Ligand density-dependent influence of arginine–glycine–aspartate functionalized gold nanoparticles on osteogenic and adipogenic differentiation of mesenchymal stem cells

Extracellular matrix (ECM) plays a very important role in regulating cell function and fate. It is highly desirable to fabricate biomimetic models to investigate the role of ECM in stem cell differentiation. In this study, arginine–glycine–aspartate (RGD)-modified gold nanoparticles (Au NPs) with tunable surface ligand density were prepared to mimic the ECM microenvironment. Their effect on osteogenic and adipogenic differentiation of human mesenchymal stem cells (MSCs) was investigated. The biomimetic Au NPs were taken up by MSCs in a ligand density-dependent manner. The biomimetic NPs with a high RGD density had an inhibitive effect on the alkaline phosphatase (ALP) activity, calcium deposition, and osteogenic marker gene expression of MSCs. Their effect on oil droplet formation and adipogenic marker gene expression was negative when RGD density was low, while their effect was promotive when RGD density was high. The biomimetic Au NPs regulated the osteogenic and adipogenic differentiation of MSCs mainly through affecting the focal adhesion and cytoskeleton. This study highlights the roles of biomimetic NPs on stem cell differentiation that could provide a meaningful strategy in fabricating functional biomaterials for tissue engineering and biomedical applications.

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Fabrication of X-rays mask with carbon membrane for diffraction gratings

We have produced diffraction gratings for obtaining high resolution X-ray phase imaging, such as X-ray Talbot interferometer. These diffraction gratings were required to have a fine, high accuracy, high aspect ratio structure. Therefore, we decided to use the X-rays lithography technique that used synchrotron radiation of the directivity for a manufacture process. The accuracy of the completed structure depends largely on the accuracy of the X-ray mask. In our group, a resin material is conventionally used for the membrane of large X-ray masks. However, X-ray masks comprising a resin membrane have the disadvantage that, after several cycles of X-ray exposure, they crease and sag due to X-ray-derived heat. As a substitute for the conventional resin membrane, we experimentally fabricated a new X-ray mask using a carbon wafer membrane. The newly fabricated X-ray mask was subjected to X-ray exposure experiment. We succeeded in making the structure body which was almost shape. And the experimental results verified that the new mask did not deteriorate even when used repeatedly, demonstrating that it was highly durable.     

Translational lemmas for DLOGTIME-uniform circuits,alternating TMs,and PRAMs

We present translational lemmas for the three standard models of parallel computation, and apply them to obtain tight hierarchy results. It is shown that, for arbitrarily small rational constant , (i) there is a language which can be accepted by a -uniform circuit family of depth and size but not by any -uniform circuit family of depth and size , (ii) there is a language which can be accepted by a -time -space ATM with l worktapes but not by any -time -space ATM with the same l worktapes if the number of tape symbols is fixed, and (iii) there is a language which can be accepted by a -time PRAM with processors but not by any -time PRAM with processors. Here, c > 0, d ≥ 1, r ₁ > 1, and r ₂ ≥ 1 are arbitrary rational constants, and l ≥ 2 is an arbitrary integer. Preliminary versions of different parts of this paper appeared in Proc. MCU 2004 (LNCS 3354) and Proc. FCT 2005 (LNCS 3623).     

Simultaneous rate-synchrony codes in populations of spiking neurons

Firing rates and synchronous firing are often simultaneously relevant signals, and they independently or cooperatively represent external sensory inputs, cognitive events, and environmental situations such as body position. However, how rates and synchrony comodulate and which aspects of inputs are effectively encoded, particularly in the presence of dynamical inputs, are unanswered questions. We examine theoretically how mixed information in dynamic mean input and noise input is represented by dynamic population firing rates and synchrony. In a subthreshold regime, amplitudes of spatially uncorrelated noise are encoded up to a fairly high input frequency, but this requires both rate and synchrony output channels. In a suprathreshold regime, means and common noise amplitudes can be simultaneously and separately encoded by rates and synchrony, respectively, but the input frequency for which this is possible has a lower limit.     

Learning commutative deterministic finite state automata in polynomial time

We consider the problem of learning the commutative subclass of regular languages in the on-line model of predicting {0,1∼-valued functions from examples and reinforcements due to Littlestone [7,4]. We show that the entire class of commutative deterministic finite state automata (CDFAs) of an arbitrary alphabet sizek is predictable inO(s ^k) time with the worst case number of mistakes bounded above byO(s ^kk logs), wheres is the number of states in the target DFA. As a corollary, this result implies that the class of CDFAs is also PAC-learnable from random labeled examples in timeO(s ^k) with sample complexity, using a different class of representations. The mistake bound of our algorithm is within a polynomial, for a fixed alphabet size, of the lower boundO(s+k) we obtain by calculating the VC-dimension of the class. Our result also implies the predictability of the class of finite sets of commutative DFAs representing the finite unions of the languages accepted by the respective DFAs. Part of this work was supported by the Office of Naval Research under contract number N00014-87-K-0401 while the author was at the Department of Computer and Information Science, University of Pennsylvania, and N0014-86-K-0454 while at the Department of Computer and Information Sciences, U.C. Santa Cruz. The author’s email address is abe@IBL.CL.nec.co.jp     

Role of disorder-order transformation in consolidation of ceramics

The ordering of stacking-disordered silicon carbide prepared from the elements by high energy ball milling was investigated during sintering. A sharp increase in density in the temperature region 1700–1800°C was associated with a decrease in the disorder. Samples which had low disorder density showed a more continuous sintering behavior with temperature. Highly dense (up to 99% relative density) SiC can be obtained at 1900°C under a pressure of 70 MPa with no hold time. Similar results were observed for structurally disordered carbon with 10 at% of boron. The sintering behavior exhibited an abrupt density increase in the narrow temperature region of 1450–1600°C and was associated with disorder-order transformation.     

Heavy-ion-induced luminescence of amorphous SiO2 during nanoparticle formation

Silica glass was implanted with negative 60 keV Cu ions at an ion flux from 5 to 75 μA/cm² up to a fluence of 1 × 10¹⁷ ions/cm² at initial sample temperatures of 300, 573 and 773 K. Spectra of ion-induced photon emission (IIPE) were collected in situ in the range from 250 to 850 nm. Optical absorption spectra of implanted specimens were ex situ measured in the range from 190 to 2500 nm.

IIPE spectra showed a broad band centered around 560 nm (2.2 eV) that was assigned to Cu⁺ solutes. The band appeared at the onset of irradiation, increased in intensity up to a fluence of about 5 × 10¹⁵ ions/cm² and then gradually decreased indicating three stage of the ion beam synthesis of nanoclusters: accumulation of implants, nucleation and growth nanoclusters. The IIPE intensity normalized on the ion flux is independent on the ion flux below 20 μA/cm²at higher fluences. The intensity of the band increased with increasing samples temperature, when optical absorption spectra reveal the increase of Cu nanoparticles size.     

Efficient distribution-free population learning of simple concepts

We consider a variant of the ‘population learning model’ proposed by Kearns and Seung [8], in which the learner is required to be ‘distribution-free’ as well as computationally efficient. A population learner receives as input hypotheses from a large population of agents and produces as output its final hypothesis. Each agent is assumed to independently obtain labeled sample for the target concept and output a hypothesis. A polynomial time population learner is said to PAC-learn a concept class, if its hypothesis is probably approximately correct whenever the population size exceeds a certain bound which is polynomial, even if the sample size for each agent is fixed at some constant. We exhibit some general population learning strategies, and some simple concept classes that can be learned by them. These strategies include the ‘supremum hypothesis finder’, the ‘minimum superset finder’ (a special case of the ‘supremum hypothesis finder’), and various voting schemes. When coupled with appropriate agent algorithms, these strategies can learn a variety of simple concept classes, such as the ‘high–low game’, conjunctions, axis-parallel rectangles and others. We give upper bounds on the required population size for each of these cases, and show that these systems can be used to obtain a speed up from the ordinary PAC-learning model [11], with appropriate choices of sample and population sizes. With the population learner restricted to be a voting scheme, what we have is effectively a model of ‘population prediction’, in which the learner is to predict the value of the target concept at an arbitrarily drawn point, as a threshold function of the predictions made by its agents on the same point. We show that the population learning model is strictly more powerful than the population prediction model. Finally, we consider a variant of this model with classification noise, and exhibit a population learner for the class of conjunctions in this model. This revised version was published online in June 2006 with corrections to the Cover Date.     

Optical CO2 sensor with the combination of colorimetric change of α-naphtholphthalein and internal reference fluorescent porphyrin dye

A new optical CO₂ sensor based on the overlay of the CO₂ induced absorbance change of pH indicator dye α-naphtholphthalein with the fluorescence of tetraphenylporphyrin (TPP) was developed. The observed luminescence intensity from TPP at 655 nm increased with increasing the CO₂ concentration. The ratio I₁₀₀/I₀ values of the sensing films consisting of α-naphtholphthalein in ethyl cellulose layer and TPP in polystyrene layer, where I₀ and I₁₀₀ represent the detected luminescence intensities from a layer exposed to 100% nitrogen and 100% CO₂, respectively, that the sensitivity of the sensor, are more than 53.9. The response and recovery times of the sensing films consisting of α-naphtholphthalein in ethyl cellulose layer and TPP in polystyrene layer were less than 5 s for switching from nitrogen to CO₂, and for switching from CO₂ to nitrogen. The signal changes were fully reversible and no hysterisis was observed during the measurements. The highly sensitive optical CO₂ sensor based on fluorescence intensity changes of TPP due to the absorption change of α-naphtholphthalein with CO₂ was achieved.     

Laser Photolysis Study on Mechanism and Efficiency of Electron Transfer Between Fullerenes (C60 and C70) and Tetraselenafulvalenes

Abstract

Efficient electron-transfer reactions from three kind of tetraselenafulvalenes (TSeF's) to photoexcited triplet state of C₆₀ or C₇₀ in polar solvents have been confirmed by transient absorption spectroscopy observing the decay of ³C₆₀*/³C₇₀* and rise of C₆₀ ^??/C₇₀ ^??. Growth of single crystal seems to be stimulated by laser irradiation of the solution containing C₆₀ and bis(ethylenedithio)tetraselena-fulvalene (BEDT-TSeF), in which C₆₀ ^?? was effectively formed.