Electrospun pH-sensitive core–shell polymer nanocomposites fabricated using a tri-axial process

A modified tri-axial electrospinning process was developed for the generation of a new type of pH-sensitive polymer/lipid nanocomposite. The systems produced are able to promote both dissolution and permeation of a model poorly water-soluble drug. First, we show that it is possible to run a tri-axial process with only one of the three fluids being electrospinnable. Using an electrospinnable middle fluid of Eudragit S100 (ES100) with pure ethanol as the outer solvent and an unspinnable lecithin-diclofenac sodium (PL–DS) core solution, nanofibers with linear morphology and clear core/shell structures can be fabricated continuously and smoothly. X-ray diffraction proved that these nanofibers are structural nanocomposites with the drug present in an amorphous state. In vitro dissolution tests demonstrated that the formulations could preclude release in acidic conditions, and that the drug was released from the fibers in two successive steps at neutral pH. The first step is the dissolution of the shell ES100 and the conversion of the core PL–DS into sub-micron sized particles. This frees some DS into solution, and later the remaining DS is gradually released from the PL–DS particles through diffusion. Ex vivo permeation results showed that the composite nanofibers give a more than twofold uplift in the amount of DS passing through the colonic membrane as compared to pure DS; 74% of the transmitted drug was in the form of PL–DS particles. The new tri-axial electrospinning process developed in this work provides a platform to fabricate structural nanomaterials, and the core–shell polymer-PL nanocomposites we have produced have significant potential applications for oral colon-targeted drug delivery.

Mem Tri: Memory Forensics Triage Tool

This work explores the development of MemTri. A memory forensics triage tool that can assess the likelihood of criminal activity in a memory image, based on evidence data artefacts generated by several applications. Fictitious illegal suspect activity scenarios were performed on virtual machines to generate 60 test memory images for input into MemTri. Four categories of applications (i.e. Internet Browsers, Instant Messengers, FTP Client and Document Processors) are examined for data artefacts located through the use of regular expressions. These identified data artefacts are then analysed using a Bayesian Network, to assess the likelihood that a seized memory image contained evidence of illegal activity. Currently, MemTri is under development and this paper introduces only the basic concept as well as the components that the application is built on. A complete description of MemTri coupled with extensive experimental results is expected to be published in the first semester of 2017.