Fluorescence correlation spectroscopy (FCS) has been widely used to investigate molecular diffusion behavior in various samples. The use of the maximum entropy method (MEM) for FCS data analysis provides a unique means to determine multiple distinct diffusion coefficients without a priori assumption of their number. Comparison of the MEM-based FCS method (MEM-FCS) with another method will reveal its utility and advantage as an analytical tool to investigate diffusion dynamics. Herein, we measured diffusion of fluorescent probes doped into nanostructured thin films using MEM-FCS, and validated the results with single molecule tracking (SMT) data. The efficacy of the MEM code employed was first demonstrated by analyzing simulated FCS data for systems incorporating one and two diffusion modes with broadly distributed diffusion coefficients. The MEM analysis accurately afforded the number of distinct diffusion modes and their mean diffusion coefficients. These results contrasted with those obtained by fitting the simulated data to conventional two-component and anomalous diffusion models, which yielded inaccurate estimates of the diffusion coefficients. Subsequently, the MEM analysis was applied to FCS data acquired from hydrophilic dye molecules incorporated into microphase-separated polystyrene-block-poly(ethylene oxide) (PS-b-PEO) thin films characterized under a water-saturated N2 atmosphere. The MEM analysis revealed distinct fast and slow diffusion components attributable to molecules diffusing on the film surface and inside the film, respectively. SMT studies of the same materials yielded trajectories for mobile molecules that appear to follow the curved PEO microdomains. Diffusion coefficients obtained from the SMT data were consistent with those obtained for the slow diffusion component detected by MEM-FCS. These results highlight the utility of MEM-FCS and SMT for gaining complementary information on molecular diffusion processes in heterogeneous material systems.
The main challenge in working with gene expression microarrays is that the sample size is small compared to the large number of variables (genes). In many studies, the main focus is on finding a small subset of the genes, which are the most important ones for differentiating between different types of cancer, for simpler and cheaper diagnostic arrays. In this paper, a sparse Bayesian variable selection method in probit model is proposed for gene selection and classification. We assign a sparse prior for regression parameters and perform variable selection by indexing the covariates of the model with a binary vector. The correlation prior for the binary vector assigned in this paper is able to distinguish models with the same size. The performance of the proposed method is demonstrated with one simulated data and two well known real data sets, and the results show that our method is comparable with other existing methods in variable selection and classification. 相似文献
Two hydrophilic conjugated polymers, PmP‐NOH and PmP36F‐NOH, with polar diethanolamine on the side chains and main chain structures of poly(meta‐phenylene) and poly(meta‐phenylene‐alt‐3,6‐fluorene), respectively, are successfully synthesized. The films of PmP‐NOH and PmP36F‐NOH show absorption edges at 340 and 343 nm, respectively. The calculated optical bandgaps of the two polymers are 3.65 and 3.62 eV, respectively, the largest ones so far reported for hydrophilic conjugated polymers. PmP‐NOH and PmP36F‐NOH also possess deep‐lying highest occupied molecular orbital levels of −6.19 and −6.15 eV, respectively. Inserting PmP‐NOH and PmP36F‐NOH as a cathode interlayer in inverted polymer solar cells with a PTB7/PC71BM blend as the active layer, high power conversion efficiencies of 8.58% and 8.33%, respectively, are achieved, demonstrating that the two hydrophilic polymers are excellent interlayers for efficient inverted polymer solar cells.
Information-rich molecules provide opportunities for evolution.Genetically engineered materials are superior in that their properties are coded within genetic sequences and could be fine-tuned.In this review,we elaborate the concept of genetically engineered materials(GEMs)using examples ranging from engineered protein materials to engineered living materials.Proteinbased materials are the materials of choice by nature.Recent progress in protein engineering has led to opportunities to tune their sequences for optimal material performance.Proteins also play a central role in living materials where they act in concert with other biological components as well as nonbiological cofactors,giving rise to living features.While the existing GEMs are often limited to those constructed by building blocks of biological origin,being genetically engineerable does not preclude nonbiologic or synthetic materials,the latter of which have yet to be fully explored. 相似文献
Mesoporous slabstone‐like anatase TiO2 micro‐nanometer composite structure has been successfully synthesized by a facile solvothermal method at 180 °C using polyethylene glycol (PEG) as a structure‐directing agent, followed by calcination at 400 °C for 2 h. The crystal structure and morphology of the product were characterized by XRD, SEM, TEM and HRTEM. Its BET specific surface area was obtained from N2 adsorption‐desorption isotherm measurement. Rhodamine B (RB) aqueous solution was used to evaluate the photocatalytic activity of the as‐prepared TiO2 under simulated sunlight irradiation and compared with that of commercial TiO2 (P25). A RB and methyl orange (MO) coexisting solution was chosen to investigate the photodegradation preference of the slabstone‐like TiO2 on these two dyes. The results show that the photocatalytic activity of the as‐prepared TiO2 is much higher than that of P25, and MO is the preferential degradation species in the MO‐RB mixture solution. 相似文献
Controlling protein topology has been a long standing challenge to go beyond their linear configuration defined by the translation mechanism of cellular machinery. In this mini-review, we focus on the topological diversity in proteins and review the major categories of protein topologies known to date, including branched/star proteins, circular proteins, lasso proteins, knotted proteins, and protein catenanes. The discovery of these topologically complex natural proteins and their synthetic pathways, the rational design and recombinant synthesis of artificial topological proteins and their biophysical studies, are summarized and discussed with regard to their general features and broad implications. The complexity of protein topology is recognized and the routes to diverse protein topologies are illustrated. We believe that topology engineering is an important way to modify protein properties without alternating their native sequences and shall bring in valuable dynamic features central to the creation of artificial protein machinery. 相似文献