Functional polymers for biomedical application : synthesis and applications

Aromatic and aliphatic diacid chlorides were used to condense naturally occurring diamino acids and their esterified derivatives. It was anticipated the resulting functional polyamides would biodegrade to physiologically acceptable compounds and show pH dependant solubility could be used for biomedical applications ranging from enteric coatings to hydrosoluble drug delivery vehicles capable of targeting areas of low physiological pH. With these applications in mind the polymers were characterised by infra red spectroscopy, gel permeation chromatography and in the case of aqueous soluble polymers by potentiometric titration. Thin films of poly (lysine ethyl ester isophthalamide) plasticised with poly (caprolactone) were cast from DMSO/chloroform solutions and their mechanical properties measured on a Hounsfield Hti tensiometer. Interfacial synthesis was investigated as a synthetic route for the production of linear functional polyamides. High molecular weight polymer was obtained only when esterified diamino acids were condensed with aromatic diacid chlorides. The method was unsuitable for the production of copolymers of free and esterified amino acids with a diacid chloride. A novel miscible mixed solvent single phase reaction was investigated for production of copolymers of esterified and non-esterified amino acids with diacid chlorides. Aliphatic diacid chlorides were unsuitable for condensing diamino acids using this technique because of high rates of hydrolysis. The technique gave high molecular weight homopolymers from esterified diamino acids and aromatic diacid chlorides.

Watermarking biomedical time series data

This thesis addresses the problem of information hiding in low dimensional digital data focussing on issues of privacy and security in Electronic Patient Health Records (EPHRs). The thesis proposes a new security protocol based on data hiding techniques for EPHRs. This thesis contends that embedding of sensitive patient information inside the EPHR is the most appropriate solution currently available to resolve the issues of security in EPHRs. Watermarking techniques are applied to one-dimensional time series data such as the electroencephalogram (EEG) to show that they add a level of confidence (in terms of privacy and security) in an individual’s diverse bio-profile (the digital fingerprint of an individual’s medical history), ensure belief that the data being analysed does indeed belong to the correct person, and also that it is not being accessed by unauthorised personnel. Embedding information inside single channel biomedical time series data is more difficult than the standard application for images due to the reduced redundancy. A data hiding approach which has an in built capability to protect against illegal data snooping is developed. The capability of this secure method is enhanced by embedding not just a single message but multiple messages into an example one-dimensional EEG signal. Embedding multiple messages of similar characteristics, for example identities of clinicians accessing the medical record helps in creating a log of access while embedding multiple messages of dissimilar characteristics into an EPHR enhances confidence in the use of the EPHR. The novel method of embedding multiple messages of both similar and dissimilar characteristics into a single channel EEG demonstrated in this thesis shows how this embedding of data boosts the implementation and use of the EPHR securely.

Femtosecond laser micro-inscription of optical coherence tomography resolution test artifacts

Optical coherence tomography (OCT) systems are becoming more commonly used in biomedical imaging and, to enable continued uptake, a reliable method of characterizing their performance and validating their operation is required. This paper outlines the use of femtosecond laser subsurface micro-inscription techniques to fabricate an OCT test artifact for validating the resolution performance of a commercial OCT system. The key advantage of this approach is that by utilizing the nonlinear absorption a three dimensional grid of highly localized point and line defects can be written in clear fused silica substrates.

Multiterminal DC wind farm collection grid internal fault analysis and protection design

The multiterminal dc wind farm is a promising topology with a voltage-source inverter (VSI) connection at the onshore grid. Voltage-source converters (VSCs) are robust to ac-side fault conditions. However, they are vulnerable to dc faults on the dc side of the converter. This paper analyzes dc faults, their transients, and the resulting protection issues. Overcurrent faults are analyzed in detail and provide an insight into protection system design. The radial wind farm topology with star or string connection is considered. The outcomes may be applicable for VSCs in the multi-VSC dc wind farm collection grid and VSC-based high-voltage direct current (HVDC) offshore transmission systems.

Charge-balanced copolymer hydrogels:potential as biomedical materials

Polyzwitterionic-containing hydrogel materials been proposed for use in biomaterial applications. Polyzwitterions contain anions and cations in the same monomeric unit, unlike polyampholytes which contain them in different monomeric units. The use of cationic and anionic monomers in stoichiometrically equivalent proportions produces charge-balanced polyampholytes (PA) copolymers. Membranes prepared using either betaine-containing (BT) polyzwitterionic copolymers or PA copolymers can share similar properties, but the range of EWCs offered by membranes incorporating BT and PA monomers is greater than that for conventional neutral hydrogels and methacrylic acid-based systems. Here we compare properties of BT-containing and PA-containing copolymer membranes, relevant to their potential as biomedical materials. Membranes of the copolymers were prepared as previously described. Surface energy was determined using a GBX Digidrop (GBX Scientific Instruments), with diidomethane and water as probes. The absorption of proteins was determined by soaking the membranes in 1mg/ml protein solutions for a predetermined time, and measuring UV absorption of the membranes at certain wavelengths. The BT and PA copolymer membranes displayed similar values for the polar components and dispersive components of total surface free energy. This was perhaps not surprising when the structures of the monomers were considered. The BT and PA copolymer membranes displayed differences in their protein absorption over time, with the PA demonstrating higher uptake of protein than the BT. In addition to the aforementioned greater EWC range, the use of BT and PA copolymer membranes also avoids some of the problems associated with net anionicity. Comparison of the BT copolymer with the “pseudo” zwitterionic PA copolymers shows that controlled molecular architecture is required to gain the benefits of balancing the charges present in the copolymers in a way that will make them beneficial to hydrogel design.

Biomedical events extraction using the hidden vector state model

Objective: Biomedical events extraction concerns about events describing changes on the state of bio-molecules from literature. Comparing to the protein-protein interactions (PPIs) extraction task which often only involves the extraction of binary relations between two proteins, biomedical events extraction is much harder since it needs to deal with complex events consisting of embedded or hierarchical relations among proteins, events, and their textual triggers. In this paper, we propose an information extraction system based on the hidden vector state (HVS) model, called HVS-BioEvent, for biomedical events extraction, and investigate its capability in extracting complex events. Methods and material: HVS has been previously employed for extracting PPIs. In HVS-BioEvent, we propose an automated way to generate abstract annotations for HVS training and further propose novel machine learning approaches for event trigger words identification, and for biomedical events extraction from the HVS parse results. Results: Our proposed system achieves an F-score of 49.57% on the corpus used in the BioNLP'09 shared task, which is only 2.38% lower than the best performing system by UTurku in the BioNLP'09 shared task. Nevertheless, HVS-BioEvent outperforms UTurku's system on complex events extraction with 36.57% vs. 30.52% being achieved for extracting regulation events, and 40.61% vs. 38.99% for negative regulation events. Conclusions: The results suggest that the HVS model with the hierarchical hidden state structure is indeed more suitable for complex event extraction since it could naturally model embedded structural context in sentences.

From biomedical literature to knowledge:mining protein-protein interactions

To date, more than 16 million citations of published articles in biomedical domain are available in the MEDLINE database. These articles describe the new discoveries which accompany a tremendous development in biomedicine during the last decade. It is crucial for biomedical researchers to retrieve and mine some specific knowledge from the huge quantity of published articles with high efficiency. Researchers have been engaged in the development of text mining tools to find knowledge such as protein-protein interactions, which are most relevant and useful for specific analysis tasks. This chapter provides a road map to the various information extraction methods in biomedical domain, such as protein name recognition and discovery of protein-protein interactions. Disciplines involved in analyzing and processing unstructured-text are summarized. Current work in biomedical information extracting is categorized. Challenges in the field are also presented and possible solutions are discussed.