Fabricating porous poly(lactic acid) fibres via electrospinning

© 2018 Elsevier Ltd In this paper, amorphous poly(lactic acid) (PLA), a biodegradable polymer with excellent bio-compatibility, is successfully electrospun into micron-sized fibres with controlled surface and internal morphologies. By careful solvent selection, either surface porosity or internal porosity can be achieved through different mechanisms. Use of chloroform as the solvent gives rise to circular pores of 100 nm diameter confined to the surface. These are obtained in humid conditions by the so-called ‘Breath Figure’ mechanism. It is found that combining chloroform with a water-miscible non-solvent yields either surface porosity (wrinkled effect) using a low boiling point liquid, e.g. ethanol, or internal porosity using a high boiling point liquid, e.g. dimethyl sulphoxide (DMSO). Both these microstructures are obtained through a non-solvent induced phase separation (NIPS) mechanism. Finally, it is found possible to produce both surface and internal porosity using DMSO by a vapour induced phase separation (VIPS) mechanism. The porous electrospun PLA mats were shown to exhibit significantly increased oil absorption capacity compared with the non-porous fibre mats

Electrospinning of polylactic acid fibres containing tea tree and manuka oil

Here the effect of tea tree and manuka essential oils (EOs) on the mechanical properties and antibacterial activity of electrospun polylactic acid (PLA) fibres is investigated. It is found that the essential oils work as plasticisers for PLA, lowering the glass transition temperature of the resulting composite fibres up to 60% and increasing elongation-at-break and tensile strength up to 12 times. Manuka EO is particularly successful in blocking the formation of biofilms of Staphylococcus epidermidis that is typically involved in nosocomial infections associated with implanted devices. The results demonstrate that natural extracts can be used to control the mechanical behaviour of PLA fibres and to confer antibacterial activity

A Functional Varying-Coefficient Single-Index Model for Functional Response Data

<p>Motivated by the analysis of imaging data, we propose a novel functional varying-coefficient single-index model (FVCSIM) to carry out the regression analysis of functional response data on a set of covariates of interest. FVCSIM represents a new extension of varying-coefficient single-index models for scalar responses collected from cross-sectional and longitudinal studies. An efficient estimation procedure is developed to iteratively estimate varying coefficient functions, link functions, index parameter vectors, and the covariance function of individual functions. We systematically examine the asymptotic properties of all estimators including the weak convergence of the estimated varying coefficient functions, the asymptotic distribution of the estimated index parameter vectors, and the uniform convergence rate of the estimated covariance function and their spectrum. Simulation studies are carried out to assess the finite-sample performance of the proposed procedure. We apply FVCSIM to investigate the development of white matter diffusivities along the corpus callosum skeleton obtained from Alzheimer’s Disease Neuroimaging Initiative (ADNI) study. Supplementary material for this article is available online.</p

Clustering High-Dimensional Landmark-Based Two-Dimensional Shape Data

<div><p>An important goal in image analysis is to cluster and recognize objects of interest according to the shapes of their boundaries. Clustering such objects faces at least four major challenges including a curved shape space, a high-dimensional feature space, a complex spatial correlation structure, and shape variation associated with some covariates (e.g., age or gender). The aim of this article is to develop a penalized model-based clustering framework to cluster landmark-based planar shape data, while explicitly addressing these challenges. Specifically, a mixture of offset-normal shape factor analyzers (MOSFA) is proposed with mixing proportions defined through a regression model (e.g., logistic) and an offset-normal shape distribution in each component for data in the curved shape space. A latent factor analysis model is introduced to explicitly model the complex spatial correlation. A penalized likelihood approach with both adaptive pairwise fused Lasso penalty function and <i>L</i>₂ penalty function is used to automatically realize variable selection via thresholding and deliver a sparse solution. Our real data analysis has confirmed the excellent finite-sample performance of MOSFA in revealing meaningful clusters in the corpus callosum shape data obtained from the Attention Deficit Hyperactivity Disorder-200 (ADHD-200) study. Supplementary materials for this article are available online.</p></div

Role of Cl Ion Desorption in Photocurrent Enhancement of the Annealed Rutile Single-Crystalline TiO₂ Nanorod Arrays

TiO₂ nanorods arrays (NRAs) have been considered as very promising photoanode materials in photoelectrochemical (PEC) cells. However, the performance of TiO₂ NRAs still requires substantial improvement in order to reach the goal of practical applications. Annealing treatment of TiO₂ NRAs can help to improve the PEC performance, but the mechanism is still not yet fully understood. In this work, we systematically investigated the optical and electronic properties, as well as the PEC performance of the thermally treated rutile single-crystalline TiO₂ NRAs. Surprisingly, we recorded a maximum photocurrent density of 1.38 mA/cm² at 1.3 V versus reversible hydrogen electrode for TiO₂ NRAs annealed in O₂, which is about 28 times higher than that of the pristine TiO₂ NRAs. We further revealed that the surface adsorbed Cl ions largely suppress the photoresponse of the TiO₂ NRAs as they serve as recombination centers and block the adsorption of water molecules to the surface of TiO₂ NRAs. The enhancement in photocurrent after annealing in O₂ is due to the desorption of the Cl ions, filling of the surface V_o, expansion of the depletion layer, and increase of the grain size. Our results shed light on the effect of annealing on the PEC performance of TiO₂ NRAs and offer guidance for annealing of other semiconductor materials

Combined ATRP and ‘Click’ Chemistry for Designing Stable Tumor-Targeting Superparamagnetic Iron Oxide Nanoparticles

Important issues in the design of superparamagnetic iron oxide nanoparticles (SPIONs) for cancer diagnosis include stability under physiological conditions and specificity in targeting the cancer cells. In the present study, atom transfer radical polymerization (ATRP) was used to graft SPIONs with poly(glycidyl methacrylate-<i>co</i>-poly(ethylene glycol) methyl ether methacrylate) (SPIONs-P(GMA-<i>co</i>-PEGMA)). The PEGMA in the copolymer chain confers high stability to the nanoparticles in aqueous medium, and prevents recognition by macrophages with the aim of prolonging their <i>in vivo</i> circulation time. The GMA groups were used for conjugating the cancer targeting ligand, folic acid (FA), <i>via</i> ‘click’ chemistry. Using this method, the amount of FA conjugated to the nanoparticles (SPIONs-P(GMA-<i>co</i>-PEGMA)-FA) can be readily controlled. The specificity of cellular uptake of the nanoparticles by three different cell lines was investigated. The cellular iron uptake by KB cells (human epidermoid carcinoma) after 24 h of incubation is about thirteen and five times higher than those by 3T3 fibroblasts and macrophages, respectively. No significant cytotoxicity was observed with these three types of cells. The high targeting efficiency and biocompatibility of these nanoparticles are promising features for <i>in vivo</i> specific targeting and detection of tumor cells which overexpress the folate receptor

Involvement of putative PI-linked D₁-like receptors in SKF83959-induced ERK1/2 phosphorylation.

<p>(A) Effects of D₁ dopamine receptor antagonist SCH23390 (10 µM, 30 min) on SKF83959 (30 µM, 10 min)-induced ERK1/2 phosphorylation. (B) Quantification of ERK1/2 phosphorylation level in astrocytes pre-incubated with SCH23390 and treated with SKF83959 (Mean ± S.E., n = 3, *<i>P</i> < 0.05, 10 min vs. 0 min). N.S.: no significance. (C) Effects of D₂ receptor antagonist spiperone (10 µM, 30 min) on SKF83959 (30 µM, 10 min)-induced ERK1/2 phosphorylation. (D) Quantification of ERK1/2 phosphorylation level in astrocytes pre-incubated with spiperone and treated with SKF83959 (Mean ± S.E., n = 3, **<i>P</i> < 0.01 or *<i>P</i> < 0.05, 10 min vs. 0 min). (E) Effects of α-adrenoceptor antagonist prazosin (1 µM, 30 min) on SKF83959 (30 µM, 10 min)-induced ERK1/2 phosphorylation. (F) Quantification of ERK1/2 phosphorylation level in astrocytes pre-incubated with prazosin and treated with SKF83959 (Mean ± S.E., n = 3, **<i>P</i> < 0.01 or *<i>P</i> < 0.05, 10 min vs. 0 min).</p

Roles of PLC and IP3 receptor in the mediation of SKF83959-induced ERK1/2 phosphorylation.

<p>(A) Representative Western blot results indicating the effects of 2-APB (100 µM, 30 min) on SKF83959 (30 µM, 10 min)-induced ERK1/2 phosphorylation. (B) Quantitative analysis of pretreatment with 2-APB on SKF83959-induced ERK1/2 phosphorylation (Mean ± S.E., n = 3, *<i>P</i> < 0.05, 10 min vs. 0 min, *<i>P</i> < 0.05, 2-APB 0 min vs. control 0 min). (C) Representative Western blot results showing the effects of U73122 (3 µM, 30 min) on SKF83959 (30 µM, 10 min)-induced ERK1/2 phosphorylation. (D) Quantitative analysis of pretreatment with U73122 on SKF83959-induced ERK1/2 phosphorylation (Mean ± S.E., n = 3, *<i>P</i> < 0.05, 10 min vs. 0 min, **<i>P</i> < 0.01, U73122 0 min vs. control 0 min). N.S.: no significance.</p

Roles of PKCδ and PKCα in SKF83959-induced ERK1/2 phosphorylation.

<p>(A) Effects of the PKCα inhibitor Gö6976 (1 µM, 30 min) on SKF83959 (30 µM, 10 min)-induced ERK1/2 phosphorylation. (B) Quantitative analysis of pretreatment with 1 µM Gö6976 on SKF83959-induced ERK1/2 phosphorylation (Mean ± S.E., n = 3, *<i>P</i> < 0.05, 10 min vs. 0 min). (C) Effects of PKCδ inhibitor rottlerin (5 µM, 30 min) on SKF83959 (30 µM, 10 min)-induced ERK1/2 phosphorylation. (D) Quantitative analysis of pretreatment with rottlerin on SKF83959-induced ERK1/2 phosphorylation (Mean ± S.E., n = 3, *<i>P</i> < 0.05, 10 min vs. 0 min). N.S.: no significance. (E) Respective roles of rottlerin (middle, 5 µM, 30 min) and Gö6976 (right, 1 µM, 30 min) in SKF83959 (30 µM, 24 h)-induced migration of astrocytes. Bar: 5 µm. (F) Statistical analysis of respective pretreatment with rottlerin (middle) and Gö6976 (right) on SKF83959-induced migration of astrocytes (Mean ± S.E., n = 3, **<i>P</i> < 0.01, 24 h vs. 0 h). N.S.: no significance.</p

The spike threshold depends on the history of the membrane potential in both real and simulated data.

<p><b>(A)</b> We performed patch-clamp recordings in layer 2/3 pyramidal neurons in vitro, in response to population input from stimulation in layer 4 (left). The pyramidal neuron identity was confirmed in a subset by filling the targeted neuron using biotin (middle). <b>(B)</b> From recorded action potentials (top), the spike threshold is determined as the maximal positive peak of the second derivative of the membrane potential (bottom). <b>(C1)</b> A cortical neuron stimulated with current inputs of different slopes (bottom, different shades of gray) lead to action potentials (top, corresponding grays) with different thresholds for spike initiation (top, red lines in corresponding brightness to grays of voltage traces, inset shows zoom in of spike initiation). The response is delayed w.r.t. to the stimulation due to the propagation delay from L4 to L2/3. The inset shows a magnified view of the threshold region. (<b>C2</b>) As in previous studies, thresholds were found to vary with the slope of the preceding membrane voltage. In the current stimulation settings, only a limited range of input slopes was realized. <b>(D1)</b> Neurons with an adaptive threshold were simulated on the basis of the model by Fontaine et al. [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004984#pcbi.1004984.ref002" target="_blank">2</a>], after adapting the parameterization to cortical excitatory neurons (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004984#sec018" target="_blank">Methods</a>). In addition to the voltage traces (grays), the adapting thresholds are also shown (reds, brightness corresponding to the gray traces). (<b>D2</b>) Applying the same analysis as in the in vitro data to measure the threshold, indicates that designed and measured threshold agree. The relationship between EPSP slope and spike threshold is overall captured by an exponential function especially when the wider range of EPSP slopes was used, which could be explored in the model (compare C2 and D2), see also [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004984#pcbi.1004984.ref005" target="_blank">5</a>]. <b>(E1)</b> Neurons with a fixed threshold were also simulated. The threshold was set to equalize firing probability with the adaptive threshold model. (<b>E2</b>) Re-estimating the threshold, we obtain the expected constant threshold.</p