Automatic indexing and retrieval of encounter-specific evidence for point-of-care support

Evidence-based medicine relies on repositories of empirical research evidence that can be used to support clinical decision making for improved patient care. However, retrieving evidence from such repositories at local sites presents many challenges. This paper describes a methodological framework for automatically indexing and retrieving empirical research evidence in the form of the systematic reviews and associated studies from The Cochrane Library, where retrieved documents are specific to a patient-physician encounter and thus can be used to support evidence-based decision making at the point of care. Such an encounter is defined by three pertinent groups of concepts - diagnosis, treatment, and patient, and the framework relies on these three groups to steer indexing and retrieval of reviews and associated studies. An evaluation of the indexing and retrieval components of the proposed framework was performed using documents relevant for the pediatric asthma domain. Precision and recall values for automatic indexing of systematic reviews and associated studies were 0.93 and 0.87, and 0.81 and 0.56, respectively. Moreover, precision and recall for the retrieval of relevant systematic reviews and associated studies were 0.89 and 0.81, and 0.92 and 0.89, respectively. With minor modifications, the proposed methodological framework can be customized for other evidence repositories. © 2010 Elsevier Inc.

Extracting interactions between proteins from the literature

During the last decade, biomedicine has witnessed a tremendous development. Large amounts of experimental and computational biomedical data have been generated along with new discoveries, which are accompanied by an exponential increase in the number of biomedical publications describing these discoveries. In the meantime, there has been a great interest with scientific communities in text mining tools to find knowledge such as protein-protein interactions, which is most relevant and useful for specific analysis tasks. This paper provides a outline of the various information extraction methods in biomedical domain, especially for discovery of protein-protein interactions. It surveys methodologies involved in plain texts analyzing and processing, categorizes current work in biomedical information extraction, and provides examples of these methods. Challenges in the field are also presented and possible solutions are discussed.

Computer-aided biotechnology:from immuno-informatics to reverse vaccinology

Genome sequences from many organisms, including humans, have been completed, and high-throughput analyses have produced burgeoning volumes of 'omics' data. Bioinformatics is crucial for the management and analysis of such data and is increasingly used to accelerate progress in a wide variety of large-scale and object-specific functional analyses. Refined algorithms enable biotechnologists to follow 'computer-aided strategies' based on experiments driven by high-confidence predictions. In order to address compound problems, current efforts in immuno-informatics and reverse vaccinology are aimed at developing and tuning integrative approaches and user-friendly, automated bioinformatics environments. This will herald a move to 'computer-aided biotechnology': smart projects in which time-consuming and expensive large-scale experimental approaches are progressively replaced by prediction-driven investigations.

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.

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.

Nanopatterned UV curable hydrogels for biomedical applications

With an increasing use of emerging patterning technologies such as UV-NIL in biotechnological applications there is at the same time a raising demand for new material for such applications. Here we present a PEG based precursor mixed with a photoinitiator to make it UV sensitive as a new material aimed at biotechnological applications. Using HSQ patterned quartz stamps we observed excellent pattern replication indicating good flow properties of the resist. We were able to obtain imprints with <20 nm residual layer. The PEG based resist has hydrogel properties and it swelling in water was observed by AFM.

Complexity and chirality indices for molecular informatics::differential geometry approach

Novel molecular complexity measures are designed based on the quantum molecular kinematics. The Hamiltonian matrix constructed in a quasi-topological approximation describes the temporal evolution of the modelled electronic system and determined the time derivatives for the dynamic quantities. This allows to define the average quantum kinematic characteristics closely related to the curvatures of the electron paths, particularly, the torsion reflecting the chirality of the dynamic system. A special attention has been given to the computational scheme for this chirality measure. The calculations on realistic molecular systems demonstrate reasonable behaviour of the proposed molecular complexity indices.

Interferometric microstructured polymer optical fiber ultrasound sensor for optoacoustic endoscopic imaging in biomedical applications

We report a characterization of the acoustic sensitivity of microstructured polymer optical fiber interferometric sensors at ultrasonic frequencies from 100kHz to 10MHz. The use of wide-band ultrasonic fiber optic sensors in biomedical ultrasonic and optoacoustic applications is an open alternative to conventional piezoelectric transducers. These kind of sensors, made of biocompatible polymers, are good candidates for the sensing element in an optoacoustic endoscope because of its high sensitivity, its shape and its non-brittle and non-electric nature. The acoustic sensitivity of the intrinsic fiber optic interferometric sensors depends strongly of the material which is composed of. In this work we compare experimentally the intrinsic ultrasonic sensitivities of a PMMA mPOF with other three optical fibers: a singlemode silica optical fiber, a single-mode polymer optical fiber and a multimode graded-index perfluorinated polymer optical fiber. © 2014 SPIE.