Fractional order and non-linear system identification algorithms for biomedical applications

We discuss the modelling of dielectric responses of amorphous biological samples. Such samples are commonly encountered in impedance spectroscopy studies as well as in UV, IR, optical and THz transient spectroscopy experiments and in pump-probe studies. In many occasions, the samples may display quenched absorption bands. A systems identification framework may be developed to provide parsimonious representations of such responses. To achieve this, it is appropriate to augment the standard models found in the identification literature to incorporate fractional order dynamics. Extensions of models using the forward shift operator, state space models as well as their non-linear Hammerstein-Wiener counterpart models are highlighted. We also discuss the need to extend the theory of electromagnetically excited networks which can account for fractional order behaviour in the non-linear regime by incorporating nonlinear elements to account for the observed non-linearities. The proposed approach leads to the development of a range of new chemometrics tools for biomedical data analysis and classification.

Biomedical applications of hydrogels: a review of patents and commercial products

Hydrogels have become very popular due to their unique properties such as high water content, softness, flexibility and biocompatibility. Natural and synthetic hydrophilic polymers can be physically or chemically cross-linked in order to produce hydrogels. Their resemblance to living tissue opens up many opportunities for applications in biomedical areas. Currently, hydrogels are used for manufacturing contact lenses, hygiene products, tissue engineering scaffolds, drug delivery systems and wound dressings. This review provides an analysis of their main characteristics and biomedical applications. From Wichterle’s pioneering work to the most recent hydrogel-based inventions and products on the market, it provides the reader with a detailed introduction to the topic and perspective on further potential developments.

Designing Temperature-Responsive Biocompatible Copolymers and Hydrogels Based on 2-Hydroxyethyl(meth)acrylates

Free-radical copolymerization of 2-hydroxyethyl methacrylate with 2-hydroxyethyl acrylate can be successively utilized for the synthesis of water-soluble polymers and hydrogels with excellent physicochemical properties, thus showing promise for pharmaceutical and biomedical applications. In the work presented it has been demonstrated that water-soluble copolymers based on 2-hydroxyethyl methacrylate and 2-hydroxyethyl acrylate exhibit lower critical solution temperature in aqueous solutions, whereas the corresponding high molecular weight homopolymers do not have this unique property. The temperature-induced transitions observed upon heating the aqueous solutions of these copolymers proceed via liquid−liquid phase separation. The hydrogels were also synthesized by copolymerizing 2-hydroxyethyl methacrylate and 2-hydroxyethyl acrylate in the absence of a bifunctional cross-linker. The cross-linking of these copolymers during copolymerization is believed to be due to the presence of bifunctional admixtures or transesterification reactions. Transparency, swelling behavior, mechanical properties, and porosity of the hydrogels are dependent upon the monomer ratio in the copolymers. Hydrogel samples containing more 2-hydroxyethyl methacrylate are less transparent, have lower swelling capacity, higher elastic moduli, and pores of smaller size. The assessment of the biocompatibility of the copolymers using the slug mucosal irritation test revealed that they are also less irritant than poly(acrylic acid).

Spectroscopic imaging of arteries and atherosclerotic plaques

Fourier transform infrared (FTIR) spectroscopic imaging using a focal plane array detector has been used to study atherosclerotic arteries with a spatial resolution of 3-4 mum, i.e., at a level that is comparable with cellular dimensions. Such high spatial resolution is made possible using a micro-attenuated total reflection (ATR) germanium objective with a high refractive index and therefore high numerical aperture. This micro-ATR approach has enabled small structures within the vessel wall to be imaged for the first time by FTIR. Structures observed include the elastic lamellae of the tunica media and a heterogeneous distribution of small clusters of cholesterol esters within an atherosclerotic lesion, which may correspond to foam cells. A macro-ATR imaging method was also applied, which involves the use of a diamond macro-ATR accessory. This study of atherosclerosis is presented as an illustrative example of the wider potential of these A TR imaging approaches for cardiovascular medicine and biomedical applications. (C) 2004 Wiley Periodicals, Inc.

Self-nucleation and crystallization kinetics of double crystalline poly(p-dioxanone)-b-poly(epsilon-caprolactone) diblock copolymers

The crystallization kinetics of each constituent of poly(p-dioxanone)-b-poly(epsilon-caprolactone) diblock copolymers (PPDX-b-PCL) has been determined in a wide composition range by differential scanning calorimetry and compared to that of the equivalent homopolymers. Spherulitic growth rates were also measured by polarized optical microscopy while atomic force microscopy was employed to reveal the morphology of one selected diblock copolymer. It was found that crystallization drives structure formation and both components form lamellae within mixed spherulitic superstructures. The overall isothermal crystallization kinetics of the PPDX block at high temperatures, where the PCL is molten, was determined by accelerating the kinetics through a previous self-nucleation procedure. The application of the Lauritzen and Ho. man theory to overall growth rate data yielded successful results for PPDX and the diblock copolymers. The theory was applied to isothermal overall crystallization of previously self-nucleated PPDX ( where growth should be the dominant factor if self-nucleation was effective) and the energetic parameters obtained were perfectly matched with those obtained from spherulitic growth rate data of neat PPDX. A quantitative estimate of the increase in the energy barrier for crystallization of the PPDX block, caused by the covalently bonded molten PCL as compared to homo-PPDX, was thus determined. This energy increase can dramatically reduce the crystallization rate of the PPDX block as compared to homo-PPDX. In the case of the PCL block, both the crystallization kinetics and the self-nucleation results indicate that the PPDX is able to nucleate the PCL within the copolymers and heterogeneous nucleation is always present regardless of composition. Finally, preliminary results on hydrolytic degradation showed that the presence of relatively small amounts of PCL within PPDX-bPCL copolymers substantially retards hydrolytic degradation of the material in comparison to homo-PPDX. This increased resistance to hydrolysis is a complex function of composition and its knowledge may allow future prediction of the lifetime of the material for biomedical applications.

Dynamical complexity in a mean-field model of human EEG

A recently proposed mean-field theory of mammalian cortex rhythmogenesis describes the salient features of electrical activity in the cerebral macrocolumn, with the use of inhibitory and excitatory neuronal populations (Liley et al 2002). This model is capable of producing a range of important human EEG (electroencephalogram) features such as the alpha rhythm, the 40 Hz activity thought to be associated with conscious awareness (Bojak & Liley 2007) and the changes in EEG spectral power associated with general anesthetic effect (Bojak & Liley 2005). From the point of view of nonlinear dynamics, the model entails a vast parameter space within which multistability, pseudoperiodic regimes, various routes to chaos, fat fractals and rich bifurcation scenarios occur for physiologically relevant parameter values (van Veen & Liley 2006). The origin and the character of this complex behaviour, and its relevance for EEG activity will be illustrated. The existence of short-lived unstable brain states will also be discussed in terms of the available theoretical and experimental results. A perspective on future analysis will conclude the presentation.

Evaluation of water properties in HEA–HEMA hydrogels swollen in aqueous-PEG solutions using thermoanalytical techniques

Hydrogels are polymeric materials used in many pharmaceutical and biomedical applications due to their ability to form 3D hydrophilic polymeric networks, which can absorb large amounts of water. In the present work, polyethylene glycols (PEG) were introduced into the hydrogel liquid phase in order to improve the mechanical properties of hydrogels composed of 2-hydroxyethylacrylate and 2-hydroxyethylmethacrylate (HEA–HEMA) synthesized with different co-monomer compositions and equilibrated in water or in 20 % water–PEG 400 and 600 solutions. The thermoanalytical techniques [differential scanning calorimetry (DSC) and thermogravimetry (TG)] were used to evaluate the amount and properties of free and bound water in HEA–HEMA hydrogels. The internal structure and the mechanical properties of hydrogels were studied using scanning electron microscopy and friability assay. TG “loss-on-drying” experiments were applied to study the water-retention properties of hydrogels, whereas the combination of TG and DSC allowed estimating the total amount of freezable and non-freezing water in hydrogels. The results show that the addition of viscous co-solvent (PEG) to the liquid medium results in significant improvement of the mechanical properties of HEA–HEMA hydrogels and also slightly retards the water loss from the hydrogels. A redistribution of free and bound water in the hydrogels equilibrated in mixed solutions containing 20 vol% of PEGs takes place.

Lipopeptides: from self-assembly to bioactivity

This Feature Article discusses several classes of lipopeptide with important biomedical applications as antimicrobial and antifungal agents, in immune therapies and in personal care applications among others. Two main classes of lipopeptide are considered: (i) bacterially-expressed lipopeptides with a cyclic peptide headgroup and (ii) linear lipopeptides (with one or more lipid chains) based on bio-derived and bio-inspired amino acid sequences with current clinical applications. The applications are briefly summarized, and the biophysical characterization of the molecules is reviewed, with a particular focus on self-assembly. For several of these types of biomolecule, the formation of micelles above a critical micelle concentration has been observed while others form bilayer structures, depending on conditions of pH and temperature. As yet, there are few studies on the possible relationship between self-assembly into structures such as micelles and bioactivity of this class of molecule although this is likely to attract further attention.

Enzymatically-triggered, isothermally responsive polymers: re-programming poly(oligoethylene glycols) to respond to phosphatase

Polymers which can respond to externally applied stimuli have found much application in the biomedical field due to their (reversible) coil–globule transitions. Polymers displaying a lower critical solution temperature are the most commonly used, but for blood-borne (i.e., soluble) biomedical applications the application of heat is not always possible, nor practical. Here we report the design and synthesis of poly(oligoethylene glycol methacrylate)-based polymers whose cloud points are easily varied by alkaline phosphatase-mediated dephosphorylation. By fine-tuning the density of phosphate groups on the backbone, it was possible to induce an isothermal transition: A change in solubility triggered by removal of a small number of phosphate esters from the side chains activating the LCST-type response. As there was no temperature change involved, this serves as a model of a cell-instructed polymer response. Finally, it was found that both polymers were non cytotoxic against MCF-7 cells (at 1 mg·mL–1), which confirms promise for biomedical applications.

An adhesive elastomeric supramolecular polyurethane healable at body temperature

In this paper, we report the synthesis and healing ability of a non-cytotoxic supramolecular polyurethane network whose mechanical properties can be recovered efficiently (> 99%) at the temperature of the human body (37 ºC). Rheological analysis revealed an acceleration in the drop of the storage modulus above 37 ºC, on account of the dissociation of the supramolecular polyurethane network, and this decrease in viscosity enables the efficient recovery of the mechanical properties. Microscopic and mechanical characterisation has shown that this material is able to recover mechanical properties across a damage site with minimal contact required between the interfaces and also demonstrated that the mechanical properties improved when compared to other low temperature healing elastomers or gel-like materials. The supramolecular polyurethane was found to be non-toxic in a cytotoxicity assay carried out in human skin fibroblasts (cell viability > 94% and non-significantly different compared to the untreated control). This supramolecular network material also exhibited excellent adhesion to pig skin and could be healed completely in situ post damage indicating that biomedical applications could be targeted, such as artificial skin or wound dressings with supramolecular materials of this type.

Complex extreme learning machine applications in terahertz pulsed signals feature sets

This paper presents a novel approach to the automatic classification of very large data sets composed of terahertz pulse transient signals, highlighting their potential use in biochemical, biomedical, pharmaceutical and security applications. Two different types of THz spectra are considered in the classification process. Firstly a binary classification study of poly-A and poly-C ribonucleic acid samples is performed. This is then contrasted with a difficult multi-class classification problem of spectra from six different powder samples that although have fairly indistinguishable features in the optical spectrum, they also possess a few discernable spectral features in the terahertz part of the spectrum. Classification is performed using a complex-valued extreme learning machine algorithm that takes into account features in both the amplitude as well as the phase of the recorded spectra. Classification speed and accuracy are contrasted with that achieved using a support vector machine classifier. The study systematically compares the classifier performance achieved after adopting different Gaussian kernels when separating amplitude and phase signatures. The two signatures are presented as feature vectors for both training and testing purposes. The study confirms the utility of complex-valued extreme learning machine algorithms for classification of the very large data sets generated with current terahertz imaging spectrometers. The classifier can take into consideration heterogeneous layers within an object as would be required within a tomographic setting and is sufficiently robust to detect patterns hidden inside noisy terahertz data sets. The proposed study opens up the opportunity for the establishment of complex-valued extreme learning machine algorithms as new chemometric tools that will assist the wider proliferation of terahertz sensing technology for chemical sensing, quality control, security screening and clinic diagnosis. Furthermore, the proposed algorithm should also be very useful in other applications requiring the classification of very large datasets.