Surface modification of low-density polyethylene with poly(2-ethyl-2- oxazoline) using a low-pressure plasma treatment

Low-density polyethylene (LDPE) is a suitable polymer for biomedical applications due to its good physiochemical properties, but its insufficient biocompatibility is often an issue. Therefore, biocompatible substances such as those based on 2-ethyl-2-oxazoline seem to be a good choice to increase the LDPE biocompatibility. In this work, the surface modification of LDPE with poly(2-ethyl-2-oxazoline) with two different end-groups was investigated. This modification led to the improvement of surface and adhesion properties, which were investigated by several analytical methods. The low-temperature plasma treatment of the LDPE surface was sufficient to create binding sites for the permanent attachment of poly(2ethyl-2-oxazoline) chains. This was confirmed by infrared spectroscopy and X-Ray photoelectron spectroscopy. It was found that the polymer containing the acrylic end-group was well attached to the LDPE surface. 2013 Elsevier Ltd. All rights reserved.This work was supported by the Slovak Grant Agency VEGA for projects Nr. 2/0064/10 , Nr. 2/0151/12 , and Nr. 2/0185/10 ). The Center for Materials, Layers and Systems for Applications and Chemical Processes under Extreme Conditions was supported by the Research & Development Operational Program funded by the ERDF. Electron microscopy at IMC was performed with financial support through grant TACR TE01020118 .Scopu

Surface Behavior of Polyamide 6 Modified by Barrier Plasma in Oxygen and Nitrogen

Polyamide (PA) 6 was modified by diffuse coplanar surface barrier discharge (DCSBD) plasma in an atmosphere of nitrogen and oxygen. The surface roughness decrease of PA 6 was detected by AFM and nano-indentation after modification in DCSBD plasma. A significant increase in O/C and N/C ratios of plasma-modified PA 6 using XPS analysis was found. The results show the importance of introducing oxygenic polar functional groups on the polymeric surface in order to increase its surface energy during a short time of plasma activation. The modification of PA 6 by DCSBD oxygen plasma was more efficient than by nitrogen plasma.Ministry of Education of the Slovak Republic and Slovak Academy of Sciences, projects VEGA (grants no. 2/0185/10, 2/0199/14, and 1/0581/12) as well to the Ministry of Education, Youth and Sport of the Czech Republic (CZ.1.05/2.1.00/03.0111)Scopu

Phase change materials based on high-density polyethylene filled with microencapsulated paraffin wax

A modified in situ polymerization microencapsulation procedure for the preparation of microcapsules with paraffin wax cores (43 wt.%) and melamine–formaldehyde resin shells having a uniform size distribution and a spherical shape with average diameters of approximately 15 μm was developed. The high-density polyethylene/microcapsule blends were prepared via two routes. In the first case, the dry high-density polyethylene powder covered by microcapsules was simply hot pressed, whereas, in the second case, the dry high density polyethylene/capsule powder was first blended in the molten state to obtain better homogeneity before hot pressing. It was observed that both systems behave qualitatively the same with comparable mechanical properties and thermal behavior. The thermal stability of high-density polyethylene/microcapsule blends characterized by thermogravimetry is significantly lower than that of neat high-density polyethylene. The selected characteristic temperatures of degradation decreased by more than 200 °C compared with the related temperatures for neat high-density polyethylene. An analysis based on Differential Scanning Calorimetry revealed separated melting and crystallization behavior of wax within the capsules and high density polyethylene in the blends. The enthalpies of melting and crystallization are proportional to the amount of individual components in the material. The capsules have a strong plasticizing effect on the high density polyethylene, resulting in a significant decrease in the melting and crystallization temperatures. The plasticizing effect was also confirmed by measurements of the tensile mechanical properties and rheological behavior.This work was made possible by NPRP Grant No. 4-465-2-173 from the Qatar National Research Fund (A Member of The Qatar Foundation). Scientific Grant Agency of the Ministry of Education of Slovak Republic and the Slovak Academy of Sciences (Project No. 2/0119/12).Scopu

Not all roads lead to the immune system: the genetic basis of multiple sclerosis severity

Multiple sclerosis is a leading cause of neurological disability in adults. Heterogeneity in multiple sclerosis clinical presentation has posed a major challenge for identifying genetic variants associated with disease outcomes. To overcome this challenge, we used prospectively ascertained clinical outcomes data from the largest international multiple sclerosis registry, MSBase. We assembled a cohort of deeply phenotyped individuals of European ancestry with relapse-onset multiple sclerosis. We used unbiased genome-wide association study and machine learning approaches to assess the genetic contribution to longitudinally defined multiple sclerosis severity phenotypes in 1813 individuals. Our primary analyses did not identify any genetic variants of moderate to large effect sizes that met genome-wide significance thresholds. The strongest signal was associated with rs7289446 (β = -0.4882, P = 2.73 × 10-7), intronic to SEZ6L on chromosome 22. However, we demonstrate that clinical outcomes in relapse-onset multiple sclerosis are associated with multiple genetic loci of small effect sizes. Using a machine learning approach incorporating over 62 000 variants together with clinical and demographic variables available at multiple sclerosis disease onset, we could predict severity with an area under the receiver operator curve of 0.84 (95% CI 0.79-0.88). Our machine learning algorithm achieved positive predictive value for outcome assignation of 80% and negative predictive value of 88%. This outperformed our machine learning algorithm that contained clinical and demographic variables alone (area under the receiver operator curve 0.54, 95% CI 0.48-0.60). Secondary, sex-stratified analyses identified two genetic loci that met genome-wide significance thresholds. One in females (rs10967273; βfemale = 0.8289, P = 3.52 × 10-8), the other in males (rs698805; βmale = -1.5395, P = 4.35 × 10-8), providing some evidence for sex dimorphism in multiple sclerosis severity. Tissue enrichment and pathway analyses identified an overrepresentation of genes expressed in CNS compartments generally, and specifically in the cerebellum (P = 0.023). These involved mitochondrial function, synaptic plasticity, oligodendroglial biology, cellular senescence, calcium and G-protein receptor signalling pathways. We further identified six variants with strong evidence for regulating clinical outcomes, the strongest signal again intronic to SEZ6L (adjusted hazard ratio 0.72, P = 4.85 × 10-4). Here we report a milestone in our progress towards understanding the clinical heterogeneity of multiple sclerosis outcomes, implicating functionally distinct mechanisms to multiple sclerosis risk. Importantly, we demonstrate that machine learning using common single nucleotide variant clusters, together with clinical variables readily available at diagnosis can improve prognostic capabilities at diagnosis, and with further validation has the potential to translate to meaningful clinical practice change