nm nano-amorphous calcium phosphate precipitates in the biomimetic mineralizing solution. The particles were found separately bound to the oligopeptide fibres. Biomimetic mineralization with or without the oligopeptide increased demineralized enamel microhardness. Conclusions A novel OPA was successfully fabricated, which fostered the biomimetic mineralization of demineralized enamel. It is one of the primary steps towards the design and construction of novel biomaterial for future clinical therapy of dental erosion.published_or_final_versio

High volumetric energy density capacitors based on new electrode material lanthanum nitride

This is the author accepted manuscript. The final version is available from the American Chemical Society via the DOI in this recordLaN is synthesized via calcining La2O3 in NH3 and studied as capacitive material for energy storage. A volumetric capacitance of 951.3 F cm-3 was found in 1 mol dm-3 Na2SO4 using a current density of 1 Ag-1, with less than 1% loss of capacitance being experienced after 5000 cycles. In addition, 87.3% of the initial capacitance remained at a current density of 10 A g-1. LaN exhibits high capacitance that is attributed to subsurface space charge accumulation with a possible electric double-layer capacitor component. A reversible electrode process ensures long cycle life and favorable electrical charge transfer. The assembled LaN symmetrical capacitor showed high volumetric energy densities, facilitating high-duty applications.National Natural Science Foundation of ChinaFoundation for Innovation Groups of Basic Research in Gansu Provinc

Enabling decision trend analysis with interactive scatter plot matrices visualization

© 2015 Elsevier Ltd. This paper presents a new interactive scatter plot visualization for multi-dimensional data analysis. We apply Rough Set Theory (RST) to reduce the visual complexity through dimensionality reduction. We use an innovative point-to-region mouse click concept to enable direct interactions with scatter points that are theoretically impossible. To show the decision trend we use a virtual Z dimension to display a set of linear flows showing approximation of the decision trend. We conducted case studies to demonstrate the effectiveness and usefulness of our new technique for analyzing the property of three popular data sets including wine quality, wages and cars. The paper also includes a pilot usability study to evaluate parallel coordinate visualization with scatter plot matrices visualization with RST results

Calmodulin in complex with the first IQ motif of myosin-5a functions as an intact calcium sensor

© 2016, National Academy of Sciences. All rights reserved. The motor function of vertebrate myosin-5a is inhibited by its tail in a Ca2+-dependent manner. We previously demonstrated that the calmodulin (CaM) bound to the first isoleucine-glutamine (IQ) motif (IQ1) of myosin-5a is responsible for the Ca2+-dependent regulation of myosin-5a. We have solved the crystal structure of a truncated myosin-5a containing the motor domain and IQ1 (MD-IQ1) complexed with Ca2+-bound CaM (Ca2+-CaM) at 2.5-Å resolution. Compared with the structure of the MD-IQ1 complexed with essential light chain (an equivalent of apo-CaM), MD-IQ1/Ca2+-CaM displays large conformational differences in IQ1/CaM and little difference in the motor domain. In the MD-IQ1/Ca2+-CaM structure, the N-lobe and the C-lobe of Ca2+-CaM adopt an open conformation and grip the C-terminal and the N-terminal portions of the IQ1, respectively. Remarkably, the interlobe linker of CaM in IQ1/Ca2+-CaM is in a position opposite that in IQ1/apo-CaM, suggesting that CaM flip-flops relative to the IQ1 during the Ca2+ transition. We demonstrated that CaM continuously associates with the IQ1 during the Ca2+ transition and that the binding of CaM to IQ1 increases Ca2+ affinity and substantially changes the kinetics of the Ca2+ transition, suggesting that the IQ1/CaM complex functions as an intact Ca2+ sensor responding to distinct calcium signals

On Accelerating Diffusion-Based Sampling Processes via Improved Integration Approximation

This is the final version. Available from ICLR via the link in this recordA popular approach to sample a diffusion-based generative model is to solve an ordinary differential equation (ODE). In existing samplers, the coefficients of the ODE solvers are pre-determined by the ODE formulation, the reverse discrete timesteps, and the employed ODE methods. In this paper, we consider accelerating several popular ODE-based sampling processes (including DDIM, DPM-Solver++, and EDM) by optimizing certain coefficients via improved integration approxi mation (IIA). We propose to minimize, for each time step, a mean squared error (MSE) function with respect to the selected coefficients. The MSE is constructed by applying the original ODE solver for a set of fine-grained timesteps, which in principle provides a more accurate integration approximation in predicting the next diffusion state. The proposed IIA technique does not require any change of a pre-trained model, and only introduces a very small computational overhead for solving a number of quadratic optimization problems. Extensive experiments show that considerably better FID scores can be achieved by using IIA-DDIM, IIA-DPM-Solver++, and IIA-EDM than the original counterparts when the neural function evaluation (NFE) is small (i.e., less than 25).Nippon Telegraph and Telephone Corporatio

A DNN Optimizer that Improves over AdaBelief by Suppression of the Adaptive Stepsize Range

This is the final version. Available from Transactions on Machine Learning Research via the link in this recordWe make contributions towards improving adaptive-optimizer performance. Our improvements are based on suppression of the range of adaptive stepsizes in the AdaBelief optimizer. Firstly, we show that the particular placement of the parameter ϵ within the update expressions of AdaBelief reduces the range of the adaptive stepsizes, making AdaBelief closer to SGD with momentum. Secondly, we extend AdaBelief by further suppressing the range of the adaptive stepsizes. To achieve the above goal, we perform mutual layerwise vector projections between the gradient gt and its first momentum mt before using them to estimate the second momentum. The new optimization method is referred to as Aida. Thirdly, extensive experimental results show that Aida outperforms nine optimizers when training transformers and LSTMs for NLP, and VGG and ResNet for image classification over CIAF10 and CIFAR100 while matching the best performance of the nine methods when training WGAN-GP models for image generation tasks. Furthermore, Aida produces higher validation accuracies than AdaBelief for training ResNet18 over ImageNet. Our implementation is available at https://github.com/guoqiang-zhang-x/Aida-OptimizerNippon Telegraph and Telephone Corporatio

Fyn Kinase regulates GluN2B subunit-dominant NMDA receptors in human induced pluripotent stem cell-derived neurons

NMDA receptor (NMDAR)-mediated fast excitatory neurotransmission is implicated in a broad range of physiological and pathological processes in the mammalian central nervous system. The function and regulation of NMDARs have been extensively studied in neurons from rodents and other non-human species, and in recombinant expression systems. Here, we investigated human NMDARs in situ by using neurons produced by directed differentiation of human induced pluripotent stem cells (iPSCs). The resultant cells showed electrophysiological characteristics demonstrating that they are bona fide neurons. In particular, human iPSC-derived neurons expressed functional ligand-gated ion channels, including NMDARs, AMPA receptors, GABAA receptors, as well as glycine receptors. Pharmacological and electrophysiological properties of NMDAR-mediated currents indicated that these were dominated by receptors containing GluN2B subunits. The NMDAR currents were suppressed by genistein, a broad-spectrum tyrosine kinase inhibitor. The NMDAR currents were also inhibited by a Fyn-interfering peptide, Fyn(39-57), but not a Src-interfering peptide, Src(40-58). Together, these findings are the first evidence that tyrosine phosphorylation regulates the function of NMDARs in human iPSC-derived neurons. Our findings provide a basis for utilizing human iPSC-derived neurons in screening for drugs targeting NMDARs in neurological disorders