Effects of hydroxyapatite and PDGF concentrations on osteoblast growth in a nanohydroxyapatite-polylactic acid composite for guided tissue regeneration

The technique of guided tissue regeneration (GTR) has evolved over recent years in an attempt to achieve periodontal tissue regeneration by the use of a barrier membrane. However, there are significant limitations in the currently available membranes and overall outcomes may be limited. A degradable composite material was investigated as a potential GTR membrane material. Polylactic acid (PLA) and nanohydroxyapatite (nHA) composite was analysed, its bioactive potential and suitability as a carrier system for growth factors were assessed. The effect of nHA concentrations and the addition of platelet derived growth factor (PDGF) on osteoblast proliferation and differentiation was investigated. The bioactivity was dependent on the nHA concentration in the films, with more apatite deposited on films containing higher nHA content. Osteoblasts proliferated well on samples containing low nHA content and differentiated on films with higher nHA content. The composite films were able to deliver PDGF and cell proliferation increased on samples that were pre absorbed with the growth factor. nHA–PLA composite films are able to deliver active PDGF. In addition the bioactivity and cell differentiation was higher on films containing more nHA. The use of a nHA–PLA composite material containing a high concentration of nHA may be a useful material for GTR membrane as it will not only act as a barrier, but may also be able to enhance bone regeneration by delivery of biologically active molecules

Nanotopographical induction of osteogenesis through adhesion, bone morphogenic protein cosignaling, and regulation of microRNAs

It is emerging that nanotopographical information can be used to induce osteogenesis from mesenchymal stromal cells from the bone marrow and it is hoped that this nanoscale bioactivity can be utilized to engineer next generation implants. However, the osteogenic mechanism of surfaces is currently poorly understood. In this report, we investigate mechanism and implicate bone morphogenic protein (BMP) in up-regulation of RUNX2 and show that RUNX2 and its regulatory miRNAs are BMP sensitive. Our data demonstrates that osteogenic nanotopography promotes co-localization of intergrins and BMP2 receptors in order to enhance osteogenic activity and that vitronectin is important in this interface. This provides insight that topographical regulation of adhesion can have effects on signaling cascades outside of cytoskeletal signaling and that adhesions can have roles in augmenting BMP signaling

Applications of Direct Injection Soft Chemical Ionisation-Mass Spectrometry for the Detection of Pre-blast Smokeless Powder Organic Additives

Analysis of smokeless powders is of interest from forensics and security perspectives. This article reports the detection of smokeless powder organic additives (in their pre-detonation condition), namely the stabiliser diphenylamine and its derivatives 2-nitrodiphenylamine and 4-nitrodiphenylamine, and the additives (used both as stabilisers and plasticisers) methyl centralite and ethyl centralite, by means of swab sampling followed by thermal desorption and direct injection soft chemical ionisation-mass spectrometry. Investigations on the product ions resulting from the reactions of the reagent ions H3O+ and O2+ with additives as a function of reduced electric field are reported. The method was comprehensively evaluated in terms of linearity, sensitivity and precision. For H3O+, the limits of detection (LoD) are in the range of 41-88 pg of additive, for which the accuracy varied between 1.5 and 3.2%, precision varied between 3.7 and 7.3% and linearity showed R20.9991. For O2+, LoD are in the range of 72 to 1.4 ng, with an accuracy of between 2.8 and 4.9% and a precision between 4.5 and 8.6% and R20.9914. The validated methodology was applied to the analysis of commercial pre-blast gun powders from different manufacturers.(VLID)4826148Accepted versio

High platelet reactivity in patients with acute coronary syndromes undergoing percutaneous coronary intervention: Randomised controlled trial comparing prasugrel and clopidogrel

Background: Prasugrel is more effective than clopidogrel in reducing platelet aggregation in acute coronary syndromes. Data available on prasugrel reloading in clopidogrel treated patients with high residual platelet reactivity (HRPR) i.e. poor responders, is limited. Objectives: To determine the effects of prasugrel loading on platelet function in patients on clopidogrel and high platelet reactivity undergoing percutaneous coronary intervention for acute coronary syndrome (ACS). Patients: Patients with ACS on clopidogrel who were scheduled for PCI found to have a platelet reactivity ≥40 AUC with the Multiplate Analyzer, i.e. “poor responders” were randomised to prasugrel (60 mg loading and 10 mg maintenance dose) or clopidogrel (600 mg reloading and 150 mg maintenance dose). The primary outcome measure was proportion of patients with platelet reactivity <40 AUC 4 hours after loading with study medication, and also at one hour (secondary outcome). 44 patients were enrolled and the study was terminated early as clopidogrel use decreased sharply due to introduction of newer P2Y12 inhibitors. Results: At 4 hours after study medication 100% of patients treated with prasugrel compared to 91% of those treated with clopidogrel had platelet reactivity <40 AUC (p = 0.49), while at 1 hour the proportions were 95% and 64% respectively (p = 0.02). Mean platelet reactivity at 4 and 1 hours after study medication in prasugrel and clopidogrel groups respectively were 12 versus 22 (p = 0.005) and 19 versus 34 (p = 0.01) respectively. Conclusions: Routine platelet function testing identifies patients with high residual platelet reactivity (“poor responders”) on clopidogrel. A strategy of prasugrel rather than clopidogrel reloading results in earlier and more sustained suppression of platelet reactivity. Future trials need to identify if this translates into clinical benefit

FIB patterning of stainless steel for the development of nano-structured stent surfaces for cardiovascular applications

Stent implantation is a percutaneous interventional procedure that mitigates vessel stenosis, providing mechanical support within the artery and as such a very valuable tool in the fight against coronary artery disease. However, stenting causes physical damage to the arterial wall. It is well accepted that a valuable route to reduce in-stent re-stenosis can be based on promoting cell response to nano-structured stainless steel (SS) surfaces such as by patterning nano-pits in SS. In this regard patterning by focused ion beam (FIB) milling offers several advantages for flexible prototyping. On the other hand FIB patterning of polycrystalline metals is greatly influenced by channelling effects and redeposition. Correlative microscopy methods present an opportunity to study such effects comprehensively and derive structure–property understanding that is important for developing improved patterning. In this chapter we present a FIB patterning protocol for nano-structuring features (concaves) ordered in rectangular arrays on pre-polished 316L stainless steel surfaces. An investigation based on correlative microscopy approach of the size, shape and depth of the developed arrays in relation to the crystal orientation of the underlying SS domains is presented. The correlative microscopy protocol is based on cross-correlation of top-view scanning electron microscopy, electron backscattering diffraction, atomic force microscopy and cross-sectional (serial) sectioning. Various FIB tests were performed, aiming at improved productivity by preserving nano-size accuracy of the patterned process. The optimal FIB patterning conditions for achieving reasonably high throughput (patterned rate of about 0.03 mm2/h) and nano-size accuracy in dimensions and shapes of the features are discussed as well

Thin Polymer Brush Decouples Biomaterial's Micro-/Nano-Topology and Stem Cell Adhesion

Surface morphology and chemistry of polymers used as biomaterials, such as tissue engineering scaffolds, have a strong influence on the adhesion and behavior of human mesenchymal stem cells. Here we studied semicrystalline poly(ε-caprolactone) (PCL) substrate scaffolds, which exhibited a variation of surface morphologies and roughness originating from different spherulitic superstructures. Different substrates were obtained by varying the parameters of the thermal processing, i.e. crystallization conditions. The cells attached to these polymer substrates adopted different morphologies responding to variations in spherulite density and size. In order to decouple substrate topology effects on the cells, sub-100 nm bio-adhesive polymer brush coatings of oligo(ethylene glycol) methacrylates were grafted from PCL and functionalized with fibronectin. On surfaces featuring different surface textures, dense and sub-100 nm thick brush coatings determined the response of cells, irrespective to the underlying topology. Thus, polymer brushes decouple substrate micro-/nano-topology and the adhesion of stem cells

Foreign policy and political possibility

This article explores the relationship between foreign policy and political possibility in two parts. First, the relationship between foreign policy and political possibility is theorized around three analytical moments: political possibility is linked to the framing of conceivable, communicable and coercive foreign policy. Second, this framework is developed and demonstrated through a brief analysis of Coalition foreign policy in the War on Terror, considering American, British and Australian foreign policy between 2001 and 2003. This analysis dissects distinct and divergent Coalition foreign policies through a linked three-part conceptualization of political possibility. It enables an understanding of how the War on Terror was rendered possible through the construction of foreign policy in thinkable, resonant and ultimately dominant terms. The article concludes by looking to the wider analytical applicability of this particular theorization of the relationship between foreign policy and political possibility

Classifying and scoring of molecules with the NGN: new datasets, significance tests, and generalization

<p>Abstract</p> <p/> <p>This paper demonstrates how a Neural Grammar Network learns to classify and score molecules for a variety of tasks in chemistry and toxicology. In addition to a more detailed analysis on datasets previously studied, we introduce three new datasets (BBB, FXa, and toxicology) to show the generality of the approach. A new experimental methodology is developed and applied to both the new datasets as well as previously studied datasets. This methodology is rigorous and statistically grounded, and ultimately culminates in a Wilcoxon significance test that proves the effectiveness of the system. We further include a complete generalization of the specific technique to arbitrary grammars and datasets using a mathematical abstraction that allows researchers in different domains to apply the method to their own work.</p> <p>Background</p> <p>Our work can be viewed as an alternative to existing methods to solve the quantitative structure-activity relationship (QSAR) problem. To this end, we review a number approaches both from a methodological and also a performance perspective. In addition to these approaches, we also examined a number of chemical properties that can be used by generic classifier systems, such as feed-forward artificial neural networks. In studying these approaches, we identified a set of interesting benchmark problem sets to which many of the above approaches had been applied. These included: ACE, AChE, AR, BBB, BZR, Cox2, DHFR, ER, FXa, GPB, Therm, and Thr. Finally, we developed our own benchmark set by collecting data on toxicology.</p> <p>Results</p> <p>Our results show that our system performs better than, or comparatively to, the existing methods over a broad range of problem types. Our method does not require the expert knowledge that is necessary to apply the other methods to novel problems.</p> <p>Conclusions</p> <p>We conclude that our success is due to the ability of our system to: 1) encode molecules losslessly before presentation to the learning system, and 2) leverage the design of molecular description languages to facilitate the identification of relevant structural attributes of the molecules over different problem domains.</p